93 Llamaindex Jobs - Page 2

Location: Bangalore Key Responsibilities: Design, develop, and deploy AI/ML models, particularly using LLAMA and similar LLM frameworks. Integrate vector databases and PostgreSQL for intelligent data retrieval and storage. Build and optimize Python-based pipelines , APIs, and backend services for AI applications. Leverage Databricks for scalable data processing, model training, and deployment. Collaborate with cross-functional teams to deliver production-ready AI solutions rapidly. Contribute to POCs and prototypes to validate ideas and iterate quickly. Must-Have Skills: 7+ years of experience in Data Science / AI Engineering roles. Proficiency with Databricks , Python , and PostgreSQL . Hands-on experience working with LLMs (especially LLAMA) and vector DBs like Pinecone, FAISS, or similar. Strong understanding of AI/ML lifecycle , from model development to deployment. Experience in startup or agile environments , with proven rapid delivery capabilities. Good to Have: Familiarity with cloud platforms (AWS/Azure/GCP). Knowledge of LangChain or similar LLM orchestration frameworks. Exposure to MLOps best practices and deployment tools.

As a leading financial services and healthcare technology company based on revenue, SS&C is headquartered in Windsor, Connecticut, and has 27,000+ employees in 35 countries. Some 20,000 financial services and healthcare organizations, from the world's largest companies to small and mid-market firms, rely on SS&C for expertise, scale, and technology. We are looking for an experienced AI Developer with proficiency in Python, Generative AI (GenAI) incorporating Retrieval-Augmented Generation (RAG), Robotic Process Automation (RPA), and advanced document intelligence utilizing OCR and LLMs. In this role, you will be responsible for developing AI-driven solutions that extract valuable insights from intricate documents, whether digital or scanned, by utilizing tools such as Tesseract, Hugging Face Transformers, or similar technologies. Your primary focus will be on creating end-to-end automation and AI integration for intelligent document processing, enhancing decision-making capabilities and optimizing workflow efficiencies throughout the organization. Key Responsibilities: - Develop and implement GenAI solutions with RAG pipelines to facilitate intelligent querying and summarization of document repositories. - Extract and organize data from complex documents (e.g., PDFs, Images) using a combination of OCR engines (e.g., Tesseract) and AI-based document and vision language models (DiNO, SmolVLM, etc.). - Incorporate OCR+LLM pipelines into business applications for processing scanned forms, contracts, and other unstructured documents. - Automate repetitive, document-centric tasks using RPA tools (e.g., Blue Prism, etc.). - Design and manage Python-based workflows to coordinate document ingestion, extraction, and LLM-powered processing. - Collaborate across various teams including product, data, and operations to deliver scalable, AI-enhanced document automation solutions. - Ensure model performance, compliance, and audit readiness for all document-handling workflows. Required Qualifications: - Minimum of 4 years of hands-on programming experience with Python. - Demonstrated expertise in building RAG-based GenAI applications using tools like LangChain, LlamaIndex, or equivalent. - Proficiency in OCR tools (e.g., Tesseract, PaddleOCR) and transformer-based document models. - Experience working with LLMs for document understanding, summarization, and Q&A. - Proficient in RPA development utilizing platforms like Blueprism, etc. - Knowledge of vector databases (e.g., FAISS, Pinecone) and embeddings for semantic retrieval. - Strong understanding of REST APIs, JSON, and data integration workflows. Please note that unless explicitly requested or approached by SS&C Technologies, Inc. or any of its affiliated companies, the company will not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services.,

We are looking for a GenAI/ML Engineer to design, develop, and deploy cutting-edge AI/ML models and Generative AI applications . This role involves working on large-scale enterprise use cases, implementing Large Language Models (LLMs) , building Agentic AI systems , and developing data ingestion pipelines . The ideal candidate should have hands-on experience with AI/ML development , Generative AI applications , and a strong foundation in deep learning , NLP , and MLOps practices. Key Responsibilities Design, develop , and deploy AI/ML models and Generative AI applications for various enterprise use cases. Implement and integrate Large Language Models (LLMs) using frameworks such as LangChain , LlamaIndex , and RAG pipelines . Develop Agentic AI systems capable of multi-step reasoning and autonomous decision-making . Create secure and scalable data ingestion pipelines for structured and unstructured data, enabling indexing, vector search, and advanced retrieval techniques. Collaborate with cross-functional teams (Data Engineers, Product Managers, Architects) to deploy AI solutions and enhance the AI stack. Build CI/CD pipelines for ML/GenAI workflows and support end-to-end MLOps practices. Leverage Azure and Databricks for training , serving , and monitoring AI models at scale. Required Qualifications & Skills (Mandatory) 4+ years of hands-on experience in AI/ML development , including Generative AI applications . Expertise in RAG , LLMs , and Agentic AI implementations. Strong experience with LangChain , LlamaIndex , or similar LLM orchestration frameworks. Proficiency in Python and key ML/DL libraries : TensorFlow , PyTorch , Scikit-learn . Solid foundation in Deep Learning , Natural Language Processing (NLP) , and Transformer-based architectures . Experience in building data ingestion , indexing , and retrieval pipelines for real-world enterprise use cases. Hands-on experience with Azure cloud services and Databricks . Proven track record in designing CI/CD pipelines and using MLOps tools like MLflow , DVC , or Kubeflow . Soft Skills Strong problem-solving and critical thinking ability. Excellent communication skills , with the ability to explain complex AI concepts to non-technical stakeholders. Ability to collaborate effectively in agile , cross-functional teams . A growth mindset , eager to explore and learn emerging technologies. Preferred Qualifications Familiarity with vector databases such as FAISS , Pinecone , or Weaviate . Experience with AutoGPT , CrewAI , or similar agent frameworks . Exposure to Azure OpenAI , Cognitive Search , or Databricks ML tools . Understanding of AI security , responsible AI , and model governance . Role Dimensions Design and implement innovative GenAI applications to address complex business problems. Work on large-scale, complex AI solutions in collaboration with cross-functional teams. Take ownership of the end-to-end AI pipeline , from model development to deployment and monitoring. Success Measures (KPIs) Successful deployment of AI and Generative AI applications . Optimization of data pipelines and model performance at scale. Contribution to the successful adoption of AI-driven solutions within enterprise use cases. Effective collaboration with cross-functional teams, ensuring smooth deployment of AI workflows. Competency Alignment AI/ML Development : Expertise in building and deploying scalable and efficient AI models. Generative AI : Strong hands-on experience in Generative AI , LLMs , and RAG frameworks. MLOps : Proficiency in designing and maintaining CI/CD pipelines and implementing MLOps practices . Cloud Platforms : Experience with Azure and Databricks for AI model training and serving.

