53 Llm Apis Jobs

As a Lead Engineer GenAI at Verisk, you will be responsible for developing and maintaining GenAI systems, ensuring they are robust, secure, and performant. Your role will involve leveraging advanced knowledge of Python open-source software stack, such as Django or Flask, and developing innovative solutions using GenAI technologies. Your qualifications and responsibilities include: Key Responsibilities: - Lead the implementation of GenAI systems, ensuring robustness, security, and performance - Develop scalable and efficient GenAI solutions tailored to specific requirements - Work on all aspects of enterprise-scale implementation for AI/GenAI solutions, including architecture, design, security, and infrastructure - Interact with business partners or customers, and guide project direction - Lead technical meetings and provide guidance on design Qualifications Required: - 8+ years of proven experience in software development and system maintenance - Highly experienced with N-tiered applications, multi-tier architecture, and scalable system design - Proficiency in Python open-source software stack and GenAI technologies - AWS experience preferred - Experience with RAG technologies, LLM frameworks, and LLM model registries - Strong understanding of object-oriented design concepts and software development processes - Excellent organization skills and ability to recognize priorities About Verisk: Verisk has been a leading data analytics and technology partner to the global insurance industry for over 50 years. They empower communities and businesses to make better decisions on risk faster. Verisk values inclusivity, diversity, learning, and caring, and is recognized as a Great Place to Work for its outstanding workplace culture. With a focus on innovation and ethical pursuit, Verisk offers a unique and rewarding career experience with work flexibility and support for personal growth. Verisk Businesses: - Underwriting Solutions - Claims Solutions - Property Estimating Solutions - Extreme Event Solutions - Specialty Business Solutions - Marketing Solutions - Life Insurance Solutions - Verisk Maplecroft Join Verisk and be part of a team that translates big data into big ideas, creating a better tomorrow for future generations in an exceptional work environment. Verisk Analytics is an equal opportunity employer. For more information and to explore career opportunities with Verisk, visit their [careers page](https://www.verisk.com/company/careers/).,

Role Overview: You will be leading a high-impact engineering team in Abu Dhabi for a fast-scaling AI infrastructure startup. As the Technical Team Lead, you will have the opportunity to shape the technical culture, build a local team from scratch, and drive projects that involve LLMs, AI agents, and Retrieval-Augmented Generation (RAG) systems used globally. Key Responsibilities: - Build, mentor, and lead a growing engineering team in Abu Dhabi consisting of 3-10 members - Take ownership of delivering high-impact technical initiatives related to AI infrastructure, backend systems, and developer tooling - Serve as the technical liaison between the teams in Abu Dhabi, Tel Aviv, and NYC to ensure smooth collaboration - Be actively involved in coding tasks while also leading architectural decisions, sprint planning, and team development - Establish engineering best practices and cultivate a high-performance culture in a rapidly expanding environment Qualifications Required: - 12-17 years of experience in backend, infrastructure, or machine learning domains - Demonstrated leadership skills with at least 8 years of experience managing engineering teams in fast-paced environments - Proficiency in Python, FastAPI, and cloud-native systems such as AWS, Docker, and Kubernetes, along with CI/CD knowledge - Deep expertise in AI agent frameworks, LangChain, vector databases, and modern LLM APIs - Strong passion for fostering team collaboration, maintaining technical excellence, and coordinating across different time zones Additional Details (If available): The company is already generating over $3M in annual recurring revenue, serving more than 200,000 users, and has garnered over 5 million downloads. The tech environment includes backend technologies like Python and FastAPI, infrastructure tools like AWS, Docker, and Kubernetes, AI stack components such as LangChain, Pinecone/Weaviate, OpenAI, and Anthropic, and DevOps practices using GitHub Actions and CI/CD pipelines. The primary focus areas are developer tools, AI agents, and real-time search APIs. If you are a hands-on technical leader eager to make a significant impact at the intersection of AI and engineering scale, this role offers you the chance to become the face of engineering in a strategic location, work in a startup with impressive user metrics, and contribute to shaping a global tech presence from the ground up.,

Inviting applications for the role of Senior Principal Consultant - ML Engineers! In this role, lead the automation and orchestration of our machine learning infrastructure and CI/CD pipelines on public cloud (preferably AWS). This role is essential for enabling scalable, secure, and reproducible deployments of both classical AI/ML models and Generative AI solutions in production environments. Responsibilities . Develop and maintain CI/CD pipelines for AI/GenAI models on AWS using GitHub Actions and CodePipeline. (Not Limited to) . Automate infrastructure provisioning using IAC. (Terraform, Bicep Etc) . Any cloud platform- Azure or AWS . Package and deploy AI/GenAI models on (SageMaker, Lambda, API Gateway). . Write Python scripts for automation, deployment, and monitoring. . Engaging in the design, development and maintenance of data pipelines for various AI use cases . Active contribution to key deliverables as part of an agile development team . Set up model monitoring, logging, and alerting (e.g., drift, latency, failures). . Ensure model governance, versioning, and traceability across environments. . Collaborating with others to source, analyse, test and deploy data processes . Experience in GenAI project Qualifications we seek in you! Minimum Qualifications experience with MLOps practices. . Degree/qualification in Computer Science or a related field, or equivalent work experience . Experience developing, testing, and deploying data pipelines Strong Python programming skills. Hands-on experience in deploying 2 - 3 AI/GenAI models in AWS. Familiarity with LLM APIs (e.g., OpenAI, Bedrock) and vector databases. . Clear and effective communication skills to interact with team members, stakeholders and end users Preferred Qualifications/ Skills . Experience with Docker-based deployments. . Exposure to model monitoring tools (Evidently, CloudWatch). . Familiarity with RAG stacks or fine-tuning LLMs. . Understanding of GitOps practices. . Knowledge of governance and compliance policies, standards, and procedures . . . . .

