689 Langchain Jobs - Page 15

Role : Senior Agentic AI Developer Location: Bangalore/Hyderabad Roles & Responsibilities: We are seeking a skilled Agentic AI Developer to design and implement intelligent agent systems powered by Large Language Models (LLMs) . This role involves developing LLM-based pipelines that can ingest transcripts, documents, or business narratives and generate structured artifacts such as workflows, decision trees, action plans, or contextual recommendations. You will collaborate with cross-functional teams to deploy autonomous AI agents capable of reasoning, planning, memory, and tool usage in enterprise environments primarily within the Microsoft ecosystem (Azure, Power Platform, Copilot, and M365 integrations). Key Responsibilities Build and deploy autonomous agent systems using frameworks such as LangChain, AutoGen, CrewAI, or Semantic Kernel. Develop pipelines to process natural language input and generate structured outputs tailored to business needs. Implement agentic features such as task orchestration, memory storage, tool integration , and feedback loops. Fine-tune LLMs or apply prompt engineering to optimize accuracy, explainability, and responsiveness. Integrate agents with Microsoft 365 services (Teams, Outlook, SharePoint) and Power Platform components (Dataverse, Power Automate). Collaborate with business and product teams to define use cases, test scenarios, and performance benchmarks. Participate in scenario-based UAT testing, risk evaluation, and continuous optimization. Must-Have Skills Proficiency in Python and hands-on experience with ML/AI libraries and frameworks (Transformers, PyTorch, LangChain). Strong understanding of LLMs (e.g., GPT, Claude, LLaMA, Mistral) and prompt engineering principles. Experience developing agent workflows using ReAct, AutoGen, CrewAI, or OpenAI function calling . Familiarity with Vector Databases (FAISS, Pinecone, Qdrant) and RAG-based architectures . Skills in Natural Language Processing (NLP) : summarization, entity recognition, intent classification. Integration experience with APIs, SDKs , and enterprise tools (preferably Microsoft stack).

We are hiring a Full Stack Developer with strong exposure to AI tools, APIs, and product development workflows. This role is for someone who can independently design, build, and deploy full-stack applications, and also integrate AI-powered components such as RSVP agents, recommendation systems, conversational flows, and automation tools. Responsibilities Build and maintain full-stack web apps using React, Node.js, Python Integrate AI/ML APIs like OpenAI, Cohere, LangChain, Pinecone, etc. Architect intelligent features using vector databases, RAG pipelines, and custom agent flows Work on both frontend + backend and own deployment, testing & CI/CD Collaborate closely with product & automation teams Must-Have Skills Strong proficiency in JavaScript/TypeScript, Python, Node.js Comfortable with NoSQL, PostgreSQL, Firebase, or Supabase Experience with API integrations, automation, and microservices Understanding of AI agentic flows, embeddings, and webhooks Experience deploying products on Vercel, Render, or similar Good to Have Familiarity with tools like LangChain, LlamaIndex, or OpenAI Assistants Working knowledge of Next.js, Tailwind CSS, and prompt engineering Work Culture Fully remote Flat structure Fast execution environment Product-first mindset

Role & responsibilities Develop and fine-tune LLMs using techniques like RAG, transfer learning, or domain-specific adaptation Build AI agents using frameworks like LangChain or CrewAI to manage dynamic and multi-step workflows Work with vector databases (e.g., Pinecone) to enable semantic search and retrieval Design and maintain ETL pipelines and ensure smooth data preprocessing and transformation Implement NLP solutions for tasks like intent detection, sentiment analysis, and content generation Develop backend APIs and services using Python frameworks like FastAPI or Flask Contribute to scalable microservice-based architectures Requirements Bachelor's degree in Computer Science, Information Technology, or a related field. 2 to 4 years in AI/ML development and backend system Machine Learning Fundamentals: Strong grasp of algorithms, model training, evaluation, and tuning Generative AI Models: Experience working with LLMs, RAG architecture, and fine-tuning techniques LangChain or Similar Frameworks: Hands-on experience building AI workflows using toolkits like LangChain Natural Language Processing (NLP): Proficiency in text analytics, classification, tokenization, embeddings Vector Databases: Practical use of tools like Pinecone, FAISS, or similar for retrieval-augmented generation Big Data Handling: Ability to work with large datasets, optimize storage, and processing pipelines SQL/NoSQL: Experience in querying and managing structured and unstructured data Python & API Development: Proficiency in Python and frameworks like FastAPI or Flask ETL & Data Preprocessing: Strong understanding of building pipelines for clean and efficient data processing Soft Skills: Strong problem-solving, communication, and collaboration abilities

