696 Langchain Jobs - Page 27

Preferred candidate profile 1. LLM Basics : (Llama, Gemini ) : Understand the basics of generative AI and LLMs, such as key terminology, uses, potential issues, and primary frameworks. One should know what the data is trained on and any potential biases/issues that there may be with the data . Knowledge on know exactly how big LLMs can be, how computationally expensive training will be, and the differences between training LLMs and machine learning models. 1. Prompt Engineering : Knowledge on designing inputs for LLMs once theyre developed. 2. Prompt Engineering with OpenAI : As a leading figure in LLMs and generative AI, it’s important to know how to use prompt engineering specifically with OpenAI tools, as you’ll likely be using them at some point in your career. 3. Question-Answering :Question-answering (QA) LLMs are a type of large language model that has been trained specifically to answer questions. 4. Fine-Tuning : Knowledge on Fine-tuning to improve the performance of an LLM on a variety of tasks, including text generation, translation, summarization, and question-answering. Customize LLMs for specific applications, such as customer service chatbots or medical diagnosis systems. Awareness on supervised learning. This involves providing the LLM with a dataset of labelled data, where each data point is a pair of input and output.. 1. Lang Chain : To architect complex LLM pipelines by chaining multiple models together (Classification, text generation, code generation, etc.)`Agents` to interact with all these external systems to execute actions dictated by LLMs. 2. Parameter Efficiency/Tuning : LORA 3. RAG Building : Generative AI, mastering RAG building—short for Retrieval-Augmented Generation—is becoming increasingly crucial 4. ML OPS and in particular LLMOps : Large Language Model Operations, is the practice of managing and maintaining large language models (LLMs) in a production setting 5. TensorFlow i s like a versatile toolbox for creating intelligent programs that can learn and understand various concepts, including machine learning, deep learning, and data science

Job Type: Full Time Job Description: We are seeking an experienced AI Engineer with 4-5 years of hands-on experience in designing and implementing AI solutions. The ideal candidate should have a strong foundation in developing AI/ML-based solutions, including expertise in Computer Vision (OpenCV). Additionally, proficiency in developing, fine-tuning, and deploying Large Language Models (LLMs) is essential. As an AI Engineer, candidate will work on cutting-edge AI applications, using LLMs like GPT, LLaMA, or custom fine-tuned models to build intelligent, scalable, and impactful solutions. candidate will collaborate closely with Product, Data Science, and Engineering teams to define, develop, and optimize AI/ML models for real-world business applications. Key Responsibilities: Research, design, and develop AI/ML solutions for real-world business applications, RAG is must. Collaborate with Product & Data Science teams to define core AI/ML platform features. Analyze business requirements and identify pre-trained models that align with use cases. Work with multi-agent AI frameworks like LangChain, LangGraph, and LlamaIndex. Train and fine-tune LLMs (GPT, LLaMA, Gemini, etc.) for domain-specific tasks. Implement Retrieval-Augmented Generation (RAG) workflows and optimize LLM inference. Develop NLP-based GenAI applications, including chatbots, document automation, and AI agents. Preprocess, clean, and analyze large datasets to train and improve AI models. Optimize LLM inference speed, memory efficiency, and resource utilization. Deploy AI models in cloud environments (AWS, Azure, GCP) or on-premises infrastructure. Develop APIs, pipelines, and frameworks for integrating AI solutions into products. Conduct performance evaluations and fine-tune models for accuracy, latency, and scalability. Stay updated with advancements in AI, ML, and GenAI technologies. Required Skills & Experience: AI & Machine Learning: Strong experience in developing & deploying AI/ML models. Generative AI & LLMs: Expertise in LLM pretraining, fine-tuning, and optimization. NLP & Computer Vision: Hands-on experience in NLP, Transformers, OpenCV, YOLO, R-CNN. AI Agents & Multi-Agent Frameworks: Experience with LangChain, LangGraph, LlamaIndex. Deep Learning & Frameworks: Proficiency in TensorFlow, PyTorch, Keras. Cloud & Infrastructure: Strong knowledge of AWS, Azure, or GCP for AI deployment. Model Optimization: Experience in LLM inference optimization for speed & memory efficiency. Programming & Development: Proficiency in Python and experience in API development. Statistical & ML Techniques: Knowledge of Regression, Classification, Clustering, SVMs, Decision Trees, Neural Networks. Debugging & Performance Tuning: Strong skills in unit testing, debugging, and model evaluation. Hands-on experience with Vector Databases (FAISS, ChromaDB, Weaviate, Pinecone). Good to Have: Experience with multi-modal AI (text, image, video, speech processing). Familiarity with containerization (Docker, Kubernetes) and model serving (FastAPI, Flask, Triton).