You should have 6-10+ years of experience in AI/ML development, including at least 3 years of hands-on experience in Generative AI, RAG frameworks, and Agentic AI systems. As a Generative AI Engineer, you will be responsible for designing, developing, and optimizing RAG pipelines using frameworks such as LangChain, LlamaIndex, or custom-built stacks. You will also implement Agentic AI architectures involving task-based agents, stateful memory, planning-execution workflows, and tool augmentation. Additionally, you will perform model fine-tuning, embedding generation, and evaluation of LLM outputs while incorporating human and automated feedback loops. Building and enforcing guardrails to ensure safe, compliant, and robust model behavior will be a crucial part of your role, including prompt validation, output moderation, and access controls. Collaboration with cross-functional teams to deploy solutions in cloud-native environments such as Azure OpenAI, AWS Bedrock, or Google Vertex AI will also be expected. Furthermore, you will contribute to system observability via dashboards and logging, as well as support post-deployment model monitoring and optimization. To excel in this role, you must have proven production experience with RAG frameworks like LangChain, LlamaIndex, or custom-built solutions. A solid understanding of Agentic AI design patterns, strong expertise in LLM fine-tuning, vector embeddings, evaluation strategies, and feedback integration are essential. Experience with implementing AI guardrails, proficiency in Python, LLM APIs (OpenAI, Anthropic, Cohere, etc.), and vector database integration are also required. Familiarity with CI/CD pipelines, API integrations, and cloud-native deployment patterns is a plus. Preferred qualifications include experience working on AI projects in regulated environments (Banking domain), hands-on experience with cloud AI platforms like Azure OpenAI, AWS Bedrock, or Google Vertex AI, knowledge of prompt engineering, RLHF, and LLM observability frameworks, as well as experience building or leveraging internal LLM evaluation harnesses, agent orchestration layers, or compliance dashboards.,

We are seeking a talented AI/ML Developer with a strong passion for Artificial Intelligence to become a valuable member of our innovative organization. This role presents a thrilling opportunity to actively participate in AI projects and contribute to the creation of cutting-edge solutions. Your primary responsibilities will include developing and maintaining applications for AI and Large Language Model (LLM) projects. You will be tasked with conducting data analysis to identify trends and insights that can enhance the efficiency of models. Designing, developing, and deploying machine learning models for diverse applications will also be a key aspect of your role. Optimization of algorithms for improved performance and scalability will be essential, along with staying abreast of the latest advancements in the field of AI. To qualify for this position, you should possess a Bachelor's or Master's degree in Computer Science or a related field from an accredited university. While internship experience in AI or related domains is advantageous, demonstrable expertise in AI/ML programming and development is crucial. Proficiency in utilizing OpenAI technologies and Vector Databases is required, along with familiarity with Large Language Models (LLMs) and frameworks like LangChain and LLamaIndex. Experience in API Development and managing Relational Databases is also highly desirable. Strong problem-solving abilities, meticulous attention to detail, and the capacity to work both independently and collaboratively in a team environment are key attributes we are looking for. Join our team and embark on an exciting journey to drive forward the advancement of AI technology. Your expertise in machine learning models, LlamaIndex, Vector databases, algorithm optimization, data analysis, OpenAI technologies, API development, Large Language Models (LLMs), AI/ML programming, and relational databases will be invaluable assets in contributing to our innovative projects.,

Atologist Infotech is seeking an experienced and forward-thinking AI Engineer to contribute to the shaping and scaling of the AI Agent Framework. In this hands-on engineering position, your primary focus will be on the development of intelligent and modular agent systems capable of reasoning, planning, and autonomously interacting in real-world scenarios. Working closely with a collaborative team, you will be responsible for designing and implementing agent-oriented systems that facilitate task decomposition, memory management, and contextual planning. Additionally, you will play a key role in extending the in-house AI Agent Framework by incorporating reusable components such as tools, memory modules, and orchestration logic. Your duties will also involve building and integrating vector search, semantic retrieval, and memory systems to empower long-term, goal-oriented behavior in agents. You will be tasked with connecting LLMs (e.g., OpenAI, Anthropic) and NLU/NLP layers to enable natural task inputs and autonomous reasoning capabilities. Furthermore, you will develop RESTful APIs using FastAPI, Flask, or Django to expose agent functionalities and facilitate integration with other products. As an AI Engineer at Atologist Infotech, you will be expected to design scalable, event-driven microservice architectures customized for AI-native workloads and agent frameworks. Emphasizing responsible AI design, you will prioritize user safety, transparency, and privacy throughout the development process. **Key Responsibilities:** - AI Agent System Development: Design and implement agent-oriented systems supporting task decomposition, memory handling, and contextual planning. - Framework Engineering: Extend the in-house AI Agent Framework with reusable components like tools, memory modules, and orchestration logic. - Contextual Intelligence: Build and integrate vector search, semantic retrieval, and memory systems to enable long-term, goal-driven agent behavior. - Natural Language Interfaces: Connect LLMs and NLU/NLP layers for natural task inputs and autonomous reasoning capabilities. - API Engineering: Develop RESTful APIs using FastAPI, Flask, or Django to expose agent capabilities and integrate with other products. - System Architecture: Design scalable, event-driven microservice architectures tailored for AI-native workloads and agent frameworks. - Ethical AI: Prioritize responsible AI design with user safety, transparency, and privacy at the core. **Required Skills & Qualifications:** - Education: Bachelors or Masters degree in Computer Science, Artificial Intelligence, or a related field. - Python Proficiency: Strong software engineering skills in Python (3.x) with expertise in async programming, architecture design, and typing. - AI/LLM Experience: Practical experience using LLMs for reasoning, prompt engineering, chaining, or building agent-like applications. - Frameworks & Tools: FastAPI, Flask, or Django; LangChain, LlamaIndex, or other agent frameworks; Vector stores (FAISS, Weaviate, Pinecone); PostgreSQL, Redis, and event queues (Celery, RabbitMQ). - Version Control & Testing: Proficient with Git workflows and writing tests using Pytest or similar. **Bonus Skills (Nice-to-Have):** - Experience with autonomous agents, tool-calling, or memory-driven task systems. - Familiarity with cognitive architectures or symbolic reasoning. - Contributions to open-source AI frameworks or tooling. This is a full-time, permanent position offering benefits such as leave encashment, paid sick time, paid time off, and Provident Fund. The work schedule is fixed from Monday to Friday. Experience: AI - 3 years (Preferred) Work Location: In person,