Job Summary: We are seeking a visionary and hands-on AI Architect of experience in designing and deploying AI-driven systems, including Generative AI (GenAI), LLM integration, computer vision, and agentic workflows. This role demands deep technical expertise in transformer models, PyTorch, and tools such as Stable Diffusion, ControlNet, and LangChain, as well as a strong grasp of dataset strategy, bias mitigation, and scalable AI system architecture. Experience with e-commerce or fashion datasets is a strong plus. Key Responsibilities: Architect and lead the development of AI/ML systems, with a focus on Generative AI, including diffusion models, GANs, and LLMs. Implement and optimize models such as Stable Diffusion, ControlNet, and OpenPose for real-world use cases in visual content generation. Design LLM-integrated solutions using LangChain, agentic workflows, and multimodal AI systems. Collaborate with cross-functional teams to define dataset strategy, ensuring data relevance, diversity, and quality. Integrate Hugging Face Transformers and PyTorch-based architectures into production environments. Define and implement best practices around bias & fairness, model explainability, and ethical AI design. Lead architectural decisions for scalable AI platforms, focusing on performance, reliability, and continuous learning capabilities. Leverage domain knowledge in e-commerce/fashion for visual understanding, recommendation, or personalization solutions. Qualifications: Experience in AI/ML system architecture, including 3+ years specifically in Generative AI and LLM ecosystems. Proficiency in PyTorch, Transformers, Hugging Face, and LangChain. Deep understanding of diffusion models, GANs, ControlNet, and OpenPose. Experience in designing agentic AI workflows, real-time inference systems, and production-grade AI infrastructure. Proven track record in dataset creation/curation, bias analysis, and fairness optimization. Strong communication skills and the ability to translate complex AI concepts into business impact. Preferred Qualifications : Contributions to open-source AI frameworks or publications in relevant research areas. Understanding of AI observability, versioning, and model governance.

We will count on you to: Identify opportunities which add value to the business and make the process more efficient. Invest in understand the core business including products, process, documents, and data points with the objective of identifying efficiency and value addition opportunities. Design and develop end-to-end NLP/LLM solutions for document parsing, information extraction, and summarization from PDFs and scanned text. Develop AI applications to automate manual and repetitive tasks using generative AI and machine learning. Fine-tune open-source LLMs (like LLaMA, Mistral, Falcon, or similar) or build custom pipelines using APIs (OpenAI, Anthropic, Azure OpenAI). Build custom extraction logic using tools like LangChain, Haystack, Hugging Face Transformers, and OCR libraries like Tesseract or Azure Form Recognizer. Create pipelines to convert outputs into formatted Microsoft Word or PDF files using libraries like docx, PDFKit, ReportLab, or LaTeX. Collaborate with data engineers and software developers to integrate AI models into production workflows. Ensure model performance, accuracy, scalability, and cost-efficiency across business use cases. Stay updated with the latest advancements in generative AI, LLMs, and NLP research to identify innovative solutions. Design, develop, and maintain robust data pipelines for extracting, transforming, and loading (ETL) data from diverse sources. As the operational scales updesign and implement scalable data storage solutions and integrate them with existing systems. Utilize cloud platforms (AWS, Azure, Google Cloud) for data storage and processing. Conduct code reviews and provide mentorship to junior developers. Stay up-to-date with the latest technology trends and best practices in data engineering and cloud services. Ability to lead initiatives and deliver results by engaging with cross-functional teams and resolving data ambiguity issues. Be responsible for the professional development of your projects and institute a succession plan. What you need to have: Bachelors degree in Engineering, Analytics, or a related field, MBA, Computer Applications, IT, Business Analytics, or any discipline. Proven experience of 8-12 years in Python development Hands-on experience with frameworks and libraries like Transformers, LangChain, PyTorch/TensorFlow, spaCy, Hugging Face, and Haystack. Strong expertise in document parsing, OCR (Tesseract, AWS Textract, Azure Form Recognizer), and entity extraction. Proficiency in Python and familiarity with cloud-based environments (Azure, AWS, GCP). Experience deploying models as APIs/microservices using FastAPI, Flask, or similar. Familiarity with PDF parsing libraries (PDFMiner, PyMuPDF, Apache PDFBox) and Word generation libraries (python-docx, PDFKit). Solid understanding of prompt engineering and prompt-tuning techniques. Proven experience with data automation and building data pipelines. Proven track record in building and maintaining data pipelines and ETL processes. Strong knowledge of Python libraries such as Pandas, NumPy, and PySpark, Camelot. Familiarity with database management systems (SQL and NoSQL databases). Experience in designing and implementing system architecture. Ability to operate in a multi layered technology architecture and shape the technology maturity of the organization. Solid understanding of software development best practices, including version control (Git), code reviews, and testing frameworks (PyTest, UnitTest). Strong attention to detail and ability to work with complex data sets. Effective communication skills to present findings and insights to both technical and non-technical stakeholders. Specify superior listening, verbal and written communication skills Excellent project management and organization skills Superlative stakeholder management skills - ability to positively influence stakeholders. Synthesis skills- Ability to connect the dots and answer the business question. Excellent problem-solving, structuring and critical-thinking skills. Ability to work independently and collaboratively in a fast-paced environment.