Role & responsibilities We are looking for Gen AI Engineer position permanent position with US MNC for Bangalore/Chennai/Pune/Noida/Gurgaon location (Hybrid). Preferred candidate profile Experience Hands-on engineering role focused on designing, building, and deploying Generative AI and LLM-based solutions. The role requires deep technical proficiency in Python and modern LLM frameworks with the ability to contribute to roadmap development and cross-functional collaboration. Key Responsibilities: Design and develop GenAI/LLM-based systems using tools such as Langchain and Retrieval-Augmented Generation (RAG) pipelines. Implement prompt engineering techniques and agent-based frameworks to deliver intelligent, context-aware solutions. Collaborate with the engineering team to shape and drive the technical roadmap for LLM initiatives. Translate business needs into scalable, production-ready AI solutions. Work closely with business SMEs and data teams to ensure alignment of AI models with real-world use cases. Contribute to architecture discussions, code reviews, and performance optimization. Skills Required: Proficient in Python, Langchain, and SQL. Understanding of LLM internals, including prompt tuning, embeddings, vector databases, and agent workflows. Background in machine learning or software engineering with a focus on system-level thinking. Experience working with cloud platforms like AWS, Azure, or GCP. Ability to work independently while collaborating effectively across teams. Excellent communication and stakeholder management skills. Preferred Qualifications: Hands-on experience in LLMs and Generative AI techniques. Experience contributing to ML/AI product pipelines or end-to-end deployments. Familiarity with MLOps and scalable deployment patterns for AI models. Prior exposure to client-facing projects or cross-functional AI teams.

Role & responsibilities We are looking for Gen AI Engineer position permanent position with US MNC for Bangalore/Chennai/Pune/Noida/Gurgaon location (Hybrid). Preferred candidate profile Experience Hands-on engineering role focused on designing, building, and deploying Generative AI and LLM-based solutions. The role requires deep technical proficiency in Python and modern LLM frameworks with the ability to contribute to roadmap development and cross-functional collaboration. Key Responsibilities: Design and develop GenAI/LLM-based systems using tools such as Langchain and Retrieval-Augmented Generation (RAG) pipelines. Implement prompt engineering techniques and agent-based frameworks to deliver intelligent, context-aware solutions. Collaborate with the engineering team to shape and drive the technical roadmap for LLM initiatives. Translate business needs into scalable, production-ready AI solutions. Work closely with business SMEs and data teams to ensure alignment of AI models with real-world use cases. Contribute to architecture discussions, code reviews, and performance optimization. Skills Required: Proficient in Python, Langchain, and SQL. Understanding of LLM internals, including prompt tuning, embeddings, vector databases, and agent workflows. Background in machine learning or software engineering with a focus on system-level thinking. Experience working with cloud platforms like AWS, Azure, or GCP. Ability to work independently while collaborating effectively across teams. Excellent communication and stakeholder management skills. Preferred Qualifications: Hands-on experience in LLMs and Generative AI techniques. Experience contributing to ML/AI product pipelines or end-to-end deployments. Familiarity with MLOps and scalable deployment patterns for AI models. Prior exposure to client-facing projects or cross-functional AI teams.

Seeking a highly skilled and motivated Senior Generative AI Developer with approximately 2 years of hands-on experience in developing and deploying AI models, particularly in the generative space (e.g., NLP, AL/ML, AWS, Python, RASA, MCP, Flutter). Required Candidate profile 2+ yrs of exp in AI/ML dev, with focus on gen models. Prog skills in Python & ML libraries/frameworks Langchain, spacy, NLTK, Hugging Face Exp in AI bot/agent platforms like Make, POE, RetellAI

In this role you will: Develop and fine-tune LLMs for contract analysis, regulatory classification, and risk assessment. Implement Retrieval-Augmented Generation (RAG) using vector embeddings and hybrid DB-based querying to power DPIA and compliance workflows. Build AI-driven contract analysis systems to detect dark patterns, classify clauses, and provide remediation suggestions. Develop knowledge graph-based purpose taxonomies for privacy policies and PII classification. Automate data discovery for structured and unstructured data, classifying it into PII categories. Optimize sliding window chunking, token-efficient parsing, and context-aware summarization for legal and compliance texts. Build APIs and ML services for deploying models in a high-availability production environment. Collaborate with privacy, legal, and compliance teams to build AI solutions that power Privy s data governance tools. Stay ahead of the curve with agentic RAG, multi-modal LLMs, and self-improving models in the compliance domain. Skills Required: LLM , RAG , AgenticAI , NLP , Python , Problem solving Candidate Attributes: Must-Have Skills 3-5 years of experience in Machine Learning, NLP, and LLM-based solutions. Strong expertise in fine-tuning and deploying LLMs (GPT-4, Llama, Mistral, or custom models). Experience with RAG-based architectures, including vector embeddings (FAISS, ChromaDB, Weaviate, Pinecone, or similar). Hands-on with agentic RAG, sliding window chunking, and efficient context retrieval techniques. Deep understanding of privacy AI use cases, including contract analysis, regulatory classification, and PII mapping. Proficiency in Python and frameworks like PyTorch, TensorFlow, JAX, Hugging Face, or LangChain. Experience in building scalable AI APIs and microservices. Exposure to MLOps practices, including model monitoring, inference optimization, and API scalability. Experience working with at least one cloud provider (AWS, GCP, or Azure). Good-to-Have Skills Experience in hybrid AI architectures combining vector search + relational databases. Familiarity with functional programming languages (Go, Elixir, Rust, etc.). Understanding of privacy compliance frameworks (DPDP Act, GDPR, CCPA, ISO 27701). Exposure to Kubernetes, Docker, and ML deployment best practices. Contributions to open-source LLM projects or privacy AI research.