Role Overview: You will have the opportunity to lead a high-impact engineering team based in Abu Dhabi for a fast-scaling AI infrastructure startup. As the Technical Team Lead, you will play a crucial role in shaping the technical culture, building the local team, and driving projects that support LLMs, AI agents, and Retrieval-Augmented Generation (RAG) systems used globally. Key Responsibilities: - Build, mentor, and lead a growing engineering team of 3-10 members in Abu Dhabi - Take ownership of delivering high-impact technical initiatives related to AI infrastructure, backend systems, and developer tooling - Serve as the technical bridge between Abu Dhabi, Tel Aviv, and NYC teams to ensure seamless collaboration - Be actively involved in coding tasks, drive architectural decisions, oversee sprint planning, and foster team growth - Establish engineering best practices and promote a high-performance culture in a rapidly scaling environment Qualifications Required: - 8-12 years of experience in backend, infrastructure, or machine learning domains - Demonstrated leadership skills with at least 3 years of experience managing engineering teams in fast-paced environments - Proficiency in Python, FastAPI, cloud-native systems (AWS, Docker, Kubernetes), and CI/CD practices - Deep expertise in AI agent frameworks, LangChain, vector databases, and modern LLM APIs - Strong passion for team-building, technical excellence, and coordination across different time zones Additional Details: The company's tech environment includes backend technologies like Python and FastAPI, infrastructure tools such as AWS, Docker, Kubernetes, AI Stack components like LangChain, Pinecone/Weaviate, OpenAI, Anthropic, and DevOps tools like GitHub Actions and CI/CD pipelines. The focus is on developer tools, AI agents, and real-time search APIs. If you are a hands-on technical leader seeking to make a significant impact at the convergence of AI and engineering scale, this role offers the chance to be the face of engineering in a strategic location, work in a startup with impressive metrics, and shape a global tech presence from the ground up.,

As an experienced AI Architect, your role will involve leading the design, development, and deployment of large-scale AI solutions. You will be responsible for bridging the gap between business requirements and technical implementation, with a focus on generative AI and modern MLOps practices. Key Responsibilities: - Architect end-to-end AI systems utilizing large language models and generative AI technologies - Design scalable, production-ready AI applications that align with business objectives and performance requirements - Evaluate and integrate LLM APIs from leading providers such as OpenAI, Anthropic Claude, and Google Gemini - Establish best practices for prompt engineering, model selection, and AI system optimization - Fine-tune open-source models like Llama and Mistral for specific business use cases - Implement custom training pipelines and evaluation frameworks - Optimize model performance, latency, and cost for production environments - Stay updated with the latest model architectures and fine-tuning techniques - Deploy and manage AI models at an enterprise scale using containerization (Docker) and orchestration (Kubernetes) - Build robust, scalable APIs using FastAPI and similar frameworks - Design and implement MLOps pipelines for model versioning, monitoring, and continuous deployment - Ensure high availability, security, and performance of AI systems in production - Collaborate with stakeholders to understand business problems and translate them into technical requirements - Provide technical guidance and mentorship to development teams - Conduct feasibility assessments and technical due diligence for AI initiatives - Create technical documentation, architectural diagrams, and implementation roadmaps Required Qualifications: - 7+ years of experience in machine learning engineering or data science - Proven track record of delivering large-scale ML solutions Technical Skills: - Expert-level proficiency with LLM APIs (OpenAI, Claude, Gemini, etc.) - Hands-on experience fine-tuning transformer models (Llama, Mistral, etc.) - Strong proficiency in FastAPI, Docker, and Kubernetes - Experience with ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers) - Proficiency in Python and modern software development practices - Experience with cloud platforms (AWS, GCP, or Azure) and their AI/ML services Core Competencies: - Strong understanding of transformer architectures, attention mechanisms, and modern NLP techniques - Experience with MLOps tools and practices (model versioning, monitoring, CI/CD) - Ability to translate complex business requirements into technical solutions - Strong problem-solving skills and architectural thinking Preferred Qualifications: - Experience with vector databases and retrieval-augmented generation (RAG) systems - Knowledge of distributed training and model parallelization techniques - Experience with model quantization and optimization for edge deployment - Familiarity with AI safety, alignment, and responsible AI practices - Experience in specific domains (finance, healthcare, legal, etc.) - Advanced degree in Computer Science, AI/ML, or related field,

As a Python Developer with 1-2 years of experience, you will be responsible for designing and developing core modules of the AI Agent SDK in Python. Your role will include integrating and optimizing Speech-to-Text (STT), Language Model (LLM), and Text-to-Speech (TTS) pipelines to ensure real-time performance. You will work with APIs from various providers like OpenAI, Anthropic, Deepgram, AssemblyAI, Whisper, ElevenLabs, and others. Your key responsibilities will involve implementing efficient data structures and algorithms for streaming, concurrency, and low-latency AI interactions. Collaboration with frontend/mobile SDK teams (JS, React Native, Android, iOS) will be essential to ensure smooth integrations. Additionally, you will be tasked with building and maintaining unit tests, CI/CD pipelines, and documentation for SDK releases. Optimizing memory usage, error handling, and network performance for production-ready deployments will be part of your daily tasks. You will also be required to conduct research and experiments with the latest AI models, open-source tools, and SDK best practices to stay updated in the field. To excel in this role, you should have at least 1 year of experience in Python development with a strong focus on core concepts such as Object-Oriented Programming (OOP), asynchronous programming, multithreading, and multiprocessing. Hands-on experience with LLM APIs like OpenAI, Anthropic, and Llama is necessary. Previous experience with STT engines such as Whisper and TTS engines like ElevenLabs and Azure Speech is preferred. A solid understanding of WebSockets, gRPC, REST APIs, and real-time streaming is required. Proficiency in data handling, serialization (JSON, Protobuf), and message queues is expected. Familiarity with AI frameworks/libraries like PyTorch, Hugging Face Transformers, and LangChain would be beneficial. Experience in SDK development, packaging, and distribution, including PyPI, wheels, and versioning, is essential. Comfort working in Linux/macOS development environments is necessary, along with a good understanding of testing using tools like pytest, code quality, and performance profiling. Experience with Docker, Kubernetes, cloud deployments (AWS/GCP/Azure), and knowledge of WebRTC, audio codecs, or real-time communication protocols are considered nice-to-have skills.,

You are a skilled AI Engineer with 3 to 6 years of experience in LLM integration, platform observability, performance optimization, and API development. Your primary responsibility will involve enhancing critical platform features, including LLM API integrations, observability pipelines, structured search algorithms, and performance scaling for the AI platform and related components. You must have a minimum of 3 to 6 years of experience in AI/ML engineering or platform development. Previous exposure to AI observability or model evaluation pipelines will be beneficial. Your knowledge should include Agentic AI frameworks, multi-step reasoning systems, and programming languages like Python (mandatory) and Node.js/Java (desirable). Your expertise in AI/ML Integration is crucial, with hands-on experience in LLM APIs such as OpenAI and Vertex AI. Understanding observability and logging practices with tools like Splunk, OpenTelemetry (OTel), and Arize AI is necessary. Proficiency in Testing & CI/CD using tools like Postman, PyTest, and Docker Compose is expected. Exposure to structured search techniques using technologies like Neo4j, LightRAG, and Graph DBs is advantageous. You should be familiar with memory profiling, performance optimization, and scaling techniques. Strong knowledge of Cloud Platforms such as GCP (Vertex AI), Azure, or AWS is preferred. Experience with collaboration tools like GitHub, Jira, and Confluence will be an added advantage. If you meet these requirements and are passionate about AI engineering, this role offers a challenging opportunity to work on cutting-edge AI technologies.,