Role & responsibilities Must Haves Proven track record of project delivery for 1+ years Good coding (Preferably Python) skills and DSA Good problem solving and communication skills. Good Knowledge of Gen-AI technologies (LLM prompt engineering) Familiarity with React, HTML, CSS, JS or similar frameworks Familiarity with HTTP, REST, microservices, concurrency and Multithreading Willingness to work in a dynamic and fast paced environment. 4-6 years of experience with a Bachelor / Master's Degree in Computer Science or equivalent. Ownership and commitment towards work

At EY, youll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And were counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY-Consulting AI Enabled Automation Developer Staff -Python We are looking to hire people with strong AI Enabled Automation skills and who are interested in learning new technologies in the process automation space Azure . GenAI , large Lang Models(LLM). RAG ,Vector DB , Graph DB ,Python At EY, youll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. And were counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Responsibilities Development and implementation of AI enabled automation solutions, ensuring alignment with business objectives. Design and deploy Proof of Concepts (POCs) and Points of View (POVs) across various industry verticals, demonstrating the potential of AI enabled automation applications. Ensure seamless integration of optimized solutions into the overall product or system Collaborate with cross-functional teams to understand requirements, to integrate solutions into cloud environments (Azure, GCP, AWS, etc.) and ensure it aligns with business goals and user needs Educate team on best practices and keep updated on the latest tech advancements to bring innovative solutions to the project Requirements 2 to 3 years of relevant professional experience Expertise in Python programming including experience with Al/machine learning frameworks like TensorFlow, PyTorch, Keras, Langchain, MLflow, Promtflow(Good to have) 1-2 years of working knowledge of NLP and LLMs like BERT, GPT-3/4, T5, etc. Knowledge of how these models work and how to fine-tune them Expertise in prompt engineering principles and techniques like chain of thought, in-context learning, tree of thought, etc. Knowledge of retrieval augmented generation (RAG) Knowledge of Knowledge Graph RAG Strong analytical and problem-solving skills with the ability to think critically and troubleshoot issues Excellent communication skills, both verbal and written in English What we look for A Team of people with commercial acumen, technical experience and enthusiasm to learn new things in this fast-moving environment An opportunity to be a part of market-leading, multi-disciplinary team of 1400 + professionals, in the only integrated global transaction business worldwide. Opportunities to work with EY Advisory practices globally with leading businesses across a range of industries What working at EY offers At EY, were dedicated to helping our clients, from startups to Fortune 500 companies and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way thats right for you EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.,

About Us: Oraczen is a leader in Generative AI, pioneering cutting-edge AI solutions that enable enterprises to seamlessly integrate artificial intelligence into their operations. Our team thrives on innovation, collaboration, and technical excellence, pushing the boundaries of AI technology. We are committed to revolutionizing automation testing by developing AI-driven testing models that enhance efficiency, reliability, and scalability. Role Overview: We are seeking a visionary Automation Testing Lead who will not only refine and enhance our existing testing frameworks but also develop a new AI-driven model for software testing. The ideal candidate will possess deep expertise in automation testing, Next.js, React, TypeScript, Python, and LangChain, and have a passion for leveraging AI to optimize testing methodologies. You will be at the forefront of innovation, shaping the future of AI-based testing and ensuring the highest quality standards for our cutting-edge products. Key Responsibilities: Develop AI-driven testing models to enhance automation processes and improve the efficiency of software testing Design, implement, and execute automated test scripts for Next.js, React, and TypeScript applications using Jest, Cypress, or Playwright. Create and maintain test frameworks and tools for both frontend and backend testing. Develop automated tests for backend services built with Python and LangChain. Collaborate closely with development teams to understand product requirements and design effective test strategies. Analyze test results, report defects, and work closely with developers to resolve issues efficiently. Lead code reviews, ensuring the testability and quality of code in GitHub CI/CD pipelines. Manage and mentor testing engineers, fostering a culture of best practices and continuous learning. Stay updated on the latest testing tools, frameworks, and industry trends, incorporating them into our testing processes. Ensure bug-free development pipelines through robust automation frameworks and best practices. Qualifications & Skills: Bachelor's degree in computer science, Software Engineering, or a related field. 5+ years of experience in software testing with a focus on automation ( testing experience using AI based applications and designing testing frameworks for AI based applications is mandatory). Strong expertise in Next.js, React, and TypeScript frameworks. Proficiency in JavaScript, TypeScript, and Python programming languages. Hands-on experience with Jest, Cypress, Playwright, or Selenium for frontend testing. Experience with Pytest and other backend testing frameworks. Familiarity with Python, LangChain, and testing AI-driven applications. Deep understanding of software testing methodologies, test design principles, and best practices. Experience managing CI/CD testing workflows using GitHub Actions or other DevOps tools. Strong analytical skills and problem-solving abilities. Excellent communication and collaboration skills, with experience leading teams. Why Join Us Drive the future of AI-based testing and automation. Work in an environment that fosters learning and professional development. Join a team that values teamwork, innovation, and excellence. Flexible work arrangements to support your well-being. Diversity, Equity & Inclusivity: At Oraczen, we believe a focus on diversity, equity, and inclusion (DE&I) is integral to hiring exceptional people and creating an enduring business. To inspire growth, we aspire to create an organization where every person is celebrated, valued, and empowered to achieve their full potential. These beliefs and actions are true to Oraczens philosophy, which is rooted in how we invest, hire, and show up day in and day out. We will continuously look for ways to improve and evolve in our ever-changing world, and we are driven to ensure Oraczen is one of the premier places to work for all by creating diverse teams, strengthening our culture of inclusion, and giving everyone an equitable opportunity to succeed. ,