As a Prompt Engineer in the Artificial Intelligence/R&D department, you will play a vital role in building, optimizing, and testing natural language prompts to enhance the performance of large language models like OpenAI GPT, Claude, and Gemini. Your primary responsibilities will involve designing, writing, and optimizing natural language prompts to address specific business or product challenges. Working alongside data scientists, product managers, and engineering teams, you will contribute to the development of high-quality AI prompt systems for real-world applications. Your role will require you to analyze and test the impact of different prompts on model output quality, collaborating closely with product and development teams to create deployable prompt templates and interface logic. Additionally, you will be involved in establishing prompt libraries and prompt engineering frameworks to enhance prompt reusability and scalability. Staying updated on the latest prompt engineering technologies and research papers will be crucial, as you transform these insights into practical applications. To excel in this role, you must demonstrate proficiency in utilizing mainstream large-scale language models such as GPT-4, Claude, or Gemini. Strong language expression and logical thinking skills, along with expertise in prompt tuning, few-shot learning, and chain-of-thought prompt engineering methods, are essential. A bachelor's degree in a relevant field (computer science, linguistics, cognitive science) is required, with a preference for candidates with strong English reading abilities to understand model documents and research papers. Candidates with experience in actual Large Language Model (LLM) application projects, mastery of Python programming for rapid prototyping, and familiarity with dialogue systems, search engines, knowledge graphs, and RAG technologies will be given bonus points. Understanding model fine-tuning, LoRA, and system prompt structure, as well as familiarity with tool chains like LangChain, LlamaIndex, and OpenAI Function Calling, will be advantageous. In return, we offer a competitive salary and bonus system, the chance to work with cutting-edge AI technology, flexible working hours, and remote work options. Join our team of technology enthusiasts and innovators to embark on a rewarding career journey.,

As a Data Analytics focused Senior Software Engineer at PubMatic, you will be responsible for developing advanced AI agents to enhance data analytics capabilities. Your expertise in building and optimizing AI agents, along with strong skills in Hadoop, Spark, Scala, Kafka, Spark Streaming, and cloud-based solutions, will play a crucial role in improving data-driven insights and analytical workflows. Your key responsibilities will include building and implementing a highly scalable big data platform to process terabytes of data, developing backend services using Java, REST APIs, JDBC, and AWS, and building and maintaining Big Data pipelines using technologies like Spark, Hadoop, Kafka, and Snowflake. Additionally, you will design and implement real-time data processing workflows, develop GenAI-powered agents for analytics and data enrichment, and integrate LLMs into existing services for query understanding and decision support. You will work closely with cross-functional teams to enhance the availability and scalability of large data platforms and PubMatic software functionality. Participating in Agile/Scrum processes, discussing software features with product managers, and providing customer support over email or JIRA will also be part of your role. We are looking for candidates with three plus years of coding experience in Java and backend development, solid computer science fundamentals, expertise in developing software engineering best practices, hands-on experience with Big Data tools, and proven expertise in building GenAI applications. The ability to lead feature development, debug distributed systems, and learn new technologies quickly are essential. Strong interpersonal and communication skills, including technical communications, are highly valued. To qualify for this role, you should have a bachelor's degree in engineering (CS/IT) or an equivalent degree from well-known Institutes/Universities. PubMatic employees globally have returned to our offices via a hybrid work schedule to maximize collaboration, innovation, and productivity. Our benefits package includes paternity/maternity leave, healthcare insurance, broadband reimbursement, and office perks like healthy snacks, drinks, and catered lunches. About PubMatic: PubMatic is a leading digital advertising platform that provides transparent advertising solutions to publishers, media buyers, commerce companies, and data owners. Our vision is to enable content creators to run a profitable advertising business and invest back into the multi-screen and multi-format content that consumers demand.,

Senior Engineer (GenAI & Prompt Engineering) Company : Xebia | Job Type : Fulltime| Location : Hybrid Chennai, Bangalore, Hyderabad, Pune, Jaipur, Bhopal, Gurugram (India) Job Summary Xebia is hiring an experienced GenAI Engineer to lead initiatives embedding LLMs into internal DevOps and Engineering workflows. This is a hands-on opportunity for AI engineers with strong Python and prompt engineering skills. Key Responsibilities Design and optimize LLM prompts for contextual accuracy Build RAG architectures using FAISS, Pinecone, Weaviate , etc. Integrate LLMs into CI/CD pipelines, dashboards, internal tools Use LangChain, LlamaIndex, HuggingFace, Haystack frameworks Fine-tune LLMs (OpenAI, Claude, Cohere, Mistral) for enterprise use cases Ensure compliance, security, and performance of AI systems Collaborate across teams to identify automation opportunities Required Skills & Experience 6-10 years total experience with 2+ years in GenAI/LLM/NLP systems Strong in Python, vector DBs, embedding techniques Hands-on with LLM APIs , GenAI libraries, and NLP concepts Prior experience building contextual AI agents or CI/CD automation using LLMs Nice to Have Familiarity with multi-modal models , DevSecOps, Kubernetes Experience with developer-facing GenAI use cases (log triage, changelogs, copilots) Other Details Mode : Hybrid (3 days a week in-office) Locations : Chennai / Bangalore / Hyderabad / Pune / Jaipur / Bhopal / Gurugram Notice Period : Immediate to max 2 weeks Contract Role To Apply Send the following details to vijay.s@xebia.com : Full Name Total Experience Current CTC Expected CTC Current Location Preferred Xebia Location Notice Period / Last Working Day Primary Skills LinkedIn Profile Keywords : GenAI, Prompt Engineering, RAG, LangChain, Python, FAISS, LLM, LangChain, Vector DB, HuggingFace, LlamaIndex, CI/CD, Automation, DevOps, AI, NLP