Job Description SDE I :: AI Engineer About Uniqus Consultech Uniqus Consultech is a global tech-enabled consulting company specializing in Accounting & Reporting, ESG, and Tech Consulting. Founded in December 2022 by consulting veterans and backed by marquee investors like Nexus Venture Partners and Sorin Investments, we operate across the USA, India, and the Middle East with 400+ professionals serving 200+ leading clients. Were in hypergrowth mode and so is our engineering team. Role Overview We are looking for a talented Software Development Engineer (SDE-1) to join our high-velocity AI engineering team. Youll work closely with AI Engineers and Product Managers to build cutting-edge AI-powered applications, integrating LLMs and agentic workflows into scalable products. If you love moving fast, leveraging AI tools for 10x output, and shipping impactful features, this is your place. Location - Bangalore, Mumbai & Gurgaon Key Responsibilities Build and integrate AI-first features, leveraging LLM APIs, LangChain, and related frameworks. Develop backend services (Node.js, FastAPI) and frontend applications (React, Next.js) for AI-powered products. Collaborate closely with AI Engineers and PMs to design, develop, and deploy features. Leverage AI coding assistants (ChatGPT, Claude, Cursor, etc.) for rapid prototyping and delivery. Contribute to robust data pipelines and scalable system architecture. Continuously learn and apply new AI frameworks, tools, and APIs. Technical Skills AI/ML: LLM APIs (OpenAI, Anthropic), LangChain, agentic workflows. Backend: Node.js, FastAPI, REST/GraphQL APIs. Frontend: React.js, Next.js (nice-to-have). Databases: PostgreSQL, MongoDB, Redis. Tooling & Deployment: Docker, Git, AWS/GCP. Strong understanding of modern web architecture. Qualifications 13 years of experience in software development (AI exposure preferred). Bachelor&aposs degree in Computer Science, Software Engineering, or related field. Proven ability to learn fast and adapt in a high-paced environment. Passion for AI applications and using AI tools to supercharge productivity. Why Join Us At Uniqus, youll work in a high-velocity, high-growth environment where AI is not an experiment its our core. Youll get to: Build real-world AI applications used by global enterprises. Collaborate with top-tier engineers and product leaders. Leverage the best AI tools to 10x your output. Grow alongside a company backed by some of the best investors in the industry. Show more Show less

SDE II AI Engineer About Uniqus Consultech Uniqus Consultech is a global tech-enabled consulting company specializing in Accounting & Reporting, ESG, and Tech Consulting. Founded in December 2022 by consulting veterans and backed by marquee investors like Nexus Venture Partners and Sorin Investments, we operate across the USA, India, and the Middle East with 400+ professionals serving 200+ leading clients. Were in hypergrowth mode and so is our engineering team. Role Overview We are seeking an experienced Software Development Engineer (SDE-2) to design and lead modules for our AI-powered product initiatives. This is a high-impact role where youll work at the intersection of AI engineering and full-stack development, collaborating closely with AI Engineers and Product Managers. Youll be expected to own architecture decisions, mentor junior developers, and deliver production-grade AI integrations at scale. Key Responsibilities Lead the design and development of AI-first product modules. Architect and implement backend services (Node.js, FastAPI) and integrate AI workflows using LLM APIs, LangChain, and other frameworks. Collaborate with AI Engineers and PMs to scope, design, and ship high-value features quickly. Optimize system performance and scalability for AI-heavy workloads. Mentor junior engineers and drive code quality best practices. Leverage AI coding assistants (ChatGPT, Claude, Cursor, etc.) to accelerate delivery without compromising quality. Technical Skills AI/ML: Strong experience with LLM APIs, LangChain, agentic workflows, and AI pipeline development. Backend: Node.js, FastAPI, REST/GraphQL APIs. Frontend: React.js, Next.js (beneficial). Databases: PostgreSQL, MongoDB, Redis. DevOps & Architecture: AWS/GCP, Docker, microservices, CI/CD pipelines. Qualifications 35 years of software development experience with at least 2 years in AI-related projects. Strong system design and architectural skills. Proven track record of delivering complex features from concept to production. Bachelor&aposs degree in Computer Science, Software Engineering, or related field. Ability to thrive in a high-paced, high-growth startup environment. Why Join Us At Uniqus, youll work in a high-velocity, high-growth environment where AI is not an experiment its our core. Youll get to: Build real-world AI applications used by global enterprises. Collaborate with top-tier engineers and product leaders . Leverage the best AI tools to 10x your output. Grow alongside a company backed by some of the best investors in the industry . Show more Show less

As an AI Developer specializing in Natural Language Processing (NLP) and Large Language Models (LLMs), you will have the opportunity to work remotely or in a hybrid setting. In this role, whether on a full-time or contract basis, your responsibilities will revolve around developing AI-driven conversational agents using LangChain and LangGraph. You will collaborate with various LLMs such as OpenAI, Claude, and Llama, fine-tuning and customizing models to meet project requirements. Additionally, you will be tasked with implementing vector search functionalities using databases like Milvus, MongoDB, or other relevant platforms. Integration of AI models into the backend of the platforms and optimizing their performance will be a crucial aspect of your work. Furthermore, active collaboration with front-end and back-end teams is essential to enhance the overall AI functionalities of the project. To excel in this role, you should possess a strong background in utilizing LangChain, LangGraph, and OpenAI/LLM APIs. Proficiency in programming languages such as Python, along with experience in working with PyTorch, TensorFlow, and fine-tuning transformer models, will be valuable assets. Your familiarity with vector databases like Milvus, Pinecone, Weaviate, or MongoDB Atlas will play a significant role in your day-to-day tasks. Knowledge of prompt engineering, RAG (Retrieval-Augmented Generation), and embeddings is highly desirable, alongside experience in API development and integration. Additionally, any prior exposure to cloud platforms such as AWS, GCP, or Azure will be considered advantageous. This position welcomes freshers who are eager to learn and contribute to the field of AI development, particularly in NLP and LLMs. If you are enthusiastic about leveraging advanced technologies to create innovative solutions, this role offers a stimulating environment to grow and excel in the realm of AI development.,