Job Title: Senior Gen AI Engineer GenAI / ML (Python, Langchain) Experience Required: 7–12 Years Role Overview We are seeking a highly experienced Senior Gen AI Engineer to join our engineering team focused on designing, developing, and deploying cutting-edge Generative AI and Large Language Model (LLM) based solutions. This is a hands-on role requiring deep technical expertise in Python, modern AI frameworks, and system-level thinking to translate complex business requirements into scalable and production-ready AI applications. You will play a pivotal role in shaping the GenAI strategy and delivering high-impact solutions for real-world enterprise use cases. Key Responsibilities GenAI System Design & Development: Build intelligent, context-aware systems using frameworks like Langchain and Retrieval-Augmented Generation (RAG). Prompt Engineering & Agent Workflows: Apply advanced prompt engineering and develop agent-based architectures for dynamic user interaction and reasoning. Technical Roadmapping: Collaborate with engineering leadership to define and implement the technical roadmap for GenAI and LLM initiatives. Solution Delivery: Translate business and functional requirements into scalable, robust, and maintainable AI/ML solutions. Cross-Team Collaboration: Work closely with business SMEs, product teams, and data engineers to align model outputs with domain-specific goals. Code & Architecture Excellence: Participate in system design, code reviews, and performance optimization of deployed solutions. Required Skills Proficient in Python, Langchain, and SQL. Deep understanding of LLM internals, including: Prompt tuning Embeddings Vector databases (e.g., FAISS, Pinecone) EMB Global | www.emb.global Agent workflows Strong foundation in Machine Learning or Software Engineering, especially in system design and architecture. Experience working on cloud platforms: AWS, Azure, or GCP. Ability to work autonomously and deliver in cross-functional environments. Strong communication skills, including experience with stakeholder engagement and technical documentation. Preferred Qualifications 1+ years of hands-on experience in LLMs and Generative AI technologies. Demonstrated experience contributing to or leading ML/AI product pipelines and end-to-end deployments. Familiarity with MLOps, CI/CD for ML, and model monitoring in production. Previous exposure to client-facing projects or collaborative work with business units and AI teams.

Role Title: Senior LLM Engineer Generative AI Years of Experience: 5 – 9 Years Role Overview Client is seeking experienced Senior LLM Engineers to join its GenAI Delivery Organization, working on strategic AI initiatives for Fortune 500 clients. As part of this team, you will contribute to the development of cutting-edge AI systems, including multi-agent LLM solutions, Retrieval-Augmented Generation (RAG) pipelines, and open-source LLM deployments. This is a highly technical, hands-on role that demands deep expertise in machine learning, Python development, and modern LLM frameworks such as LangChain and LangGraph. Key Responsibilities LLM Development: Design, train, fine-tune, and deploy LLM-based systems using prompt engineering, RAG techniques, and agent-based architectures. Codebase Ownership: Write and maintain high-quality, efficient, and scalable Python and SQL code using frameworks like LangChain and LangGraph. Cloud Deployment: Assist in the deployment and optimization of GenAI solutions across Azure, GCP, or AWS, ensuring cost-effective and high-performance infrastructure. Cross-functional Collaboration: Work closely with product managers, data scientists, and business SMEs to translate functional requirements into scalable AI solutions. Team Leadership & Mentorship: Provide technical guidance and mentorship to engineering peers, encouraging best practices and knowledge sharing. Innovation: Continuously stay updated on advancements in LLMs and Generative AI, evaluating new techniques and incorporating them into project workstreams. Required Skills 5+ years of professional experience in building machine learning models and systems. 1+ years of hands-on experience specifically in LLMs and Generative AI, with expertise in: Prompt Engineering Retrieval-Augmented Generation (RAG) Agent-based LLM systems

