T&T | Cyber: D&R | Consultant | Generative AI | Bengaluru

Key Responsibilities :

We are seeking an experienced Agentic AI Developer with strong hands-on experience in Generative AI and agent-based systems. The ideal candidate will design, build, and deploy intelligent agent workflows using modern LLMs, RAG architectures, and Azure AI foundation services to solve complex business problems at scale.

Candidate should be excellent in client / stakeholder communication and comfortable to develop AI agents and developing Agentic AI solutions including reasoning, planning and deployment of models on at least one cloud and Azure is the preferred.

And candidate should also have experience of production deployment of RAG pipelines and custom AI agents.

GenAI based development

·      4-6 years. Strong understanding of Generative AI and Large Language Models (LLMs).

·      Hands-on experience with Agentic AI frameworks (e.g., CrewAI, LangChain Agents, AutoGen, Semantic Kernel).

·      Should have knowledge of apply AI model safety, security and required guardrails.

·      Solid knowledge of RAG architectures, chunking strategies, and retrieval techniques.

·      Experience with text embeddings (OpenAI, Azure OpenAI, sentence transformers).

·      Expertise in prompt engineering (few-shot, chain-of-thought, structured outputs).

·      Practical experience in model fine-tuning and evaluation.

Data & Document Processing / Embeddings

• Build pipelines for document ingestion, parsing, chunking, and embeddings generation using frameworks like LangChain, Haystack, or custom solutions.
• Implement vector database solutions (e.g. Pinecone, FAISS, Azure Cognitive Search) to enable efficient semantic search and RAG implementations.

RAG Pipelines Development

• Design and develop Retrieval-Augmented Generation (RAG) architectures combining embeddings-based retrieval with LLM-based generation for accurate and context-rich responses.
• Optimize retrieval strategies for performance, relevance, and cost-effectiveness.

Prompt Engineering & Prompt Flows

• Develop and optimize prompts, chains, and prompt flows for diverse use cases to maximize LLM output accuracy and relevance.
• Test prompt templates systematically and maintain prompt repositories with versioning and evaluation metrics.

AI-Ops, Fine-tuning & Model Development

• Implement AI-Ops practices for managing LLM workloads, including monitoring, logging, and automated retraining where applicable.
• Fine-tune open-source or proprietary LLMs on domain-specific datasets to improve performance for targeted tasks.
• Integrate external data sources with model pipelines to build dynamic and responsive AI solutions.

Model Versioning & Evaluations

• Manage model versioning using MLflow, SageMaker Model Registry, or Azure ML for reproducibility and controlled deployments.
• Perform comprehensive model evaluation, including prompt output evaluations, accuracy, relevance scoring, and user feedback analysis.
• Generate evaluation and accuracy reports for technical and business stakeholders.

Collaboration & Documentation

• Work closely with data scientists, software engineers, and business analysts to deliver robust Gen-AI solutions.
• Document architectures, data flows, prompts, and evaluation methodologies clearly for knowledge sharing and compliance.

Required Skills and Experience:

Generative AI & LLMs

·      Strong experience with LLMs such as OpenAI GPT, Azure OpenAI, or open-source models like LLaMA, Mistral, Falcon, etc.

·      Knowledge of RAG architectures and vector search solutions for building context-aware applications.

Embeddings & Vector Databases

·      Practical experience in generating and managing embeddings for text/document data.

·      Hands-on with vector stores such as Pinecone, FAISS, Milvus, or Azure AI Search.

Prompt Engineering

·      Expertise in designing and optimizing prompts, chains, and prompt flows to achieve task objectives efficiently.

AI-Ops & MLOps

·      Implementing model versioning, deployment pipelines, monitoring, and automated retraining.

·      Familiarity with CI/CD for AI models, Kubernetes deployments, and containerization.

Programming & Frameworks

·      Strong programming skills in Python with libraries/ frameworks such as LangChain, Lang Graph,Transformers, SentenceTransformers, PyTorch, or TensorFlow.

·      Experience integrating Gen-AI solutions into web apps, chatbots, or enterprise workflows.

Model Evaluation & Reporting

·      Building evaluation pipelines for prompt outputs and model responses, including quantitative and qualitative metrics.

General Skills

·      Excellent problem-solving and analytical skills.

·      Strong communication and documentation abilities to explain complex Gen-AI solutions clearly.

Education:

B.Tech/BE / B.Sc / BCA/ full time graduation / Master’s degree in Computer Science, Engineering- Full time

Location and way of working

• Base location: Bangalore
• Professional is required to work from office.