We're looking for an experienced AI/ML Technical Lead to architect and drive the development of our intelligent conversation engine. Youll lead model selection, integration, training workflows (RAG/fine-tuning), and scalable deployment of natural language and voice AI components. This is a foundational hire for a technically ambitious platform. Role & responsibilities AI System Architecture: Design the architecture of the AI-powered agent including LLM-based conversation workflows, voice bots, and follow-up orchestration. Model Integration & Prompt Engineering: Leverage APIs from OpenAI, Anthropic, or deploy open models (e.g., LLaMA 3, Mistral). Implement effective prompt strategies and retrieval-augmented generation (RAG) pipelines for contextual responses. Data Pipelines & Knowledge Management: Build secure data pipelines to ingest, embed, and serve tenant-specific knowledge bases (FAQs, scripts, product docs) using vector databases (e.g., Pinecone, Weaviate). Voice & Text Interfaces: Implement and optimize multimodal agents (text + voice) using ASR (e.g., Whisper), TTS (e.g., Polly), and NLP for automated qualification and call handling. Conversational Flow Orchestration: Design dynamic, stateful conversations that can take actions (e.g., book meetings, update CRM records) using tools like LangChain, Temporal, or n8n. Platform Scalability: Ensure models and agent workflows scale across tenants with strong data isolation, caching, and secure API access. Lead a Cross-Functional Team: Collaborate with backend, frontend, and DevOps engineers to ship intelligent, production-ready features. Monitoring & Feedback Loops: Define and monitor conversation analytics (drop-offs, booking rates, escalation triggers), and create pipelines to improve AI quality continuously. Preferred candidate profile Qualifications Must-Haves: 5+ years of experience in ML/AI, with at least 2 years leading conversational AI or LLM projects. Strong background in NLP, dialog systems, or voice AI preferably with production experience. Experience with OpenAI, or open-source LLMs (e.g. LLaMA, Mistral, Falcon) and orchestration tools (LangChain, etc.). Proficiency with Python and ML frameworks (Hugging Face, PyTorch, TensorFlow). Experience deploying RAG pipelines, vector DBs (e.g. Pinecone, Weaviate), and managing LLM-agent logic. Familiarity with voice processing (ASR, TTS, IVR design). Solid understanding of API-based integration and microservices. Deep care for data privacy, multi-tenancy security, and ethical AI practices. Nice-to-Haves: Experience with CRM ecosystems (e.g. Salesforce, HubSpot) and how AI agents sync actions to CRMs. Knowledge of sales pipelines and marketing automation tools. Exposure to calendar integrations (Google Calendar API, Microsoft Graph). Knowledge of Twilio APIs (SMS, Voice, WhatsApp) and channel orchestration logic. Familiarity with Docker, Kubernetes, CI/CD, and scalable cloud infrastructure (AWS/GCP/Azure). What We Offer Founding team role with strong ownership and autonomy Opportunity to shape the future of AI-powered sales Flexible work environment Competitive salary Access to cutting-edge AI tools and training resources Post your resume and any relevant project links (GitHub, blog, portfolio) to career@sourcdeskglobal.com. Include a short note on your most interesting AI project or voicebot/conversational AI experience.

Role & responsibilities Expertise in Data Analysis, Statistics, Computer Vision, AI & Machine Learning Concepts Unflinching zeal to learn, to try out Proof of Technology for new and emerging AI/ML Design and develop applications powered by Large Language Models (LLMs) like GPT-4, Claude, Gemini, and open-source models (LLaMA, Mistral, etc.) Implement RAG pipelines using LangChain and LangGraph for production-ready applications. Build and orchestrate autonomous and tool-using LLM agents. Integrate with vector databases (e.g., Pinecone, Chroma, Weaviate, FAISS) for semantic search and memory storage. Use tools like OpenAI Function Calling, React, or LangGraph Agents for decision-based workflows. Deploy applications using cloud platforms (Azure, AWS, GCP) with APIs, microservices, or serverless functions. Collaborate with product and design teams to develop chatbots, copilots, and multimodal interfaces. Monitor performance, cost, latency, and evaluate prompt effectiveness through prompt engineering best practices. Fine-tune, quantize, or use adapters (LoRA, PEFT) for open-source models where applicable. Stay up-to-date with the latest advancements in Gen AI, MLOps, and AI safety principles. Preferred candidate profile Bachelor's/Master's degree in Computer Science, Mathematics, Statistics, or a related field. 4-9 years of experience as a Data Scientist with strong skills in Python, NLP, Deep Learning, and Statistics. Hands-on experience with Generative AI, LangChain, LangGraph, and building LLM Agents for real-world AI applications. Strong Python skills with experience in deploying Gen AI apps using frameworks like FastAPI or Streamlit. Expertise in Retrieval-Augmented Generation (RAG) and working with vector databases like Pinecone, FAISS, or Chroma. Deep understanding of prompt engineering, OpenAI function calling, and chaining logic for dynamic interactions. Familiarity with cloud platforms such as Azure and AWS and deploying models to these platforms. Strong problem-solving and analytical skills with excellent communication and presentation skills. Disclaimer: The following job description serves as an informative reference for the tasks you may be required to perform. However, it does not constitute an integral component of your employment agreement and is subject to periodic modifications to align with evolving circumstances

We're building an AI-first SEO Agent that acts, not just audits. Looking for a Co-Founder & CTO to lead dev, shape product, and co-invest. Equity + capital upside. Required Candidate profile Co-Founder & CMO at SEO Scientist Having 6 years of expereince in the SEO & Marketing domain Perks and benefits Remote, flexible, fast-paced, equity, real AI