Qualcomm India Private Limited is looking for a Lead Conversational AI Developer to join the Intelligent Automation Center (IAC) team. As a Lead Conversational AI Developer, you will be responsible for designing and implementing Conversational AI solutions using Microsoft Azure and Copilot Stack in combination with GenAI. You should have hands-on experience with Microsoft Copilot Studio, Microsoft Bot Framework, NLP, Azure AI Search, and Azure OpenAI. Additionally, you will be utilizing Generative AI in projects and should have a strong expertise in Python for building bot solutions. Furthermore, you will be working with Azure Cognitive Services, Power Automate, Azure Logic Apps, and APIs to enhance Copilot Agent and bot functionalities. You should have experience in software development focusing on Conversational AI and Machine Learning. Proficiency with tools and Frameworks such as LangChain, LlamaIndex, and Streamlit is required. Knowledge and implementation experience of chatbot technologies using Microsoft Azure Services and Power Platform is also essential. Responsibilities include ensuring the quality of coded components through unit testing, collaborating with test teams for product testing and UAT, reporting status, issues, and risks to tech leads, improving skills in automation products through certifications, and training team members on Conversational AI related technologies. You should be able to work independently with minimal supervision, possess good team management skills, and have excellent communication and collaboration skills. Minimum qualifications include 4+ years of work experience in programming, scripting, and/or automation with a Bachelor's degree or 6+ years of relevant work experience without a Bachelor's degree. Additionally, you should have 2+ years of experience with Database Design structures such as Mongo DB and MySQL. Knowledge of conversational AI, Intelligent Automation methodologies, Process Mining concepts, and experience in business process diagrams and process flow charts are required. Applicants should have a Bachelor's degree and at least 5 years of IT-relevant work experience. Certification in Industry Leading Robotic Automation products, experience in Agile development, and cloud experience are considered a plus. Qualcomm is an equal opportunity employer committed to providing accessible processes for individuals with disabilities. If you require accommodations during the application/hiring process, please contact Qualcomm.,

As a NLP & Generative AI Engineer at Gigaforce, you will be part of our dynamic AI/ML team based in Noida, working on cutting-edge technologies to revolutionize the insurance claims processing industry. We are a California-based InsurTech company with a strong focus on innovation and digital transformation in the Property and Casualty sector. You must have a minimum of 2 years of hands-on experience in traditional machine learning, natural language processing, and modern generative AI techniques to be considered for this role. We are looking for individuals who are passionate about deploying GenAI solutions to production, working with open-source technologies, and handling document-centric pipelines efficiently. Your main responsibilities will include building and deploying NLP and GenAI-driven products focusing on document understanding, summarization, classification, and retrieval. You will be designing and implementing models using LLMs such as GPT, T5, and BERT, along with working on scalable, cloud-based pipelines for training, serving, and monitoring models. Collaboration is key at Gigaforce, and you will work closely with cross-functional teams including data scientists, ML engineers, product managers, and developers. Additionally, you will contribute to open-source tools and frameworks in the ML ecosystem, deploying production-ready solutions using MLOps practices, and working on distributed/cloud systems with GPU-accelerated workflows. To be successful in this role, you should have a strong grasp of traditional ML algorithms, NLP fundamentals, and modern NLP & GenAI models. Proficiency in Python, experience with cloud platforms like AWS SageMaker, GCP, or Azure ML, and familiarity with MLOps tools and distributed computing are essential. Experience with document processing pipelines and understanding insurance-related documents is a plus. If you are looking for a challenging role where you can lead the design, development, and deployment of innovative AI/ML solutions in the insurance industry, then this position at Gigaforce is the perfect opportunity for you. Join us in our mission to transform the claims lifecycle into an intelligent, end-to-end digital experience.,

Required Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 2 to 8 years of experience in full stack software engineering. Proven experience in building AI chatbots and deploying Agentic AI solutions. Hands-on experience with Retrieval-Augmented Generation (RAG) techniques. Proficient in programming languages such as Python, JavaScript, or similar. Experience with AI frameworks and tools such as LangChain, LlamaIndex, LangGraph, MS Autogen2, Google ADK, PydanticAI, crewAI or similar. Strong understanding of front-end technologies like React, Angular, or Vue.js. Strong understanding of backend-end technologies like FastAPI, Flask, Django etc Familiarity with cloud platforms such as AWS, Azure, or Google Cloud. Excellent problem-solving skills and attention to detail. Preferred Qualifications: Experience in agile development methodologies. Knowledge of machine learning algorithms and data structures. Strong communication and collaboration skills. Ability to work in a fast-paced, dynamic environment.