Role Title: Senior LLM Engineer GenAI / ML (Python, Langchain) Role Overview We are seeking highly skilled and experienced Senior LLM Engineers with a strong background in Machine Learning and Software Engineering who have transitioned into Generative AI (GenAI) and Large Language Models (LLMs) over the past 34 years. This is a hands-on engineering role focused on designing, building, and deploying GenAI-based systems using state-of-the-art frameworks and tools. The role involves active participation in architectural design, model fine-tuning, and cross-functional collaboration with business stakeholders, data teams, and engineering leaders to deliver enterprise-grade GenAI solutions. Key Responsibilities GenAI System Design: Architect and develop GenAI/LLM-based systems using frameworks like LangChain and Retrieval-Augmented Generation (RAG) pipelines. Prompt Engineering & Agent Design: Implement advanced prompt engineering strategies and agent-based workflows to build intelligent, context-aware AI systems. Technical Roadmapping: Collaborate with product and engineering stakeholders to define and drive the technical roadmap for LLM and GenAI initiatives. AI Solution Delivery: Translate complex business requirements into scalable, production-ready AI solutions. Cross-functional Collaboration: Work closely with business SMEs, product owners, and data engineering teams to align AI models with real-world use cases. System Optimization: Contribute to code reviews, system architecture discussions, and performance tuning of deployed models. Required Skills 7–12 years of total experience in ML/Software Engineering, with 3–4 years of recent experience in LLMs and Generative AI. Strong proficiency in Python, LangChain, and SQL. Deep understanding of LLM concepts including: Prompt tuning Embeddings Vector databases (e.g., FAISS, Pinecone) Agent frameworks Experience working with cloud platforms such as AWS, Azure, or GCP. Solid understanding of ML pipelines, deployment strategies, and GenAI use cases. Ability to work independently and collaboratively in fast-paced, cross-functional environments. Strong verbal and written communication skills; ability to engage effectively with technical and non-technical stakeholders. Preferred Qualifications Minimum 1+ years of hands-on experience specifically in LLM/GenAI-focused implementations. Experience delivering ML/AI products from prototyping through to production. Familiarity with MLOps, CI/CD, containerization, and scalable AI model deployment. Prior involvement in client-facing projects orRole & responsibilities cross-functional teams building production-ready AI systems.

We're hiring a Remote AI Engineer (2+ yrs exp)! Work on GPT, LangChain, Whisper, Flask/FastAPI, and ASR. Strong Python skills required. Exciting AI projects & full remote flexibility. Apply now!

We're hiring a passionate Data Scientist / GenAI Engineer to join our AI-first team working on LLMs, RAG pipelines, NLP features, and GenAI use cases like chatbots, recommendation engines, and smart automation.

Greetings !!! Hiring GEN AI Engineers for Hyderabad Location. Skills Required - GEN AI , Python, Lang chain Experience - 3 to 5 years Location - Hyderabad Interested one can share resumes to anmol.bhatia@incedoinc.com

We are seeking a skilled Generative AI Engineer with a strong background in Python to join our dynamic team. In this role, you will integrate backend development expertise with the latest advancements in AI to create impactful solutions. If you excel in a fast-paced environment and enjoy tackling complex challenges, we encourage you to apply. Key Responsibilities: Generative AI Development Develop and implement generative AI models using frameworks like LangChain or Llama-Index. Apply prompt engineering techniques to design effective queries and ensure optimal LLM responses for diverse use cases. Master advanced LLM functionalities, including prompt optimization, hyperparameter tuning, and response caching. Implement Retrieval-Augmented Generation (RAG) workflows by integrating vector databases like Pinecone, Weaviate, Supabase, or PGVector for efficient similarity searches. Work with embeddings and build solutions that leverage similarity search for personalized query resolution. Explore and process multimodal data, including image and video understanding and generation. Integrate observability tools for monitoring and evaluating LLM performance to ensure system reliability. Backend Engineering, Build and maintain scalable backend systems using Python frameworks such as FastAPI, Django, or Flask. Design and implement RESTful APIs for seamless communication between systems and services. Optimize database performance with relational databases (PostgreSQL, MySQL) and integrate vector databases (Pinecone, PGVector, Weaviate, Supabase) for advanced AI workflows. Implement asynchronous programming and adhere to clean code principles formal maintainable, high-quality code. Seamlessly integrate third-party SDKs and APIs, ensuring robust interoperability with external systems. Develop backend pipelines for handling multimodal data processing, and supporting text, image, and video workflows. Manage and schedule background tasks with tools like Celery, cron jobs, or equivalent job queuing systems. Leverage containerization tools such as Docker for efficient and reproducible deployments. Ensure security and scalability of backend systems with adherence to industry best practices.