We are seeking a talented AI Engineer to join our team. The ideal candidate will have expertise in machine learning, NLP, deep learning, and deploying AI models, with experience in advanced tools and frameworks across AI and backend development. Responsibilities: Develop and deploy AI models using machine learning , deep learning (CNNs, RNNs, LSTMs), and NLP ( GPT , BERT ). Work with advanced AI frameworks ( Langchain , AutoGen , Streamlit ) and backend frameworks ( FastAPI , Flask ). Implement reinforcement learning and autonomous decision-making systems. Leverage cloud platforms ( AWS: Bedrock, Sagemaker ) for model deployment and scalability. Integrate third-party services ( OpenAI , Azure Foundry ) and tools ( RelevanceAI , Huggingface ). Work with databases ( MongoDB , Postgres , Redis ) and distributed systems. Utilize advanced AI techniques like RAG , fine-tuning , LoRA , QLoRA , multi-model systems , and stable diffusion . Explore AI applications in video generation models ( text-to-video , image-to-video ). Skills Needed: Expertise in AI frameworks : Langchain , AutoGen , Streamlit . Strong experience with FastAPI , Flask , and cloud platforms ( AWS , Bedrock , Sagemaker ). Knowledge of third-party services ( OpenAI , Azure Foundry ) and tools ( RelevanceAI , Huggingface ). Solid experience with databases ( MongoDB , Postgres , Redis ). Proficient in machine learning , deep learning , NLP , and reinforcement learning . Hands-on experience with advanced AI techniques: RAG , fine-tuning , LoRA , QLoRA , SLM , LLM , stable diffusion , and video generation models .

About the job: Key responsibilities: 1. Build and refine LLM-powered agents using OpenAI, Groq or HuggingFace 2. Collaborate via Cursor for fast-paced 'vibe coding' workflows 3. Design frontend UIs in React/Next.js with Tailwind or ShadCN 4. Develop backends with FastAPI (Python) or Node.js 5. Integrate and experiment with Langchain/LangGraph/Vector DBs 6. Push MVPs rapidly and iterate efficiently Requirements: 1. Demonstrate 1-2 years of experience in full-stack or AI-focused development 2. Show prior experience using Cursor.dev for collaborative coding 3. Apply solid understanding of modern web stack (React, Next.js, FastAPI, Node.js) 4. Utilize familiarity with LLM APIs (OpenAI, HuggingFace, Groq) 5. Bonus: Experience with agent frameworks, chaining, and vector databases 6. Commit 3-5 hours daily during fixed, agreed-upon time slots 7. Seek to build portfolio projects or transition into an AI specialization Tech Stack We Use: 1. Frontend: React.js, Next.js, Tailwind, ShadCN 2. Backend: FastAPI (Python), Node.js 3. AI/LLM: OpenAI, Groq, HuggingFace, Langchain, LangGraph 4. Tools: Cursor.dev, Git, Vercel, Render, Docker, Pinecone/Weaviate What you'll get: 1. Own real projects and receive GitHub credit 2. Work closely with the founder and the small team 3. Maintain part-time flexibility alongside other commitments 4. Enjoy flexible hours with regular daily sync slots 5. Gain exposure to emerging AI agent technologies 6. Earn bonus pay/recognition for outstanding contributions Who can apply: Only those candidates can apply who: have minimum 1 years of experience are Computer Science Engineering students Salary: ₹ 2,00,000 - 5,00,000 /year Experience: 1 year(s) Deadline: 2025-06-21 23:59:59 Skills required: Python, Node.js, React Native, FastAPI, LangChain and Cursor (GenAI) About Company: TopSystems builds productivity-first software that helps solopreneurs and small teams punch far above their weight. Our forthcoming SaaS delivers an on-demand executive suite of AI Agents strategy, ops, finance, marketing, and more, so founders can plan, decide, and execute faster than ever. We iterate quickly, keep pricing founder-friendly, and obsess over real business outcomes. If you love building with the latest AI tools and want to ship features that truly matter, you'll feel right at home.

About the role PubMatic is seeking Data Analytics-focused Senior Software Engineers with expertise in building and optimizing AI agents, including strong skills in Hadoop, Spark, Scala, Kafka, Spark Streaming, and cloud-based solutions, with proficiency in programming languages such as Scala and Python. You will be responsible for developing advanced AI agents that enhance our data analytics capabilities, enabling our platform to handle complex information retrieval, contextual understanding, and adaptive interactions, ultimately improving our data-driven insights and analytical workflows. What You'll Do Build, design, and implement our highly scalable, fault-tolerant big data platform to process terabytes of data and provide customers with in-depth analytics. Develop backend services using Java, REST APIs, JDBC, and AWS. Build and maintain Big Data pipelines using technologies like Spark, Hadoop, Kafka, and Snowflake. Architect and implement real-time data processing workflows and automation frameworks. Design and develop GenAI-powered agents for analytics, operations, and data enrichment use cases using frameworks like LangChain, LlamaIndex, or custom orchestration systems. Integrate LLMs (e.g., OpenAI, Claude, Mistral) into existing services for query understanding, summarization, and decision support. Manage end-to-end GenAI workflows including prompt engineering, fine-tuning, vector embeddings, and retrieval-augmented generation (RAG). Working closely with cross-functional teams on improving the availability and scalability of large data platforms and the functionality of PubMatic software. Participate in Agile/Scrum processes such as sprint planning, sprint retrospective, backlog grooming, user story management, and work item prioritization. Frequently discuss with product managers about the software features to include in the PubMatic Data Analytics platform. Support customer issues over email or JIRA (bug tracking system), provide updates, and patches to customers to fix the issues. Perform code and design reviews for code implemented by peers or as per the code review process. We'd Love for You to Have Three to six years of coding experience in Java and backend development. Solid computer science fundamentals, including data structure and algorithm design, and creation of architectural specifications. Expertise in developing the Implementation of professional software engineering best practices for the full software development life cycle, including coding standards, code reviews. Hands-on experience with Big Data tools and systems like Scala Spark, Kafka, Hadoop, and Snowflake. Proven expertise in building GenAI applications, including: LLM integration (OpenAI, Anthropic, Cohere, etc.) LangChain, or similar agent orchestration libraries Prompt engineering, embeddings, and retrieval-based generation (RAG) Experience in developing and deploying scalable, production-grade AI or data systems. Ability to lead end-to-end feature development and debug distributed systems. Experience in developing and delivering large-scale big data pipelines, real-time systems & data warehouses would be preferred. Demonstrated ability to achieve stretch goals in a very innovative and fast-paced environment. Demonstrated ability to learn new technologies quickly and independently. Excellent verbal and written communication skills, especially in technical communications. Strong interpersonal skills and a desire to work collaboratively. Qualifications Should have a bachelor's degree in engineering (CS / IT) or equivalent degree from a well-known institute/university. Apply to the link below: https://pubmatic.com/job/?gh_jid=4692032008