Position Overview We are seeking an experienced AI/ML Architect with 10+ years of experience, specializing in ML and Gen AI. The ideal candidate will possess the technical depth to design and implement cutting-edge AI/ML solutions, particularly leveraging large language models (LLMs) and agentic workflows, while translating business requirements into actionable technical architectures. This role requires a hands-on professional who thrives in a dynamic environment, delivering impactful AI/ML strategies and solutions. Skills: Technical Expertise Very good Skills in Python, Pandas, NumPy, SQL Excellent understanding of Machine Learning algorithms and metrics. Proficiency with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with LLM frameworks like LangChain, LlamaIndex, or similar tools. Strong knowledge of at least one hyperscaler (preferably GCP or Azure). Proficiency and understanding of ML APIs on the cloud. Experience in designing and implementing agentic workflows and modular AI solutions using frameworks like LangGraph, Crew.ai, Microsoft Autogen etc. Understanding of data pipelines, ETL frameworks, and big data technologies (e.g., Spark, Snowflake, Hadoop). Architecture Design Expertise in creating AI/ML solution blueprints and technical diagrams. Familiarity with MLOps practices, microservices architecture, containerization (Docker, Kubernetes), and CI/CD pipelines. Excellent understanding in Gen AI frameworks and models. Prompt Engineering, GANs, OpenAI, Dall-E, Stable Diffusion, Langchain, Lllama2. Prior experience in technical presales and building proposal Domain Expertise Preferred domain expertise in consumer/CPG/retail, supply chain Soft Skills Strong communication skills with the ability to present technical solutions to business leaders. Proven ability to collaborate cross-functionally with technical and non-technical teams. Problem-solving mindset with a focus on innovation and impact. Role Description: Solution Design & Architecture Work with business teams to identify requirements and design AI/ML solutions that address key challenges in the consumer/CPG/retail sectors. Develop comprehensive architecture diagrams and technology stacks tailored to business needs. Incorporate LLM frameworks (e.g., LangChain, LlamaIndex) into solution designs to deliver advanced language-based functionalities. Technical Implementation & Agentic Workflows Design and implement agentic workflows using LLMs to automate decision-making and complex processes. Build modular, scalable solutions that integrate with existing enterprise systems and tools. Ensure solutions are aligned with MLOps practices for robust deployment and monitoring. Prototyping & POCs Rapidly develop proof-of-concept (POC) models and prototypes, showcasing the feasibility and value of AI/ML solutions. Test and refine LLM-driven workflows and agent-based models to meet business objectives. Presales Lead AI discussions with prospects presenting Calsofts capabilities and experience and discussing client need Understand client need and design technical solution, high-level work plans, and estimates required for an AI related sales proposal

Job Summary: We are seeking a passionate and highly skilled Solution Architect Generative AI & Agentic AI to design, develop, and deploy intelligent systems leveraging large language models (LLMs), multiagent frameworks, and enterprise AI integration patterns. This role will play a key part in building next-generation AI applications that autonomously reason, act, and learn across complex business workflows.As a Generative & Agentic AI Solution Architect you will own the end-to-end architecture for enterprise-grade GenAI solutions and multi-agent systems. Youll translate business objectives into scalable, compliant, and observable AI capabilitiesspanning data pipelines, foundation-model ops, Retrieval-Augmented Generation (RAG), and autonomous agent orchestration. You will partner with product owners, data scientists, platform engineers, security, and business stakeholders to accelerate AI-driven transformation while safeguarding performance, ethics, and regulatory compliance. Key Responsibilities: 1. Solution Development: Design and implement applications using LLMs (e.g., OpenAI, Mistral, Claude, Llama) Build autonomous multi-agent systems using frameworks like AutoGen, LangGraph, CrewAI, or AgentOps Develop scalable backend services and orchestration pipelines using Python/Node.js integrated with AI APIs Lead discovery workshops, create MVP backlogs, and convert PoCs into production-ready solutions following MLOps / LLMOps best practices Oversee model selection, finetuning, prompt-engineering, evaluation, and continuous monitoring 2. Architecture & Engineering: Translate business requirements into agentic workflows with reasoning, memory, and tool usage Integrate GenAI and agents with enterprise systems (e.g., SAP, ServiceNow, Salesforce) via APIs and RAG pipelines Work with vector databases (e.g., Pinecone, FAISS, Weaviate) for semantic search and long-term memory Define reference architectures for GenAI (LLMs, Diffusion, SSMs) and agentic patterns (task-decomposition, planner-executor, tool-calling) Design secure micro-service and event-driven topologies on cloud / hybrid infra (AWS Bedrock, Azure OpenAI, Google Vertex, private GPUs) Required Technical Competencies: Generative AI: Hands-on with LLMs (GPT-4o, Claude-3, Gemini, Llama-3), Diffusion, and audio-/vision models; experience with HF Transformers, LangChain / LlamaIndex Agentic Frameworks: Experience designing goal-oriented agents using AutoGen, CrewAI, Semantic Kernel, or custom planners; familiarity with tool-calling, memory management, and AI schedulers LLMOps / MLOps: CI/CD for model artifacts, feature stores, vector DBs (Pinecone, Weaviate, FAISS), model gateways, and policy engines (Guardrails, Azure AI Safety) Cloud & DevSecOps: Terraform, Kubernetes, Docker, serverless, GPU orchestration, secret management, SAST/DAST integration Programming: Python (primary), TypeScript/Node, Bash; strong design-pattern discipline and code-review leadership Build replaceable but working proofofconceptsCLI, Streamlit, or VS Code Jupyterso stakeholders can touch” the idea Write production-grade Python/TypeScript to orchestrate agents with AutoGen / CrewAI / Semantic Kernel Hook agents to real systems (SAP BAPIs, Salesforce APIs, REST/GraphQL) and manage auth tokens & secrets Build CI/CD (GitHub Actions, Terraform, Helm) that auto-tests prompts, pushes Docker images, and provisions GPUs Instrument tracing (OpenTelemetry) and set up dashboards for tokens, latency, cost per call Education: Bachelor’s or master’s degree in computer science, Data Science, Artificial Intelligence, Engineering, or a related field Note: Working from office Mandatory

We are looking for a highly motivated and enthusiastic Senior Data Scientist with 5-8 years of experience to join our dynamic team. The ideal candidate should have a strong background in AI/ML analytics and a passion for utilizing data to drive business insights and innovation. Your main responsibilities will include developing and implementing machine learning models and algorithms, collaborating with project stakeholders to understand requirements and deliverables, analyzing and interpreting complex data sets using statistical and machine learning techniques, staying updated with the latest advancements in AI/ML technologies, and supporting various AI/ML initiatives by working with cross-functional teams. To qualify for this role, you should have a Bachelor's degree in Computer Science, Data Science, or a related field, along with a strong understanding of machine learning, deep learning, and Generative AI concepts. Preferred skills for this position include experience in machine learning techniques such as Regression, Classification, Predictive modeling, Clustering, and Deep Learning stack using Python. Additionally, expertise in cloud infrastructure for AI/ML on AWS (Sagemaker, Quicksight, Athena, Glue), building secure data ingestion pipelines for unstructured data, proficiency in Python, TypeScript, NodeJS, ReactJS, data visualization tools, deep learning frameworks, version control systems, and Generative AI/LLM based development is desired. Good to have skills include knowledge and experience in building knowledge graphs in production and an understanding of multi-agent systems and their applications in complex problem-solving scenarios. Pentair is an Equal Opportunity Employer, valuing cross-cultural insight and competence for ongoing success, with a belief that a diverse workforce enhances perspectives and ideas for continuous improvement.,

