Generative AI Engineer / Developer

Greetings from TCS!

Hiring: Generative AI Engineer / Developer

Role: Engineer / Developer

Primary Skill: Generative AI

Experience: 8–10 years

Location: Bangalore

Educational Qualification: Bachelor’s degree or above

Role Overview

We are looking for an experienced Generative AI Engineer/Developer to design, develop, and productionize AI-powered applications using Large Language Models (LLMs) and modern Generative AI frameworks.

The ideal candidate should have strong software engineering foundations along with hands-on experience building enterprise-grade GenAI, RAG, prompt engineering, and LLM-based solutions .

Mandatory Skills

• Strong programming experience in Python .
• Hands-on experience building Generative AI and LLM-based applications .
• Strong understanding of Large Language Models (LLMs) and Transformer-based architectures.
• Hands-on experience with RAG (Retrieval-Augmented Generation) .
• Experience with prompt engineering and prompt optimization techniques.
• Experience with GenAI frameworks such as LangChain or LlamaIndex .
• Experience working with vector databases/vector search , such as FAISS, Pinecone, Chroma, Azure AI Search, or equivalent.
• Knowledge of embeddings, semantic search, chunking, retrieval, and reranking techniques.
• Experience integrating LLMs through APIs and REST services .
• Strong understanding of AI/ML fundamentals , model evaluation, and data preprocessing.
• Experience developing scalable, production-grade applications using sound software engineering practices.
• Familiarity with Git, CI/CD, testing, debugging, and deployment practices.

Key Responsibilities

• Design and develop enterprise-grade Generative AI applications .
• Build GenAI solutions leveraging LLMs, RAG, embeddings, and vector search .
• Develop and optimize prompts for different business use cases.
• Design document ingestion, chunking, indexing, retrieval, and reranking pipelines.
• Integrate LLM capabilities into existing applications and APIs.
• Evaluate LLM responses for accuracy, relevance, groundedness, and hallucination risk .
• Implement guardrails and appropriate security controls for enterprise GenAI applications.
• Optimize GenAI applications for latency, scalability, reliability, and cost .
• Develop reusable AI components, APIs, and services.
• Collaborate with data engineers, ML engineers, architects, and application teams to productionize GenAI solutions.
• Follow coding standards, version control, testing, and CI/CD practices.

Good to Have

• Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, or similar enterprise AI platforms .
• Knowledge of fine-tuning, LoRA/PEFT , and model adaptation techniques.
• Exposure to MLOps/LLMOps practices.
• Experience with Docker and Kubernetes.
• Understanding of responsible AI, LLM security, monitoring, and governance.
• Experience with agentic AI or multi-agent workflows.