What Youll Own Full Stack Systems: Architect and build end-to-end applications using Flask, FastAPI, Node.js, React (or Next.js), and Tailwind. AI Integrations: Build and optimize pipelines involving LLMs (OpenAI, Groq, LLaMA), Whisper, TTS, embeddings, RAG, LangChain, LangGraph, and vector DBs like Pinecone/Milvus. Cloud Infrastructure: Deploy, monitor, and scale systems on AWS/GCP using EC2, S3, IAM, Lambda, Kafka, and ClickHouse. Real-time Systems: Design asynchronous workflows (Kafka, Celery, WebSockets) for voice-based agents, event tracking, or search indexing. System Orchestration: Set up scalable infra with autoscaling groups, Docker, and Kubernetes (PoC ready, if not full prod). Growth-Ready Features: Implement in-app nudges, tracking with Amplitude, AB testing, and funnel optimization. Must-Haves: 1+ years of experience building production-grade full-stack systems Fluency in Python and JS/TS (Node.js, React) shipping independently without handholding Deep understanding of LLM pipelines, embeddings, vector search, and retrieval-augmented generation (RAG) Experience with AR frameworks (ARKit, ARCore), 3D rendering (Three.js), and real-time computer vision (MediaPipe) Strong grasp of modern AI model architectures: Diffusion Models, GANs, AI Agent Hands-on with system debugging, performance profiling, infra cost optimization Comfort with ambiguity fast iteration, shipping prototypes, breaking things to learn faster Bonus if youve built agentic apps, AI workflows, or virtual try-ons

Role & responsibilities We are looking for Data Scientist position with US MNC company for permanent role, Remote. Preferred candidate profile Mandatory Skills : 5 Years + relevant experience in data science. Experience in RAG implementation pipeline. Experience with AI/ML Frameworks like TensorFlow, PyTorch, or similar. Proficiency in Programming Languages such as Python, SQL, and other relevant languages. Experience in the Financial Services Industry and an understanding of compliance standards. (Preferred) Experience with Master data management, Data Wrangling and ETL Processes. Experience with data and AI/ML Technologies: Such as NLP/NLU, Azure Cognitive Services, Azure Synapse Analytics, Azure data bricks and Azure ML service. Certification in Data Science or AI/ML.

The Service Enablement team is responsible for providing products and solutions that enable better and higher quality service delivery across the organization. Their primary focus is on facilitating the successful implementation and integration of these products, ensuring that they align with business needs and enhance the overall user experience. This involves offering comprehensive training and support to users, gathering feedback to drive continuous improvement, and optimizing processes to maximize efficiency. The Impact : Are you looking for an opportunity to advance your career as an innovative enterprise leader? The Platform & Tools team is seeking for an innovative professional who can bring leadership, creativity, and Product Management experience to a global team. Whats in it for you : As a Product Leader, you'll spearhead AI innovations and advance your career in enterprise leadership. You'll engage with cutting-edge technologies and gain valuable product management experience. Contribute to transformative initiatives that redefine the future of service delivery. Responsibilities : In your daily role, you will drive in the innovation, development, implementation, and adoption of product strategies that align with organizational goals. You will evaluate industry-leading technologies, conduct analyses to identify value-driven solutions, and monitor product performance. Your responsibilities will also include mentoring team members, facilitating training, and ensuring timely delivery of high-quality products. By promoting a culture of innovation, you will support the adoption of AI technologies and contribute to the success of the Service Enablement team. Product Leadership & Strategy Define and own the product vision, strategy, and roadmap for Service Enablement products, ensuring alignment with organizational goals and customer needs. Identify opportunities to leverage AI and intelligent workflows to streamline business operations and enhance user productivity. Guide cross-functional teams in delivering impactful and scalable products that meet market demands. AI and Emerging Technology Integration Evaluate and integrate cutting-edge AI capabilities, including large language models (LLMs), autonomous agents, machine learning workflows, and AI-driven decision-making frameworks. Collaborate with AI/ML research and engineering teams to develop innovative features that transform service delivery and support models. Stay updated on trends in AI and productivity platforms to apply relevant technologies. Customer & Market Insight Develop an understanding of user personas and pain points to drive effective product design. Conduct market research and competitive analysis to ensure product differentiation. Analyze product usage data and customer feedback to optimize features and outcomes. Execution & Delivery Support product strategy planning, prioritization, and execution throughout the product lifecycle. Collaborate with enterprise stakeholders to ensure alignment and success. Contribute to product OKRs and continuous improvement through agile practices. Team Leadership Mentor and develop a high-performing team of product managers. Foster a culture of innovation, accountability, and customer-centric thinking within the product organization. Qualifications: Over 7 years of product management experience or similar roles, with a proven track record of success. Experience in leading enterprise platforms and initiatives. Strong understanding of customer and market dynamics within the service enablement discipline. Customer-focused mindset with a history of delivering impactful solutions. Knowledge of AI technologies, including generative AI and intelligent workflow systems. Experience working in agile environments with cross-functional teams. Excellent leadership, communication, and stakeholder management skills. Bachelors or Masters degree in Computer Science, Engineering, Business, or a related field. Willingness to work flexible hours to meet business needs. Preferred Qualifications SAFe Certification. Experience with Service Management platforms such as Service Now, Jira Service Management, Moveworks, Aisera, etc. Familiarity with AI frameworks and tools such as OpenAI, LangChain, or AutoGPT. Proficient in measuring impact with a data-driven approach.