About Delta Tech Hub: Delta Air Lines (NYSE: DAL) is the U.S. global airline leader in safety, innovation, reliability and customer experience. Powered by our employees around the world, Delta has for a decade led the airline industry in operational excellence while maintaining our reputation for award-winning customer service. With our mission of connecting the people and cultures of the globe, Delta strives to foster understanding across a diverse world and serve as a force for social good. Delta has fast emerged as a customer-oriented, innovation-led, technology-driven business. The Delta Technology Hub will contribute directly to these objectives. It will sustain our long-term aspirations of delivering niche, IP-intensive, high-value, and innovative solutions. It supports various teams and functions across Delta and is an integral part of our transformation agenda, working seamlessly with a global team to create memorable experiences for customers. KEY RESPONSIBILITIES: Assist in the design and implementation of AI models and systems, contributing fresh ideas and approaches to the team&aposs efforts. Translate software requirements into working and maintainable solutions within the existing application frameworks. Participate in the full lifecycle of application, including design, coding, testing, implementation, deployment as well as support and maintenance. Develop and adhere to best practices for developing applications. Ensure optimization across all platforms including mobile-friendly UI/UX. Collaborate with other developers to implement AI solutions effectively. Effectively analyze a problem/task to give accurate timelines for milestones and full implementation completion. Experience in developing frameworks with AI. WHAT YOU NEED TO SUCCEED (MINIMUM QUALIFICATIONS): Bachelors degree in data science, statistics, mathematics, computer science or engineering discipline, or equivalent experience 3+ years of work/educational experience leading development of Machine Learning, prompt engineering, data analysis and Artificial Intelligence 2+ years of experience with production-grade design, deployment and implementation of AI models and systems, contributing fresh ideas and approaches to the team&aposs efforts. Experience with one or more general purpose programming languages including but not limited to: Java, Python, R or equivalent Experience and knowledge in designing, building, and deploying multi layered application Infrastructure involving On-premises & AWS Cloud platform using services BedRock LLM models. You enjoy working with people and can put yourself in other people&aposs shoes. You&aposre not afraid to ask for help when you need it or help teammates when they need a boost. Embraces diverse people, thinking, and styles Consistently makes safety and security, of self and others, the priority Experience with one or more of the following: Natural Language Processing, sentiment analysis, classification, pattern recognition Consistently makes safety and security, of self and others, the priority. WHAT WILL GIVE YOU A COMPETITIVE EDGE (PREFERRED QUALIFICATIONS): Experience with Generative AI models and frameworks such as OpenAIs GPT family of models, open-source LLMs, and LangChain. Development and debugging experience with AI frameworks such as PyTorch and SQLite DB. Automate prompt execution, result validation, and error handling to enhance reliability. Experience in working with LLM APIs and Web UI. Experience in designing data models for cloud-based solutions from leading cloud providers such as AWS (Amazon Web Services), Azure, etc. Self-motivated and take pride in building great experiences for users, whether they are employees or customers. Resourceful in finding the data and tools you need to get the job done Not afraid to ask for help when you need it, or help teammates when they need a boost Intensely curious about finding a solution to the pain-points of our customers throughout the entire travel experience. Show more Show less

The ideal candidate for this role has successfully developed data and analytics solutions, with a strong understanding of best practices in data modeling, data engineering, and AI products. To thrive in this position, you should enjoy working in a highly collaborative, cross-functional team environment. This role offers promising growth opportunities in both technology and management tracks. If you are an experienced Python engineer who excels at solving complex problems, is passionate about technology and coding, and has a knack for building and leading high-performing teams, then this could be the perfect opportunity for you! Key responsibilities include: - Demonstrating 4-10 years of proven experience and proficiency with Python - Possessing expertise in Python and associated libraries, as well as RESTful API development - Developing and designing scalable and efficient GenAI solutions tailored to specific requirements, ensuring robustness, security, and performance - Working on all aspects of enterprise-scale implementation for AI/GenAI solutions, including architecture, design, security, infrastructure, and MLOps/GenAIOps - Familiarity with RAG technologies and LLM frameworks, including LLM model registries, APIs, embedding models, and vector databases - Knowledge of cloud platforms (such as AWS), databases, system design, building data pipelines, Git, CI/CD, and Linux is a plus - Experience or hands-on exposure to AI and ML concepts, engineering techniques to optimize GenAI performance, and evaluation and selection of appropriate models and frameworks - Designing and developing components and systems from the ground up using engineering best practices and design patterns - Continuous learning and adaptation to evolving technologies - Strong understanding of object-oriented design concepts, software development processes, and methods - Leading teams, collaborating with business partners or customers, and guiding project direction - Exceptional organizational skills, with the ability to prioritize tasks and keep the team focused on critical features - Leadership qualities and the ability to lead technical and design working sessions - Proven ability to work independently with minimal supervision Verisk, a leading data analytics and technology partner to the global insurance industry for over 50 years, values inclusivity, diversity, and workplace culture. As an equal opportunity employer, Verisk offers a unique and rewarding career opportunity with work flexibility, support, coaching, and training for personal and professional growth. Join a team of 7,000 individuals who relentlessly pursue innovation and help translate big data into impactful ideas for a better future. Verisk Businesses: - Underwriting Solutions: Provides underwriting and rating solutions for assessing and pricing risk - Claims Solutions: Supports end-to-end claims handling with analytic and automation tools - Property Estimating Solutions: Offers property estimation software for efficient workflows - Extreme Event Solutions: Provides risk modeling solutions for resilience to extreme events - Specialty Business Solutions: Delivers an integrated suite of software for insurance and reinsurance business management - Marketing Solutions: Delivers data and insights for improved consumer engagement - Life Insurance Solutions: Offers data insight-driven capabilities for life and annuities policies - Verisk Maplecroft: Provides intelligence on sustainability, resilience, and ESG for societal strength Verisk Analytics is committed to creating a diverse and inclusive workplace. To explore career opportunities at Verisk, visit [Verisk Careers](https://www.verisk.com/company/careers/).,