You are a dynamic and hands-on Full Stack AI Developer with expertise in Python programming, Generative AI, LLMs, API development, and front-end frameworks like React and Streamlit. Your responsibility includes designing, developing, and maintaining AI-powered full stack applications, building and optimizing REST APIs, creating backend services, implementing Generative AI features, developing front-ends, integrating retrieval-augmented generation (RAG) and agentic AI concepts, applying best practices in software engineering, and working with cloud platforms. You must have proficiency in Core Python Development, scientific & data libraries like NumPy and Pandas, database integration, API development, Generative AI/LLMs, deployment & containerization using Docker, frontend development with HTML5, CSS3, modern JavaScript, Streamlit, and React.js. Desirable skills include experience with cloud services, monitoring and logging for AI systems, testing frameworks, PDF extraction, OCR tools, frontend accessibility, and performance optimization. Your soft skills should include strong communication and documentation skills, problem-solving mindset, and the ability to collaborate across cross-functional teams. An educational qualification of Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or related field is required, and certifications or hands-on experience in Generative AI/LLMs are a plus. This role is ideal for candidates passionate about developing end-to-end AI applications from data ingestion and model integration to real-time deployment and UI/UX delivery. You will work on real-world GenAI products using LLMs, APIs, Vector Databases, and modern front-end stacks in a production-ready setup.,

You will be responsible for designing, building, and deploying scalable NLP/ML models for real-world applications. Your role will involve fine-tuning and optimizing Large Language Models (LLMs) using techniques like LoRA, PEFT, or QLoRA. You will work with transformer-based architectures such as BERT, GPT, LLaMA, and T5, and develop GenAI applications using frameworks like LangChain, Hugging Face, OpenAI API, or RAG (Retrieval-Augmented Generation). Writing clean, efficient, and testable Python code will be a crucial part of your tasks. Collaboration with data scientists, software engineers, and stakeholders to define AI-driven solutions will also be an essential aspect of your work. Additionally, you will evaluate model performance and iterate rapidly based on user feedback and metrics. The ideal candidate should have a minimum of 3 years of experience in Python programming with a strong understanding of ML pipelines. A solid background and experience in NLP, including text preprocessing, embeddings, NER, and sentiment analysis, are required. Proficiency in ML libraries such as scikit-learn, PyTorch, TensorFlow, Hugging Face Transformers, and spaCy is essential. Experience with GenAI concepts, including prompt engineering, LLM fine-tuning, and vector databases like FAISS and ChromaDB, will be beneficial. Strong problem-solving and communication skills are highly valued, along with the ability to learn new tools and work both independently and collaboratively in a fast-paced environment. Attention to detail and accuracy is crucial for this role. Preferred skills include theoretical knowledge or experience in Data Engineering, Data Science, AI, ML, RPA, or related domains. Certification in Business Analysis or Project Management from a recognized institution is a plus. Experience in working with agile methodologies such as Scrum or Kanban is desirable. Additional experience in deep learning and transformer architectures and models, prompt engineering, training LLMs, and GenAI pipeline preparation will be advantageous. Practical experience in integrating LLM models like ChatGPT, Gemini, Claude, etc., with context-aware capabilities using RAG or fine-tuning models is a plus. Knowledge of model evaluation and alignment, as well as metrics to calculate model accuracy, is beneficial. Data curation from sources for RAG preprocessing and development of LLM pipelines is an added advantage. Proficiency in scalable deployment and logging tooling, including skills like Flask, Django, FastAPI, APIs, Docker containerization, and Kubeflow, is preferred. Familiarity with Lang Chain, LlamaIndex, vLLM, HuggingFace Transformers, LoRA, and a basic understanding of cost-to-performance tradeoffs will be beneficial for this role.,

We are hiring a passionate Agentic AI Engineer with 2+ years of experience in building LLM-powered agent systems using LlamaIndex, Python, and frameworks like LangGraph, AutoGen, or CrewAI. Please find the JD JD: https://tinyurl.com/tencysagenticai

Description: Product Operations partners with a variety of different engineering and operations teams, our team leads development of machine learning solutions. We deliver projects from end-to-end: problem statement and conceptualization, proof-of-concept, and participation in final deployment! You will also perform ad-hoc statistical analyses. You will also work closely with data engineers to generate detailed business intelligence solutions. You will be expected to conduct presentations of analyses to a wide range of audiences including executives. Minimum Qualifications 3+ years of experience in machine learning algorithms, statistics, and data mining models, with an emphasis on large language models (LLM) or large multimodal models (LMM). Masters degree in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Operations Research, Physics, Mechanical Engineering, Electrical Engineering, or a related field. Preferred Qualifications Proven experience in LLM and LMM development, fine-tuning, and application building. Experience with agents and agentic workflows is a major plus. Experience with modern LLM serving and inference frameworks, including vLLM for efficient model inference and serving. Hands-on experience with LangChain and LlamaIndex, enabling RAG applications and LLM orchestration. Strong software development skills with proficiency in Python. Experienced user of ML and data science libraries such as PyTorch, TensorFlow, Hugging Face Transformers, and scikit-learn. Familiarity with distributed computing, cloud infrastructure, and orchestration tools, such as Kubernetes, Apache Airflow (DAG), Docker, Conductor, Ray for LLM training and inference at scale is a plus. Deep understanding of transformer-based architectures (e.g., BERT, GPT, LLaMA) and their optimization for low-latency inference. Ability to meaningfully present results of analyses in a clear and impactful manner, breaking down complex ML/LLM concepts for non-technical audiences. Experience applying ML techniques in manufacturing, testing, or hardware optimization is a major plus. Proven experience in leading and mentoring teams is a plus.