Minimum of 5 years of experience in Python application development. Strong proficiency in Python programming language and its ecosystem. Solid understanding of software development principles, data structures, and algorithms. Experience with web frameworks such as Angular or React. Proficiency in relational databases (e.g., PostgreSQL, MySQL) and ORM libraries. Experience with version control systems such as Git. Strong problem-solving skills and ability to think algorithmically. Excellent communication and interpersonal skills. Ability to work effectively both independently and as part of a team in a fast-paced environment. Experience with cloud platforms (e.g., AWS ) and containerization technologies (e.g., Docker, Kubernetes) is a plus. Familiarity with Agile development methodologies. Familiarity with ML/chatbot applications development, LangChain, OpenAI or any other LLM models

Job description Technical Lead (Enterprise AI Systems) We are seeking a Technical Lead to drive the design and development of our enterprise-grade AI product. This role requires a deep understanding of AI/ML systems, cloud-native architectures, and scalable software design. The applicant should have mandatorily worked on enterprise grade AI product or project for at least 2 - 3 years. This role includes at least 50% hands on development, 30% LLD and the remaining 20% of HLD / Architecture. The role is on the technical career path and is NOT suitable for project managers, technical managers, engineering managers etc. Key Responsibilities: Develop scalable, modular, and secure AI-driven software systems. Design APIs, microservices, and cloud infrastructure for AI workloads. Ensure seamless AI model integration and efficient scaling. Optimize performance & scalability of systems. Implement caching, load balancing, and distributed computing. Ensure security compliance (GDPR, SOC2) and secure data handling. Enforce best practices in authentication, encryption, and API security. Mandatory Skills & Qualifications: Experience: 8 - 10 years in software architecture & design, with at least 3+ years focused on AI/ML product design & development. Last 1 - 2 years should include deep Gen AI experience in enterprise grade AI projects or applications. Experience with design and developing applications with LLMs, RAG Applications, Gen AI Agents. Fine-tuning open-source LLMs. Experience with deploying and monitoring LLMs. Experience with LLM evaluation frameworks or tools like DeepEval, Langfuse or similar. Experience with frameworks like langchain, llamaindex, pydantic etc. Proficiency in RDBMS like PostgreSQL and knowledge of vector databases (eg: chromadb,Pinecone, FAISS, Weaviate). Strong background in microservices, RESTful & GraphQL APIs, event-driven architectures, Working experience with Kafka, RabbitMQ etc... Proficient in Python, Java for backend development Experience with TensorFlow, PyTorch, Hugging Face etc... Skilled in data processing (NumPy, Pandas, Dask,NLTK) and front-end (TypeScript, React.js). Experience in scalable AI systems, data pipelines, MLOps, and real-time inference. Strong understanding of security protocols, IAM, OAuth2, JWT, RBAC. Expertise in cloud platforms (AWS, GCP, Azure), Kubernetes, Docker. Hands-on experience with CI/CD (Eg: github,Jenkins etc...) Hands-on with system monitoring (Eg: ELK Stack,OpenTelemetry, Prometheus, Grafana). Nice-to-Have Skills: Ensuring AI model interpretability, fairness, and bias mitigation strategies. Optimizing model inference using quantization, distillation, and pruning techniques. Experience in deploying AI models in production at scale, including MLOps best practices. Designing AI systems with privacy-preserving techniques (differential privacy, homomorphic encryption etc.). Experience with knowledge graph-based AI applications.