About the Role We are seeking a highly skilled and experienced Senior AI Engineer to lead the design, development, and implementation of robust and scalable pipelines and backend systems for our Generative AI applications. In this role, you will be responsible for orchestrating the flow of data, integrating AI services, developing RAG pipelines, working with LLMs, and ensuring the smooth operation of the backend infrastructure that powers our Generative AI solutions. You will also be expected to apply modern LLMOps practices, handle schema-constrained generation, optimize cost and latency trade-offs, mitigate hallucinations, and ensure robust safety, personalization, and observability across GenAI systems. Responsibilities Generative AI Pipeline Development Design and implement scalable and modular pipelines for data ingestion, transformation, and orchestration across GenAI workloads. Manage data and model flow across LLMs, embedding services, vector stores, SQL sources, and APIs. Build CI/CD pipelines with integrated prompt regression testing and version control. Use orchestration frameworks like LangChain or LangGraph for tool routing and multi-hop workflows. Monitor system performance using tools like Langfuse or Prometheus. Data and Document Ingestion Develop systems to ingest unstructured (PDF, OCR) and structured (SQL, APIs) data. Apply preprocessing pipelines for text, images, and code. Ensure data integrity, format consistency, and security across sources. AI Service Integration Integrate external and internal LLM APIs (OpenAI, Claude, Mistral, Qwen, etc.). Build internal APIs for smooth backend-AI communication. Optimize performance through fallback routing to classical or smaller models based on latency or cost budgets. Use schema-constrained prompting and output filters to suppress hallucinations and maintain factual accuracy. Retrieval-Augmented Generation (RAG) Pipelines Build hybrid RAG pipelines using vector similarity (FAISS/Qdrant) and structured data (SQL/API). Design custom retrieval strategies for multi-modal or multi-source documents. Apply post-retrieval ranking using DPO or feedback-based techniques. Improve contextual relevance through re-ranking, chunk merging, and scoring logic. LLM Integration and Optimization Manage prompt engineering, model interaction, and tuning workflows. Implement LLMOps best practices: prompt versioning, output validation, caching (KV store), and fallback design. Optimize generation using temperature tuning, token limits, and speculative decoding. Integrate observability and cost-monitoring into LLM workflows. Backend Services Ownership Design and maintain scalable backend services supporting GenAI applications. Implement monitoring, logging, and performance tracing. Build RBAC (Role-Based Access Control) and multi-tenant personalization. Support containerization (Docker, Kubernetes) and autoscaling infrastructure for production. Required Skills and Qualifications Education Bachelors or Masters in Computer Science, Artificial Intelligence, Machine Learning, or related field. Experience 5+ years of experience in AI/ML engineering with end-to-end pipeline development. Hands-on experience building and deploying LLM/RAG systems in production. Strong experience with public cloud platforms (AWS, Azure, or GCP). Technical Skills Proficient in Python and libraries such as Transformers, SentenceTransformers, PyTorch. Deep understanding of GenAI infrastructure, LLM APIs, and toolchains like LangChain/LangGraph. Experience with RESTful API development and version control using Git. Knowledge of vector DBs (Qdrant, FAISS, Weaviate) and similarity-based retrieval. Familiarity with Docker, Kubernetes, and scalable microservice design. Experience with observability tools like Prometheus, Grafana, or Langfuse. Generative AI Specific Skills Knowledge of LLMs, VAEs, Diffusion Models, GANs. Experience building structured + unstructured RAG pipelines. Prompt engineering with safety controls, schema enforcement, and hallucination mitigation. Experience with prompt testing, caching strategies, output filtering, and fallback logic. Familiarity with DPO, RLHF, or other feedback-based fine-tuning methods. Soft Skills Strong analytical, problem-solving, and debugging skills. Excellent collaboration with cross-functional teams: product, QA, and DevOps. Ability to work in fast-paced, agile environments and deliver production-grade solutions. Clear communication and strong documentation practices. Preferred Qualifications Experience with OCR, document parsing, and layout-aware chunking. Hands-on with MLOps and LLMOps tools for Generative AI. Contributions to open-source GenAI or AI infrastructure projects. Knowledge of GenAI governance, ethical deployment, and usage controls. Experience with hallucination suppression frameworks like Guardrails.ai, Rebuff, or Constitutional AI. Experience and Shift Shift Time: 2:30 PM to 11:30 PM IST Location: Remote- Bengaluru,Hyderabad,Delhi / NCR,Chennai,Pune,Kolkata,Ahmedabad,Mumbai

As a part of Cowbell's innovative team in the field of cyber insurance, you will play a crucial role in designing and implementing RAG-based systems, integrating LLMs with vector databases, search pipelines, and knowledge retrieval frameworks. Your responsibilities will include developing intelligent AI agents that automate tasks, retrieve relevant information, and enhance user interactions. You will work with APIs, embeddings, and multi-modal retrieval techniques to improve the performance of AI applications. Additionally, you will be tasked with optimizing inference pipelines and enhancing LLM serving, fine-tuning, and distillation for efficiency. Staying abreast of the latest advancements in generative AI and retrieval techniques will be essential, along with collaborating with stakeholders and cross-functional teams to address business needs and develop impactful ML models and AI-driven automation solutions. The ideal candidate for this position should hold a Master's degree in Computer Science, Data Science, AI, Machine Learning, or a related field (or a Bachelor's degree with significant experience). You should have at least 5 years of experience in machine learning, deep learning, and NLP for real-world applications, as well as a minimum of 1 year of hands-on experience with LLMs and generative AI. Expertise in RAG architectures, vector search, and retrieval methods is required, along with proficiency in Python and experience with LLM APIs such as OpenAI, Hugging Face, Anthropic, etc. Experience in integrating LLMs into real-world applications, solid foundation in machine learning, statistical modeling, and AI-driven software development, as well as knowledge of prompt engineering, few-shot learning, and prompt chaining techniques are also preferred qualifications. Strong software engineering skills, including experience with cloud platforms like AWS, and excellent problem-solving abilities, communication skills, and the capacity to work independently are crucial for this role. Preferred qualifications for the position include proficiency in PyTorch or TensorFlow for deep learning model development, experience in LLM fine-tuning, model compression, and optimization, familiarity with frameworks like LangChain, LlamaIndex, or Ollama, experience with multi-modal retrieval systems (text, image, structured data), and contributions to open-source AI projects or published research in AI/ML. At Cowbell, employees are offered an equity plan, wealth enablement plan for select customer-facing roles, comprehensive wellness program, meditation app subscriptions, lunch and learn sessions, a book club, happy hours, and more for professional development and growth opportunities. The company is committed to fostering a collaborative and dynamic work environment where transparency and resilience are valued, and every employee is encouraged to contribute and thrive. Cowbell is an equal opportunity employer, promoting diversity and inclusivity in the workplace and providing competitive compensation, comprehensive benefits, and continuous opportunities for professional development. To learn more about Cowbell and its mission in the cyber insurance industry, please visit https://cowbell.insure/.,

As a React Native Developer at HiAstro, you will have the opportunity to work in a well-funded Generative AI Startup that focuses on crafting exceptional, human-centered conversational experiences for consumers worldwide. Your role will involve developing, testing, and deploying React Native applications for the Google Play Store, working closely with Product Managers, Designers & Engineers to ship features, and maintaining app assets in Google Play. You will be responsible for optimizing app performance, troubleshooting/debugging issues, leading code reviews, and ensuring high code quality. The ideal candidate for this role will have a Bachelor's or Master's degree in Computer Science or related field from a reputable institution, along with 4+ years of professional experience in React Native development. You should also have 2+ years of experience with React Web and TypeScript, a solid grasp of Computer Science fundamentals, and experience working in consumer startups. Additionally, experience building with LLM APIs is highly preferred. Preferred qualifications include proficiency in React Native, React Navigation, React Query, Context API, React Native Firebase, and React Native UI/UX Component libraries. Experience implementing push notifications and A/B Testing, as well as knowledge of native iOS and Android development, are also desirable. Contributions to open-source software projects and experience with CI/CD workflows will be considered advantageous. Joining our team will allow you to play a key role in shaping a product that leverages cutting-edge AI technology to enhance user experiences for consumers in India and globally. You will work with a team committed to innovation and excellence in design, and be part of a startup where your contributions are valued, with ample opportunities for professional growth. If you are passionate about building cutting-edge AI applications and meet the qualifications mentioned above, we look forward to hearing from you!,