We are looking for a highly motivated and enthusiastic Senior Data Scientist with 5-8 years of experience to join our dynamic team. The ideal candidate will have a strong background in AI/ML analytics and a passion for leveraging data to drive business insights and innovation. As a Senior Data Scientist, your key responsibilities will include developing and implementing machine learning models and algorithms. You will work closely with project stakeholders to understand requirements and translate them into deliverables. Utilize statistical and machine learning techniques to analyze and interpret complex data sets. It is essential to stay updated with the latest advancements in AI/ML technologies and methodologies and collaborate with cross-functional teams to support various AI/ML initiatives. To qualify for this role, you should have a Bachelor's degree in Computer Science, Data Science, or a related field. A strong understanding of machine learning, deep learning, and Generative AI concepts is required. Preferred skills for this position include experience in machine learning techniques such as Regression, Classification, Predictive modeling, Clustering, and Deep Learning stack using Python. Experience with cloud infrastructure for AI/ML on AWS (Sagemaker, Quicksight, Athena, Glue) is highly desirable. Expertise in building enterprise-grade, secure data ingestion pipelines for unstructured data (ETL/ELT) is a plus. Proficiency in Python, TypeScript, NodeJS, ReactJS, and frameworks like pandas, NumPy, scikit-learn, SKLearn, OpenCV, SciPy, Glue crawler, ETL, as well as experience with data visualization tools like Matplotlib, Seaborn, and Quicksight, is beneficial. Additionally, knowledge of deep learning frameworks such as TensorFlow, Keras, and PyTorch, experience with version control systems like Git and CodeCommit, and strong knowledge and experience in Generative AI/LLM based development are essential for this role. Experience working with key LLM models APIs (e.g., AWS Bedrock, Azure Open AI/OpenAI) and LLM Frameworks (e.g., LangChain, LlamaIndex), as well as proficiency in effective text chunking techniques and text embeddings, are also preferred skills. Good to have skills include knowledge and experience in building knowledge graphs in production and an understanding of multi-agent systems and their applications in complex problem-solving scenarios. Pentair is an Equal Opportunity Employer that values diversity and believes that a diverse workforce contributes different perspectives and creative ideas, enabling continuous improvement.,

As a Full Stack AI Developer, you will be responsible for designing, developing, and maintaining AI-powered full stack applications. Your key responsibilities will include building and optimizing REST APIs using FastAPI/Flask, integrating advanced LLM capabilities, creating backend services, implementing Generative AI features, developing front-end interfaces with Streamlit or React, and applying best practices in software engineering. You will also work with cloud platforms like AWS, Azure, and GCP to monitor AI systems in production environments. Required Technical Skills: Core Python Development: Proficiency in Python 3, including syntax, control flow, data structures, functions, error handling, file I/O, modules, decorators, list/dict comprehensions, and exception management. Scientific & Data Libraries: NumPy for array operations, broadcasting; Pandas for data manipulation, aggregation, data cleaning; Database Integration with SQL, SQLite, MongoDB, Postgres, vector DBs (Chroma, PGVector, FIZZ). API Development: RESTful API design with FastAPI or Flask, async/await, dependency injection, request validation, JWT/OAuth2 auth, vector DB integration, and streaming LLM responses. Generative AI / LLMs: Understanding of Transformer architectures, LLMs (GPT, BERT, LLaMA), LangChain, LlamaIndex, Hugging Face Transformers, prompt engineering, parameter tuning, RAG, and agent-based workflows. Deployment & Containerization: Proficiency in Docker, Dockerfiles, Docker Compose, CI/CD pipelines, GitHub Actions, and deploying containerized services. Frontend Development: HTML5, CSS3, modern JavaScript (ES6+), Streamlit, React.js (with TypeScript), building conversational UIs, integrating streaming outputs via WebSockets/SSE. Desirable Skills: Experience with cloud services (AWS, Azure, GCP), monitoring and logging for AI systems, testing frameworks like pytest, httpx, React Testing Library, PDF extraction, OCR tools, frontend accessibility, and performance optimization. Soft Skills: Strong communication and documentation skills, problem-solving mindset, ability to collaborate across cross-functional teams. Educational Qualification: Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or related field. Certifications or hands-on experience in Generative AI/LLMs is a plus. In summary, this role is ideal for individuals passionate about developing end-to-end AI applications using GenAI products, LLMs, APIs, Vector Databases, and modern front-end stacks in a production-ready environment.,

As a Full-Stack AI App Developer at EMO Energy, you will play a key role in reimagining urban mobility, energy, and fleet operations through our AI-driven super app. You will have the opportunity to take full ownership of building and deploying a cutting-edge energy infrastructure startup in India. Your responsibilities will include architecting and developing a full-stack AI-enabled application, designing modular frontend views using React.js or React Native, creating intelligent agent interfaces, building secure backend APIs for managing energy and fleet operations, integrating real-time data workflows, implementing fleet tracking dashboards, and optimizing performance across various platforms. Collaboration with the founding team, ops team, and hardware teams will be essential to iterate fast and solve real-world logistics problems. The ideal candidate for this role should have a strong command of front-end frameworks such as React.js, experience with back-end technologies like FastAPI, Node.js, or Django, proficiency in TypeScript or Python, familiarity with GCP services, Docker, GitHub Actions, and experience with mobile integrations and AI APIs. End-to-end ownership of previous applications, strong UI/UX product sensibility, and experience in building dashboards or internal tools will be valuable assets. Additionally, the ability to adapt to ambiguity, communicate technical decisions to non-engineers, and a passion for clean code and impactful work are crucial for success in this role. If you are a highly motivated individual with a passion for AI-driven applications and a desire to lead the development of a cutting-edge fleet/energy platform, then this role at EMO Energy is the perfect opportunity for you. Join us in revolutionizing the future of urban mobility and energy infrastructure in India.,