Immediate to 30days NP Hybrid Mode - 3 days WFO Payments Domain is Mandatory Baner , Pune JD : TP3 Developer Generative AI (7 Years Experience | 12 Years in GenAI) Key Responsibilities: GenAI Application Development: Contribute to the design and development of AI-powered applications leveraging Generative AI models such as LLMs. Assist in integrating these models into real-world business workflows. (1–2 years experience in GenAI-related projects preferred). Prompt Engineering & RAG Pipelines: Support the creation and refinement of prompts and Retrieval-Augmented Generation (RAG) pipelines using tools like LangChain. Implement prompt chaining and retrieval flows under guidance. (1+ years of hands-on exposure ideal). Vector Database Integration: Implement and maintain vector store solutions for semantic search and knowledge retrieval. (1 year experience working with vector DBs preferred). AI Workflow Implementation: Build intelligent agents and multi-step automation pipelines using LLM APIs , chaining tools, and orchestration frameworks. Integrate with back-end systems using Java Spring Boot or Python FastAPI . (1+ years of experience with LLM-based workflows is a plus). Backend & Microservices: Develop robust backend services and REST APIs using Java (Spring Boot) and Python . Collaborate on system architecture, microservices design, and business logic development. (5+ years of backend development experience required, including 2–3 years in microservices/API work). CI/CD & Deployment: 2+ years of experience with DevOps tools like Docker, GitHub Actions, Jenkins, etc Database Support: Work with NoSQL databases (PostgreSQL) to support GenAI pipelines. (3+ years of experience in working with databases). Collaboration & Learning: Work under the guidance of senior engineers and AI architects. Proactively engage in learning new GenAI concepts and contribute to team discussions. (5–7 years total professional experience, with a strong learning and collaborative mindset). Required Qualifications: Technical Skills: Python: Strong programming skills with 5 + years of experience. Java (Spring Boot) – 3+ years of backend/API experience. GenAI Tools: 1–2 years of hands-on experience with Generative AI tools, including OpenAI APIs, Hugging Face Transformers, or similar libraries. LangChain or Equivalent: Exposure to LangChain or similar GenAI workflow tools for 1+ years . Vector Databases: Experience with Chroma, Pinecone, or Weaviate for 1+ years . Backend & Data: APIs & Microservices: At least 3+ years of experience in building backend services and REST APIs. Database Systems: Experience working with both SQL and NoSQL systems for 3–5 years . DevOps & Cloud: Exposure to Docker, CI/CD tools, and at least one cloud platform (AWS/GCP/Azure) for 2–3 years . Regards, Soniya S

* If you are 5+ years experienced and Immediate joiner , please apply: https://forms.gle/9n6GFcewkBo9VBNF8 5+ years of experience as a backend or full-stack engineer with a strong backend focus Advanced proficiency in Python Practical experience integrating LLMs (e.g., RAG pipelines, agent frameworks, LangChain, LangGraph, or similar) Background in machine learning engineering is a strong plus Solid understanding of service architecture and production deployment workflows Hands-on LLM integration in production (not academic/chatbot-only experience) Expertise in designing production-grade APIs and backend services Strong knowledge of async workflows, deployment, observability, and performance *This is a software engineering role (not data science, analytics, or annotation)* Description: A complete remote role, you can use your own laptop. 8hrs/day, Mon-Fri required Eligibility: Candidates with 5+ years of relevant professional experience are eligible to apply.Must possess strong communication skills , both written and verbal.Should have proven expertise in the specific field or role being applied for. Timings: 8 hrs/day, Mon-Fri Preferred candidate profile : Immediate Joiners Fully remote, 3 months contract in the starting

Key Responsibilities: Design and develop intelligent automation workflows integrated with LLM capabilities (e.g., summarization, classification, Q&A) Integrate LLM APIs such as OpenAI, Azure OpenAI , and Google Gemini into UiPath using REST APIs or native connectors Automate document processing leveraging UiPath tools like Document Understanding and AI Center Participate in code reviews, documentation, and development of reusable components for scalable AI/automation solutions Stay current on LLM innovations, tools, and frameworks, and actively contribute to POCs and hands-on experimentation Required Skills & Qualifications: Bachelor's degree in Computer Science , Engineering , Information Technology , or a related field 35 years of experience in automation development , preferably with UiPath Foundational knowledge of LLMs and prompt engineering , with hands-on application in automation Experience integrating with platforms like OpenAI , Azure AI , or Google Cloud AI via APIs Proficiency in Python and ability to embed Python scripts into RPA workflows Exposure to LangChain or a willingness to learn LLM orchestration frameworks Familiarity with unstructured data processing and document understanding concepts Strong communication, collaboration, and continuous learning mindset