About the job: The Red Hat, Experience Engineering (XE) team is looking for a skilled Python Developer with 2+ years of experience to join our Software Engineering team. In this role, the ideal candidate should have a strong background in Python development, a deep understanding of LLMs, and the ability to debug and optimize AI applications. Your work will directly impact our product development, helping us drive innovation and improve the customer experience. What will you do? Develop and maintain Python-based applications, integrating LLMs and AI-powered solutions. Collaborate with cross-functional teams (product managers, software engineers, and data teams) to understand requirements and translate them into data-driven solutions. Assist in the development, testing, and optimization of AI-driven features. Optimize performance and scalability of applications utilizing LLMs. Debug and resolve Python application errors, ensuring stability and efficiency. Conduct exploratory data analysis and data cleaning to prepare raw data for modelling. Optimize and maintain data storage and retrieval systems for model input/output. Research and experiment with new LLM advancements and AI tools to improve existing applications. Document workflows, model architectures, and code to ensure reproducibility and knowledge sharing across the team. What will you bring? Bachelor's degree in Computer Science, Software Engineering, or a related field with 2+ years of relevant experience. Strong proficiency in Python, including experience with frameworks like FastAPI/ Flask, or Django. Understanding of fundamental AI/ML concepts, algorithms, techniques and implementation of workflows. Familiarity with DevOps/MLOps practices and tools for managing the AI/ML lifecycle in production environments. Understanding of LLM training processes and data requirements. Experience in LLM fine-tuning, RAG and prompt engineering. Hands-on experience with LLMs (e.g., OpenAI GPT, Llama, or other transformer models) and their integration into applications(e.g. LangChain or Llama Stack). Familiarity with REST APIs, data structures, and algorithms. Strong problem-solving skills with the ability to analyze and debug complex issues. Experience with Git, CI/CD pipelines, and Agile methodologies. Experience working with cloud-based environments (AWS, GCP, or Azure) is a plus. Knowledge of vector databases (e.g., Pinecone, FAISS, ChromaDB) is a plus.

Job Description & Responsibilities Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams. Qualification, Skills & Experience Good hands-on experience in Advanced Python Programming Experiences in scalable Microservice Architecture and Development Good understanding of API Development, Messaging Queues and Asynchronous Task Management Basic DevOp skills and working with Docker Experience with LangChain, LangGraph, AutoGen or CrewAI are a big plus Ability to co-work in a small team with different locations Ability to learn and understand a new Python framework

We are seeking a proficient AI/ML Engineer responsible for testing, deploying, and hosting various Large Language Models (LLMs). The role involves monitoring deployed agentic services, ensuring their optimal performance, and staying abreast of the latest advancements in AI technologies. Key Responsibilities: LLM Deployment & Hosting Evaluate, test, and deploy diverse LLMs on cloud-based and on-premise infrastructures. Optimize model performance for scalability and efficiency. Implement secure API endpoints and model-serving pipelines. Strong CI/CD skills and knowledge of CI/CD tools like Jenkins, GitHub Actions, CircleCI etc. Agentic AI Services Deploy and maintain AI agents using frameworks such as CrewAI, Agnos(Phi Data), AutoGen etc. Integrate LLMs into business workflows and automation tools. Design, monitor, and enhance agentic services for real-world applications. Monitoring & Optimization Utilize advanced observability tools to monitor model performance, latency, and cost efficiency. Implement tools like AgentOps, OpenLIT, Langfuse, and Langtrace for comprehensive monitoring and debugging of LLM applications. Develop logging, tracing, and alerting systems for deployed models and AI agents. Conduct A/B testing and gather user feedback to refine AI behavior. Address model drift and retrain models as necessary. Best Practices & Research Stay updated with the latest advancements in AI, LLMs, and agentic systems. Implement best practices for prompt engineering, reinforcement learning from human feedback (RLHF), and fine-tuning methodologies. Optimize compute costs and infrastructure usage for AI applications. Collaborate with researchers and ML engineers to integrate state-of-the-art AI techniques. Strong knowledge on version control tools like GitHub Qualifications & Skills: Proficiency with LLM frameworks such as Hugging Face Transformers, OpenAI API, or Meta AI models. Strong programming skills in Python and experience with deep learning libraries (PyTorch, TensorFlow, JAX). Experience with cloud platforms (AWS, Azure, GCP) and model deployment tools (Docker, Kubernetes, FastAPI, Ray Serve). Familiarity with vector databases (FAISS, Pinecone, Weaviate) and retrieval-augmented generation (RAG) techniques. Hands-on experience with monitoring tools such as AgentOps, OpenLIT, Langfuse, and Langtrace. Understanding of prompt engineering, LLM fine-tuning, and agent-based automation. Excellent problem-solving skills and the ability to work in a dynamic AI research and deployment team. Preferred Qualifications: Experience in reinforcement learning, fine-tuning LLMs, or training custom models. Knowledge of security best practices for AI applications. Contributions to open-source AI/ML projects or research publications in the field.

We are looking for an AI Engineer (Senior Software Engineer). Interested candidates email me resumes on mayura.joshi@lionbridge.com OR WhatsApp on 9987538863 Responsibilities: Design, develop, and optimize AI solutions using LLMs (e.g., GPT-4, LLaMA, Falcon) and RAG frameworks. Implement and fine-tune models to improve response relevance and contextual accuracy. Develop pipelines for data retrieval, indexing, and augmentation to improve knowledge grounding. Work with vector databases (e.g., Pinecone, FAISS, Weaviate) to enhance retrieval capabilities. Integrate AI models with enterprise applications and APIs. Optimize model inference for performance and scalability. Collaborate with data scientists, ML engineers, and software developers to align AI models with business objectives. Ensure ethical AI implementation, addressing bias, explainability, and data security. Stay updated with the latest advancements in generative AI, deep learning, and RAG techniques. Requirements: 8+ years experience in software development according to development standards. Strong experience in training and deploying LLMs using frameworks like Hugging Face Transformers, OpenAI API, or LangChain. Proficiency in Retrieval-Augmented Generation (RAG) techniques and vector search methodologies. Hands-on experience with vector databases such as FAISS, Pinecone, ChromaDB, or Weaviate. Solid understanding of NLP, deep learning, and transformer architectures. Proficiency in Python and ML libraries (TensorFlow, PyTorch, LangChain, etc.). Experience with cloud platforms (AWS, GCP, Azure) and MLOps workflows. Familiarity with containerization (Docker, Kubernetes) for scalable AI deployments. Strong problem-solving and debugging skills. Excellent communication and teamwork abilities Bachelors or Masters degree in computer science, AI, Machine Learning, or a related field.