You are a highly skilled and innovative Senior Python Developer specializing in Generative AI and MLOps tools such as Argo Workflows and Kubernetes. Your role involves designing and deploying scalable GenAI applications, constructing robust pipelines, and integrating AI models into production environments. As a Python Developer, you will be responsible for designing, developing, and fine-tuning generative models like GPT, LLAMA, Mistral, FLAN, and T5. You will also build and optimize Retrieval-Augmented Generation (RAG) pipelines, implement model evaluation frameworks, and ensure responsible AI deployment. Your expertise in writing efficient, reusable, and testable Python code for AI/ML applications will be crucial in collaborating with data scientists to integrate models into scalable systems and maintaining high-performance Python applications for real-time inference. In the realm of MLOps and Infrastructure, you will develop and manage workflows using Argo Workflows for model training and deployment. Additionally, you will containerize applications using Docker, orchestrate deployments with Kubernetes, and monitor and optimize GPU usage on cloud platforms like AWS, Azure, and Databricks. Collaboration and Delivery are key aspects of your role, as you will work cross-functionally with engineering, product, and data teams to deliver AI solutions. You will interpret research papers and model architecture diagrams to guide implementation, ensuring timely delivery of AI projects with high reliability and scalability. To excel in this role, you should hold a Bachelors or Masters degree in Computer Science, AI/ML, or a related field, with at least 4+ years of experience in Python development and data science. Hands-on experience with LLM APIs, Hugging Face, transformer models, and proficiency in deep learning frameworks like PyTorch, TensorFlow, and Keras are essential. A strong understanding of Argo Workflows, Kubernetes, containerization, cloud platforms, GPU optimization, NLP tools, SQL, and Spark will be advantageous. Preferred experience includes fine-tuning models using LoRA, QLoRA, and quantization techniques, building multi-agent systems, multimodal applications, and knowledge of AI safety, ethics, and compliance. Join Tredence, a leading analytics partner dedicated to transforming data into actionable insights for Fortune 500 clients. With a global presence and a mission to drive unparalleled business value through advanced AI and data science, we welcome you to embark on this innovative journey with us.,

As a Senior Engineer - Agentic AI at Boston Scientific, you will have the opportunity to be at the forefront of innovation by harnessing the power of AI to revolutionize healthcare and provide cutting-edge solutions. Your role will involve architecting and implementing autonomous, goal-driven agents using large language models (LLMs) and multi-agent frameworks. Key Responsibilities: - Design and implement agentic AI systems that utilize LLMs for reasoning, multi-step planning, and tool execution. - Evaluate and enhance multi-agent frameworks like LangGraph, AutoGen, and CrewAI to coordinate distributed problem-solving agents effectively. - Develop context-handling, memory, and API-integration layers to enable agents to interact seamlessly with internal services and third-party tools. - Establish feedback-loop and evaluation pipelines (LangSmith, RAGAS, custom metrics) to measure factual grounding, safety, and latency. - Take ownership of backend services to scale agent workloads, optimize GPU/accelerator utilization, and ensure cost governance. - Integrate observability, drift monitoring, and alignment guardrails throughout the agent lifecycle. - Collaborate with research, product, and security teams to implement emerging agentic patterns into production-ready capabilities. - Mentor engineers on prompt engineering, tool-use chains, and best practices for agent deployment in regulated environments. Requirements: - Minimum of 8 years of software engineering experience, with at least 3 years dedicated to building AI/ML or NLP systems. - Proficiency in Python and modern LLM APIs (OpenAI, Anthropic, etc.), as well as agentic orchestration frameworks (LangGraph, AutoGen, CrewAI, LangChain, LlamaIndex). - Demonstrated success in delivering agentic systems or LLM-powered applications that interact with external APIs or tools. - Deep understanding of vector databases (Azure AI Search, Weaviate, Pinecone, FAISS, pgvector) and Retrieval-Augmented Generation (RAG) pipelines. - Hands-on experience with LLMOps, including CI/CD for fine-tuning, model versioning, performance monitoring, and drift detection. - Strong background in cloud-native micro-services, security, and observability. If you are a natural problem-solver with a passion for making a meaningful impact on a global scale, Boston Scientific welcomes your application. Join us in our mission to advance science for life by transforming lives through innovative medical solutions, supporting our employees, and contributing to the communities we serve. Apply now and be a part of a team dedicated to improving patient lives and creating value for our customers worldwide.,

Role & responsibilities Define and execute the AI/ML roadmap for personalized recommendation features. Develop and deploy ML models into production using tools like FastAPI, Docker, MLFlow , and Airflow . Build and optimize recommendation systems using collaborative filtering , content-based filtering , and knowledge-based techniques . Integrate agentic AI workflows using LLMs (OpenAI APIs, Vertex AI) and Retrieval-Augmented Generation (RAG). Work with structured and unstructured data including user behavior, travel logs, and merchant/product metadata. Use Perplexity-style LLM architectures to enhance explainability and product/merchant discovery. Collaborate across backend, frontend, and data engineering teams for end-to-end system integration . Ensure scalable and secure deployment on cloud platforms (AWS, GCP, or Azure). Preferred candidate profile 2 to 5 years of IT industry experience & min 2 years ML/AI model development, roadmap ownership, and production deployment. Proven experience deploying ML models with FastAPI, Docker, MLFlow , and Airflow . Strong hands-on expertise in Python , Pandas , scikit-learn , and recommendation libraries like LightFM or XGBoost . Solid understanding of recommender systems , including hybrid approaches combining collaborative and content-based filtering. Familiarity with agentic AI systems and LLM workflows (RAG, prompt engineering, conversational AI). Working knowledge of Vertex AI , OpenAI APIs , or Perplexity-style architectures for LLM-enhanced recommendations. Exposure to cloud environments (AWS/GCP/Azure) for training and serving ML models. Immediate availability is a must. Strong problem-solving skills, adaptability, and the ability to work independently in a fast-paced environment.