Role & responsibilities Experience: 0-1 year Location - Bengaluru Mode of work - Work from office Mode of interview - Face to Face We are looking for a highly motivated and passionate AI/ML Engineer with a strong foundation in machine learning and hands-on project experience in Generative AI. As an early-career team member, you will work on cutting-edge technologies involving Large Language Models (LLMs), Agentic AI, and toolkits like Lang Chain, Lang Graph, and Phi Data. This role is ideal for someone who has recently completed academic or personal projects and is eager to apply their knowledge to real-world use cases. Key Responsibilities Build, experiment with, and fine-tune Generative AI models using popular LLMs (e.g., OpenAI, LLaMA, Mistral, etc.). Develop agent-based workflows using tools such as LangChain, LangGraph, and PhiData. Create interactive and dynamic AI pipelines for tasks like summarization, Q&A, sentiment analysis, and more. Collaborate with the AI/ML team to design and deploy prototypes and PoCs. Write clean, modular Python code and maintain version control via Git/GitHub. Document projects clearly and effectively for internal and external stakeholders. Required Skills Solid understanding of Machine Learning, Deep Learning fundamentals, and model evaluation. Experience with Generative AI projects (transformers, text generation, prompt engineering, etc.). Familiarity with frameworks like LangChain, LangGraph, PhiData. Proficient in Python, along with common ML libraries (e.g., PyTorch, Hugging Face Transformers, scikit-learn). Good understanding of LLM APIs (OpenAI, Anthropic, Cohere, etc.). Strong problem-solving ability and communication skills. Active GitHub profile showcasing relevant projects is mandatory Good to Have Knowledge of REST APIs, basic backend frameworks like Flask or FastAPI. Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate). Basic understanding of RAG (Retrieval-Augmented Generation) pipelines. Knowledge of prompt chaining and tool-calling via LLM agents. Knowledge on web application development

Job Summary: We are seeking a visionary and hands-on AI Architect with 8+ years of experience in designing and deploying AI-driven systems, including Generative AI (GenAI), LLM integration, computer vision, and agentic workflows. This role demands deep technical expertise in transformer models, PyTorch, and tools such as Stable Diffusion, ControlNet, and LangChain, as well as a strong grasp of dataset strategy, bias mitigation, and scalable AI system architecture. Experience with e-commerce or fashion datasets is a strong plus. Key Responsibilities: Architect and lead the development of AI/ML systems, with a focus on Generative AI, including diffusion models, GANs, and LLMs. Implement and optimize models such as Stable Diffusion, ControlNet, and OpenPose for real-world use cases in visual content generation. Design LLM-integrated solutions using LangChain, agentic workflows, and multimodal AI systems. Collaborate with cross-functional teams to define dataset strategy, ensuring data relevance, diversity, and quality. Integrate Hugging Face Transformers and PyTorch-based architectures into production environments. Define and implement best practices around bias & fairness, model explainability, and ethical AI design. Lead architectural decisions for scalable AI platforms, focusing on performance, reliability, and continuous learning capabilities. Leverage domain knowledge in e-commerce/fashion for visual understanding, recommendation, or personalization solutions. Qualifications: 8+ years of experience in AI/ML system architecture, including 3+ years specifically in Generative AI and LLM ecosystems. Proficiency in PyTorch, Transformers, Hugging Face, and LangChain. Deep understanding of diffusion models, GANs, ControlNet, and OpenPose. Experience in designing agentic AI workflows, real-time inference systems, and production-grade AI infrastructure. Proven track record in dataset creation/curation, bias analysis, and fairness optimization. Strong communication skills and the ability to translate complex AI concepts into business impact. Preferred Qualifications : Prior experience with e-commerce, fashion technology, or retail-based AI datasets. Contributions to open-source AI frameworks or publications in relevant research areas. Familiarity with cloud AI services (e.g., AWS Sagemaker, Azure AI, or GCP Vertex AI). Understanding of AI observability, versioning, and model governance. Location - Pan India, Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune.

Greetings !!! We have Walkin Drive in Hyderabad on 12th July for GEN AI Developers Skills Required - GEN AI , Python , Lang chain Experience - 3 to 5 years Interested candidates can share resumes to anmol.bhatia@incedoinc.com