We are seeking a Mid-Level LLM Application Developer with 3+ years of experience in software development, who is enthusiastic about constructing intelligent applications utilizing Azure OpenAI, Python, and LLM frameworks. This full-time position is dedicated to the design, development, and implementation of scalable LLM-powered solutions, such as chatbots, knowledge assistants, and RAG-based systems. You will collaborate closely with cross-functional teams to materialize innovative AI solutions, capitalizing on the latest generative AI and agentic technologies. Responsibilities: - Design and develop LLM-powered applications utilizing Python and Azure OpenAI services. - Construct end-to-end Retrieval-Augmented Generation (RAG) pipelines, incorporating vector databases, semantic search, and related tools. - Develop conversational agents and virtual assistants, employing frameworks like LangChain or LlamaIndex. - Create effective prompts using advanced prompt engineering and design techniques. - Integrate LLMs with external tools, APIs, and business data systems. - Apply Agentic AI patterns to RAG and AI Workflows, engaging with LLMs by orchestrating various agents together. - Deploy and manage applications using Azure Functions, Azure AI services, and serverless components. - Ensure performance, scalability, and reliability of AI solutions on Azure. - Collaborate across teams and participate in agile development processes. Required Skills (Must Have): - Proficiency in Python programming language. - Expertise in Azure OpenAI Service, including foundation model usage and integration. - Build and deploy AI solutions leveraging Azure AI services (e.g., Cognitive Services, Azure ML, Azure AI Search). - Deep experience in prompt engineering, including various prompting strategies (few-shot, chain-of-thought, etc.). - Hands-on experience building RAG pipelines with vector databases and tool integrations. - Proven experience developing chatbots or virtual assistants using LLMs. - Proficiency in at least one LLM application framework (e.g., LangChain, LlamaIndex). - In-depth understanding of LLM models, their capabilities, and applications. - Good understanding of LLM evaluations, and how to evaluate LLM model outputs. - Good understanding of using AI Agents and Agentic AI Patterns to integrate with LLMs. - Experience deploying with Azure Function Apps and broader Azure ecosystem. - Solid grasp of API integrations and data workflow design. - Strong problem-solving skills and ability to deliver scalable, efficient code. - Excellent communication and team collaboration abilities. Preferred Skills (Good to Have): - Familiarity with Multi-Agent AI orchestration and agentic workflows. - Experience building cloud-native services with serverless architectures. - Understanding of NLP techniques and data transformation pipelines. - Familiarity with LLMOps concepts and AI model lifecycle. Qualifications: - Bachelor's degree in computer science, Computer Engineering, or a related field. - 3+ years of experience in software development. - Experience with LLM applications and cloud platforms. - Strong understanding of software development methodologies (e.g., Agile). Location: DGS India - Pune - Kharadi EON Free Zone Brand: Dentsu Creative Time Type: Full time Contract Type: Permanent,

About the Role We are hiring a Product Growth Manager to lead initiatives at the intersection of retail, AI, and product execution. This role requires someone who can conceptualize and build AI-native features, scale them effectively, and drive adoption through experimentation, data insights, and structured execution. You will work closely with engineering, machine learning, product, and business teams to deliver AI-powered capabilities that solve real-world retail challenges. The ideal candidate has strong technical foundations, sharp product instincts, and a proven ability to operate with speed and ownership in high-growth environments. What will you do at Fynd Build and launch AI-native product features in collaboration with ML and engineering teams. Drive product-led growth initiatives focused on activation, retention, and adoption. Translate AI/ML capabilities into scalable and intuitive product experiences. Work hands-on with model deployments, inference systems, and API integrations. Own end-to-end product executionfrom problem discovery to roadmap delivery and post-launch iteration. Contribute to platform strategies that scale AI features from MVPs to production-grade adoption. Understand and influence product flows specific to retail, catalog systems, and commerce automation. Some Specific Requirements: AI and Technical Foundations Strong grasp of LLMs, embeddings, vector databases, RAG, and fine-tuning methods like LoRA and QLoRA. Hands-on experience with OpenAI, Hugging Face, LangChain, LlamaIndex, and production-grade AI tooling. Familiar with AI workflows using FastAPI, Docker, MLflow, and model serving via Ray or TorchServe. Comfortable working with GitHub, Git, and tools for managing models, code, and experiments. Good understanding of microservices, API design (REST/GraphQL), and scalable backend systems. Experienced in CI/CD setup for training and deploying ML models to production. Data and Analytics Proficient in SQL, BigQuery, and Looker Studio for data exploration and dashboards. Able to design KPIs, success metrics, and user journey insights for product analytics. Knowledge of tools like dbt, Airflow, and event-based platforms like PostHog or Mixpanel. Experience with A/B testing, funnel analysis, and behavioral cohort tracking. Retail and Product Execution Solid understanding of retail workflows, product catalogs, and commerce ecosystems. Experience building and scaling digital products with real-world user adoption. Strong product judgment and ability to balance business, user, and technical priorities. Stakeholder Management and Execution Leadership Ability to lead and influence cross-functional teams to drive high-quality execution. Strong communication skills to present AI-driven concepts to both technical and non-technical audiences. Experience with Agile methodologies and tools such as Jira, Confluence, and Asana for planning and tracking. Preferred Experience 2 to 5 years in product, growth, or AI-focused roles. Experience in building and scaling AI-powered or technology-driven platforms. Exposure to retail, e-commerce, or SaaS environments. Track record of delivering outcomes in fast-paced, cross-functional teams. Why Join Us Be part of a team shaping the future of AI-native platforms in digital commerce. Work closely with leading AI engineers, product teams, and business stakeholders. Own and execute high-impact initiatives with autonomy and accountability. Operate in a culture that values speed, clarity, and innovation. If you're someone who thrives on execution, loves solving complex problems, and wants to build the future of AI-native platforms, we'd love to have you on board

As an AI/ML Developer at our innovative organization, you will have the exciting opportunity to work on AI initiatives and contribute to the development of innovative solutions. Your key responsibilities will include developing and maintaining applications for AI and LLM projects, conducting data analysis to identify trends and insights for model improvement, designing, developing, and deploying machine learning models for various applications, optimizing algorithms for performance and scalability, and staying up-to-date with the latest advancements in AI. To be successful in this role, you should have a Bachelor's or Master's degree in Computer Science or a related field from a recognized university, with internship experience in AI or related fields being preferred. You should also have demonstrable experience in AI/ML programming and development, proficiency in working with OpenAI technologies and Vector Databases, experience with Large Language Models (LLMs), strong knowledge of LangChain, LLamaIndex, or any other framework, experience with API development and relational databases, excellent problem-solving skills, attention to detail, and the ability to work independently and in a team environment. Join us on this exciting journey to advance AI technology and utilize your skills in machine learning model development, LLM Index, vector databases, algorithm optimization, data analysis, OpenAI technologies, artificial intelligence, API development, large language models (LLMs), AI/ML programming, and relational databases to make a significant impact in the field of AI.,