Exp -- 4+ Years Shift-- 2.00 PM to 11:30 PM IST Mandatory-- Python with LLM Ops Job Description-- We are looking for a hands-on AI Engineer with strong expertise in LLM integration, platform observability, performance optimization, and API development . The ideal candidate will work on critical platform enhancements, including LLM API integrations, observability pipelines, structured search algorithms, and performance scaling for customer&aposs AI platform and related components. You will collaborate with cross-functional teams to develop robust, scalable solutions, modernize our logging and monitoring infrastructure, and integrate advanced AI capabilities into production workflows. Key Responsibilities: 1. LLM Integration & API Development Develop and maintain LLM API integration test cases for core model availability. Refactor and reorganize LLM API code (e.g., __init__.py) for better maintainability. Add support for Vertex AI batch generation and batch transcription processing. Implement multi-step structured search algorithms and tie model IDs to relevant endpoints. Explore and integrate emerging technologies like LightRAG, SurrealDB, Neo4j, and Puppygraph for structured search. 2. Platform Observability & Performance Implement Splunk OpenTelemetry (OTel) integration for monitoring and metrics. Evaluate and integrate Arize AI for observability and model evaluation frameworks. Optimize logging decorators , memory profiling for unit tests, and enhance APM (Application Performance Monitoring) solutions. Drive scaling and performance optimization for the JedAI platform. 3. Platform Integration & Testing Implement platform integration and availability testing frameworks . Centralize Postman test cases for integration testing. Clean up outdated tests and modernize Docker Compose setups for KB API development. Develop harness configurations for automated testing pipelines. 4. Architecture & Research Spikes Support JedAI architecture consulting efforts. Conduct spike investigations on new technologies and frameworks for performance and scalability. Explore MCP design options for multi-agent orchestration and AI-enhanced workflows. Required Skills & Experience: Programming: Python (must-have), Node.js/Java (good to have) AI/ML Integration: Hands-on experience with LLM APIs (OpenAI, Vertex AI, etc.) Observability & Logging: Experience with Splunk, OpenTelemetry (OTel), Arize AI Testing & CI/CD: Proficiency with Postman, Pytest, Docker Compose Data & Search: Exposure to structured search techniques (Neo4j, LightRAG, Graph DBs) Performance Tuning: Familiarity with memory profiling, performance optimization, and scaling techniques Cloud Platforms: GCP (Vertex AI), Azure, or AWS experience preferred Collaboration Tools: GitHub, Jira, Confluence Preferred Qualifications: Bachelor&aposs or Master&aposs in Computer Science, AI/ML, or related fields 36 years of experience in AI/ML engineering or platform development Prior experience in AI observability or model evaluation pipelines Knowledge of Agentic AI frameworks and multi-step reasoning systems Show more Show less

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Principal Consultant - MLOps Engineer! In this role, lead the automation and orchestration of our machine learning infrastructure and CI/CD pipelines on public cloud (preferably AWS). This role is essential for enabling scalable, secure, and reproducible deployments of both classical AI/ML models and Generative AI solutions in production environments. Responsibilities Develop and maintain CI/CD pipelines for AI/ GenAI models on AWS using GitHub Actions and CodePipeline . (Not Limited to) Automate infrastructure provisioning using IAC. (Terraform, Bicep Etc) Any cloud platform - Azure or AWS Package and deploy AI/ GenAI models on (SageMaker, Lambda, API Gateway). Write Python scripts for automation, deployment, and monitoring. Engaging in the design, development and maintenance of data pipelines for various AI use cases Active contribution to key deliverables as part of an agile development team Set up model monitoring, logging, and alerting (e.g., drift, latency, failures). Ensure model governance, versioning, and traceability across environments. Collaborating with others to source, analyse , test and deploy data processes Experience in GenAI project Qualifications we seek in you! Minimum Qualifications experience with MLOps practices. Degree/qualification in Computer Science or a related field, or equivalent work experience Experience developing, testing, and deploying data pipelines Strong Python programming skills. Hands-on experience in deploying 2 - 3 AI/ GenAI models in AWS. Familiarity with LLM APIs (e.g., OpenAI, Bedrock) and vector databases. Clear and effective communication skills to interact with team members, stakeholders and end users Preferred Qualifications/ Skills Experience with Docker-based deployments. Exposure to model monitoring tools (Evidently, CloudWatch). Familiarity with RAG stacks or fine-tuning LLMs. Understanding of GitOps practices. Knowledge of governance and compliance policies, standards, and procedures Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

As a Senior Data Scientist, you will lead the development of scalable GenAI-powered systems, designing intelligent workflows that leverage large language models (LLMs), vector-based retrieval, and multi-agent orchestration frameworks. Youll drive solution architecture, mentor junior engineers, and deliver production-ready applications that integrate deeply with business processes and platforms. Key Responsibilities: Lead the design and deployment of GenAI systems leveraging LLMs, retrieval pipelines, and orchestration frameworks for multi-step task execution Architect and optimize prompt workflows, including chaining, templating, and context control, for high-accuracy and cost-efficient solutions Build and maintain embedding-based retrieval systems using vector databases and context-aware generation techniques (e.g., retrieval-augmented generation) Collaborate with product owners and engineering leads to align solution architecture with business objectives Guide and mentor junior engineers on best practices in prompt design, token optimization, security controls, and observability patterns Define standards for code modularity, response consistency, prompt safety, and testing across LLM-powered applications Maintain strong CI/CD practices using version-controlled workflows and cloud-native deployment pipelines Evaluate emerging GenAI tooling and provide technical recommendations for experimentation and adoption Qualifications 4+ years of experience in AI/ML solution delivery, with a strong focus on GenAI or LLM-integrated systems Expertise in Python (v3.11+) with deep familiarity in LLM APIs, embedding generation, vector-based search, and modular pipeline design Proven experience in building and deploying prompt-driven applications at scale Solid understanding of agent orchestration patterns, multi-agent task flows, and context layering techniques Hands-on experience in cloud-native delivery (preferably Azure), including containerization, CI/CD, and monitoring Show more Show less