Roles and Responsibilities Design, develop, test, and maintain backend systems using Python and other technologies. Develop algorithms for data processing and analysis using open APIs and Langchain. Ensure system architecture meets performance, scalability, and reliability standards. Collaborate with cross-functional teams to identify requirements and implement solutions. Troubleshoot issues related to system design and implementation. Desired Candidate Profile 2-7 years of experience in software development with a focus on backend engineering. B.Tech/B.E. degree from any specialization (preferred). Strong understanding of algorithm development, problem-solving skills, teamwork abilities, and proficiency in Open API.

Summary of the Role: We are seeking an AI Prompt Engineer with expertise in Large Language Models (LLMs) and prompt engineering to support legal tech solutions, specifically in contract lifecycle management and contract-related AI implementations. The ideal candidate will have a strong background in AI, NLP, and structured prompt engineering, with a keen understanding of legal tech applications. Prior experience in the legal domain is a plus but not mandatory. What you will do: Design, develop, and refine AI prompts for legal tech applications, ensuring accuracy and contextual relevance in contract-related workflows. Work with Large Language Models (LLMs) to enhance AI-driven solutions for contract analysis, review, and automation Optimize prompt structures and techniques to improve AI-generated outputs in contract drafting, compliance, and negotiations Research, test, and implement best practices in prompt engineering to maximize efficiency and accuracy in contract delivery Evaluate and refine AI-generated legal documents to align with compliance standards and client requirements Stay updated with advancements in LLMs, prompt engineering methodologies, and AI-driven legal tech solutions. What you bring: Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field. Minimum 5 years of overall professional experience, with at least 2 years in AI prompt engineering Strong understanding of LLMs (GPT, Claude, Gemini, Llama, etc.) and their application in legal or enterprise use cases Proven expertise in prompt design, optimization, and fine-tuning for AI-driven text generation Hands-on experience with AI tools, frameworks, and APIs (OpenAI, Hugging Face, LangChain, etc.) Strong problem-solving skills and ability to work in a fast-paced environment Excellent communication and collaboration skills to work with cross-functional teams. Bonus Points: Basic understanding of contracts, legal terminology, and compliance standards. Applications must be submitted exclusively through Execo's official job postings located on the following platforms: Execo Careers Website: https://www.execo.com/careers LinkedIn: https://www.linkedin.com/company/execogroup/jobs/ Indeed: US & Kenya: https://www.indeed.com/cmp/Execo-Group-Inc India: https://in.indeed.com/cmp/Execo-Group-Inc UK: https://uk.indeed.com/cmp/Execo-Group-Inc Philippines: https://ph.indeed.com/cmp/Execo-Group-Inc Singapore: https://sg.indeed.com/cmp/Execo-Group-Inc Naukri: https://www.naukri.com/

Design and build production-grade Python APIs, integrate LLMs using LangChain/LangGraph, and develop backend systems. Requires 5+ yrs in backend dev, strong Python, hands-on LLM integration, and experience with async workflows and deployment.

Position Overview: We are seeking highly motivated and innovative AI Agent Development Interns t. You will work with our AI and Oracle Cloud teams to build and prototype AI agents using Large Language Models (LLMs) integrated with Oracle Fusion Applications . This internship is ideal for students who want to work on cutting-edge AI use cases with direct business impact in enterprise environments. Key Responsibilities: Design and build AI agents using LLMs for Oracle Fusion modules: HCM, ERP, SCM, and Risk Management Integrate AI agent flows with Oracle Cloud APIs and datasets Collaborate with Oracle Fusion ERP, SCM, HCM & GRC specialists, data engineers, and cloud developers to refine models and workflows Actively participate in the entire project lifecycle from conceptualization, requirements gathering, and design, through to coding, rigorous testing, iterative refinement, and documentation Document your approach, challenges, and learning outcomes Qualifications: Currently pursuing a Bachelor's or Masters degree in Computer Science, Artificial Intelligence, Data Science, or related fields Strong proficiency in Python, APIs, and LLM frameworks (e.g., OpenAI, LangChain, HuggingFace) Familiarity with Oracle Fusion Cloud or interest in enterprise applications is a strong plus Understanding of prompt engineering, embeddings, and agent orchestration Strong problem-solving skills, curiosity, and eagerness to learn new technologies Preferred Skills: Experience with tools like LangChain, VectorDB, or Retrieval-Augmented Generation (RAG) Familiarity with REST APIs, JSON, and webhooks Exposure to enterprise IT or cloud platforms (OCI, AWS, Azure, etc.) What You Will Gain: Real-world experience building AI applications for enterprise use Exposure to Oracle’s enterprise ecosystem and industry-leading risk solutions Mentorship from cloud, AI, ERP, SCM, HCM and GRC experts Opportunity to present your work in internal demos and client-facing forums Certificate of Completion and potential full-time offer Role & responsibilities