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

Senior Manager - Senior Data Scientist (NLP & Generative AI) Location: PAN India / Remote Employment Type: Full-time About the Role We are seeking a highly experienced Senior data scientist with 8+ years of expertise in machine learning, focusing on NLP, Generative AI, and advanced LLM ecosystems. This role demands leadership in designing and deploying scalable AI systems leveraging the latest advancements such as Google ADK, Agent Engine, and Gemini LLM. You will spearhead building real-time inference pipelines and agentic AI solutions that power complex, multi-user applications with cutting-edge technology. Key Responsibilities Lead the architecture, development, and deployment of scalable machine learning and AI systems centered on real-time LLM inference for concurrent users. Design, implement, and manage agentic AI frameworks leveraging Google Adk, Langgraph or custom-built agents. Integrate foundation models (GPT, LLaMA, Claude, Gemini) and fine-tune them for domain-specific intelligent applications. Build robust MLOps pipelines for end-to-end lifecycle management of models-training, testing, deployment, and monitoring. Collaborate with DevOps teams to deploy scalable serving infrastructures using containerization (Docker), orchestration (Kubernetes), and cloud platforms. Drive innovation by adopting new AI capabilities and tools, such as Google Gemini, to enhance AI model performance and interaction quality. Partner cross-functionally to understand traffic patterns and design AI systems that handle real-world scale and complexity. Required Skills & Qualifications Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or related fields. 7+ years in ML engineering, applied AI, or senior data scientist roles. Strong programming expertise in Python and frameworks including PyTorch, TensorFlow, Hugging Face Transformers. Deep experience with NLP, Transformer models, and generative AI techniques. Practical knowledge of LLM inference scaling with tools like vLLM, Groq, Triton Inference Server, and Google ADK. Hands-on experience deploying AI models to concurrent users with high throughput and low latency. Skilled in cloud environments (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes). Familiarity with vector databases (FAISS, Pinecone, Weaviate) and retrieval-augmented generation (RAG). Experience with agentic AI using Adk, LangChain, Langgraph and Agent Engine Preferred Qualifications Experience with Google Gemini and other advanced LLM innovations. Contributions to open-source AI/ML projects or participation in applied AI research. Knowledge of hardware acceleration and GPU/TPU-based inference optimization. Exposure to event-driven architectures or streaming pipelines (Kafka, Redis).

Key Responsibilities: Generative AI Systems Design : Architect scalable, high-performance applications powered by Generative AI models (e.g., LLMs, diffusion models), with a focus on real-world usability and business integration. Prompt Engineering & RAG Pipelines : Design and implement optimized prompt strategies and Retrieval-Augmented Generation (RAG) workflows using LangChain and similar frameworks. Agentic AI & Autonomous Workflows : Develop and manage intelligent agents capable of multi-step reasoning, planning, and decision-making using frameworks like LangChain Agents or custom implementations. Vector Store Integration : Design and integrate vector databases for semantic search and document retrieval in GenAI workflows. End-to-End AI Application Development : Build and deploy AI-driven applications from scratch using Python and modern ML/AI toolkits. Ensure clean integration with APIs, databases, and frontend services. Microservices & API Development : Create modular, maintainable backend services using microservices architecture. Ensure RESTful APIs for smooth communication. CI/CD & DevOps : Develop and maintain CI/CD pipelines for model and app deployment. Ensure reproducibility, automated testing, and smooth rollout using tools like GitHub Actions, GitLab CI/CD, or Jenkins. Database Management : Use PostgreSQL and NoSQL databases effectively in storing structured and unstructured data, with focus on performance, indexing, and scaling. Performance Optimization : Continuously monitor, benchmark, and optimize applications for performance, scalability, and cost-efficiency across cloud and on-prem environments. Collaboration & Mentorship : Work closely with product managers, AI researchers, and junior developers. Lead by example and provide technical mentorship in AI system design and production-readiness. Required Qualifications: Technical Expertise : Strong proficiency in Python (mandatory) and experience with AI/ML libraries like FastAI , Hugging Face Transformers, and OpenAI APIs. Experience implementing LangChain workflows, prompt chaining, agents, tools, and memory systems. Hands-on experience building RAG systems using vector DBs like FAISS, Pinecone, Weaviate , or Chroma . Solid understanding of Generative AI technologies (LLMs, image/video generation, embeddings). Working knowledge of Agentic AI concepts for building autonomous tools and applications. Backend & Architecture : Strong skills in system design , API development, and microservices-based backend architecture. Experience with PostgreSQL and NoSQL databases (e.g., MongoDB, DynamoDB). Cloud & DevOps : Familiarity with CI/CD pipelines , containerization (Docker), and cloud deployments (AWS/GCP/Azure). Git-based version control and collaborative development workflows. Communication & Leadership : Ability to translate AI research into production-ready applications. Strong collaboration skills and experience leading engineering efforts or mentoring peers. Preferred (Nice to Have): Experience working with LLMOps tools Exposure to data labeling, fine-tuning , or custom LLM training . Familiarity with streaming architectures or real-time AI inference . Location- Pune, Baner Client Office Work Mode- Hybrid ( 3 days a week) Payments Domain is Mandatory

MNC Hiring for Data Engineer, Skils :python, Langchain,SQL, Genai 3+ years Budget: 15 LPA Immediate joiners to 15 days call:6362078823