About the Role We are seeking a highly skilled and experienced Senior AI Engineer to lead the design, development, and implementation of robust and scalable pipelines and backend systems for our Generative AI applications. In this role, you will be responsible for orchestrating the flow of data, integrating AI services, developing RAG pipelines, working with LLMs, and ensuring the smooth operation of the backend infrastructure that powers our Generative AI solutions. You will also be expected to apply modern LLMOps practices, handle schema-constrained generation, optimize cost and latency trade-offs, mitigate hallucinations, and ensure robust safety, personalization, and observability across GenAI systems. Responsibilities Generative AI Pipeline Development Design and implement scalable and modular pipelines for data ingestion, transformation, and orchestration across GenAI workloads. Manage data and model flow across LLMs, embedding services, vector stores, SQL sources, and APIs. Build CI/CD pipelines with integrated prompt regression testing and version control. Use orchestration frameworks like LangChain or LangGraph for tool routing and multi-hop workflows. Monitor system performance using tools like Langfuse or Prometheus. Data and Document Ingestion Develop systems to ingest unstructured (PDF, OCR) and structured (SQL, APIs) data. Apply preprocessing pipelines for text, images, and code. Ensure data integrity, format consistency, and security across sources. AI Service Integration Integrate external and internal LLM APIs (OpenAI, Claude, Mistral, Qwen, etc.). Build internal APIs for smooth backend-AI communication. Optimize performance through fallback routing to classical or smaller models based on latency or cost budgets. Use schema-constrained prompting and output filters to suppress hallucinations and maintain factual accuracy. Retrieval-Augmented Generation (RAG) Pipelines Build hybrid RAG pipelines using vector similarity (FAISS/Qdrant) and structured data (SQL/API). Design custom retrieval strategies for multi-modal or multi-source documents. Apply post-retrieval ranking using DPO or feedback-based techniques. Improve contextual relevance through re-ranking, chunk merging, and scoring logic. LLM Integration and Optimization Manage prompt engineering, model interaction, and tuning workflows. Implement LLMOps best practices: prompt versioning, output validation, caching (KV store), and fallback design. Optimize generation using temperature tuning, token limits, and speculative decoding. Integrate observability and cost-monitoring into LLM workflows. Backend Services Ownership Design and maintain scalable backend services supporting GenAI applications. Implement monitoring, logging, and performance tracing. Build RBAC (Role-Based Access Control) and multi-tenant personalization. Support containerization (Docker, Kubernetes) and autoscaling infrastructure for production. Required Skills and Qualifications Education Bachelors or Masters in Computer Science, Artificial Intelligence, Machine Learning, or related field. Experience 5+ years of experience in AI/ML engineering with end-to-end pipeline development. Hands-on experience building and deploying LLM/RAG systems in production. Strong experience with public cloud platforms (AWS, Azure, or GCP). Technical Skills Proficient in Python and libraries such as Transformers, SentenceTransformers, PyTorch. Deep understanding of GenAI infrastructure, LLM APIs, and toolchains like LangChain/LangGraph. Experience with RESTful API development and version control using Git. Knowledge of vector DBs (Qdrant, FAISS, Weaviate) and similarity-based retrieval. Familiarity with Docker, Kubernetes, and scalable microservice design. Experience with observability tools like Prometheus, Grafana, or Langfuse. Generative AI Specific Skills Knowledge of LLMs, VAEs, Diffusion Models, GANs. Experience building structured + unstructured RAG pipelines. Prompt engineering with safety controls, schema enforcement, and hallucination mitigation. Experience with prompt testing, caching strategies, output filtering, and fallback logic. Familiarity with DPO, RLHF, or other feedback-based fine-tuning methods. Soft Skills Strong analytical, problem-solving, and debugging skills. Excellent collaboration with cross-functional teams: product, QA, and DevOps. Ability to work in fast-paced, agile environments and deliver production-grade solutions. Clear communication and strong documentation practices. Preferred Qualifications Experience with OCR, document parsing, and layout-aware chunking. Hands-on with MLOps and LLMOps tools for Generative AI. Contributions to open-source GenAI or AI infrastructure projects. Knowledge of GenAI governance, ethical deployment, and usage controls. Experience with hallucination suppression frameworks like Guardrails.ai, Rebuff, or Constitutional AI. Shift Time: 2:30 PM to 11:30 PM IST Location-Remote,Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Python programming, AI/ML development. Generative AI Business Entity model extraction, Extracting Business Insights Flask, FastAPI LLM APIs (OpenAI GPT-4, 4.1, 4.1 mini). Docker, Azure RESTful, GraphQL API DevOps & CI/CD pipeline

About the Role We are seeking a Agentic AI Developer with 35 years of total software/AI experience and proven hands-on work in Agentic AI . The ideal candidate has built LLM-powered agents using frameworks like LangChain, AutoGen, CrewAI, or Semantic Kernel, and can design, deploy, and optimize autonomous AI systems for real-world business use cases. Key Responsibilities Architect, build, and deploy LLM-driven agents that can plan, reason, and execute multi-step workflows. Work with agent orchestration frameworks (LangChain, AutoGen, CrewAI, Semantic Kernel, Haystack, etc.). Develop and maintain tools, APIs, and connectors for extending agent capabilities. Implement RAG pipelines with vector databases (Pinecone, Weaviate, FAISS, Chroma, etc.). Optimize prompts, workflows, and decision-making for accuracy, cost, and reliability . Collaborate with product and engineering teams to design use-casespecific agents (e.g., copilots, data analysts, support agents). Ensure monitoring, security, and ethical compliance of deployed agents. Stay ahead of emerging trends in multi-agent systems and autonomous AI research . Required Skills 35 years of professional experience in AI/ML, software engineering, or backend development . Demonstrated hands-on experience in building agentic AI solutions (not just chatbots). Proficiency in Python (TypeScript/JavaScript is a plus). Direct experience with LLM APIs (OpenAI, Anthropic, Hugging Face, Cohere, etc.). Strong knowledge of vector databases and embeddings . Experience integrating APIs, external tools, and enterprise data sources into agents. Solid understanding of prompt engineering and workflow optimization . Strong problem-solving, debugging, and system design skills. Nice to Have Experience with multi-agent systems (agents collaborating on tasks). Prior contributions to open-source agentic AI projects . Cloud deployment knowledge ( AWS/GCP/Azure ) and MLOps practices. Background in reinforcement learning or agent evaluation . Familiarity with AI safety, monitoring, and guardrails . What We Offer Work on cutting-edge AI agent projects with direct real-world impact. Collaborative environment with strong emphasis on innovation & experimentation . Competitive salary and growth opportunities. Opportunity to specialize in one of the fastest-growing areas of AI . Show more Show less

As a Technical Lead Backend at Habuild, you will play a key role in leading the architecture, design, and implementation of backend systems that cater to millions of users. You will have a hands-on approach working with the codebase, guiding engineers, and ensuring that our backend infrastructure is scalable, high-performing, and future-proof. Your responsibilities will include owning and driving the technical roadmap for core backend systems, architecting and developing scalable microservices using FastAPI, optimizing asynchronous workflows for efficient API calls, integrating with vector databases and AI/ML APIs, and providing guidance on system architecture, database schema, and service orchestration. You will be responsible for setting coding standards, conducting code reviews, mentoring engineers, and fostering a culture of engineering excellence within the team. To excel in this role, you are required to have at least 6 years of backend development experience with a minimum of 3 years specifically in Python. Proficiency in FastAPI and async programming, solid knowledge of PostgreSQL and vector databases, experience with LLM APIs, and expertise in microservices architecture and API design are essential. Additionally, familiarity with real-time communication protocols, Docker, CI/CD pipelines, and cloud deployment is necessary. Your proven leadership skills, innovative mindset, and track record of exploring new technologies will be highly valued. Joining us at Habuild means being part of a mission-driven company that is dedicated to transforming lives every day. You will have the opportunity to work on critical systems, be surrounded by passionate individuals, enjoy a high-ownership culture, and benefit from a flexible work model that emphasizes continuous learning and experimentation. Together, we can build something extraordinary.,