Generative AI Engineer

Tata Consultancy Services Limited; Bengaluru; Sur place; INR 1 800 000 - 3 000 000; Plein temps

Résumé du poste

Tata Consultancy Services Limited is seeking an experienced AI engineer in Bengaluru to build scalable AI-powered applications. Focus areas include Python-based backend, REST APIs, microservices, and cloud-native deployments with AWS Bedrock, SageMaker, and secure data handling.

The role emphasizes agentic AI workflows, memory and planning components, prompt engineering, and integration with enterprise tools. Collaboration across teams and Agile practices are expected.

Qualifications

• Strong hands-on Python development experience covering object-oriented programming, reusable modules, exception handling, logging, unit testing, performance optimization and secure coding.
• Production experience developing REST APIs and microservices using FastAPI, Flask or Django.
• Hands-on Generative AI development using prompt engineering, model integration, embeddings, vector search and Retrieval-Augmented Generation (RAG).
• Experience integrating Large Language Models through managed platforms or APIs, preferably Amazon Bedrock or approved enterprise model services.
• Practical Agentic AI knowledge, including tool/function calling, workflows, memory, planning, orchestration, guardrails and human‑in‑the‑loop controls.
• Working knowledge of AWS services such as Lambda, API Gateway, S3, ECS/EKS, Bedrock, SageMaker, DynamoDB/RDS, CloudWatch, IAM, Secrets Manager, Step Functions and SQS/SNS.
• Experience with relational or NoSQL databases, Git, CI/CD, Docker and deployment automation.
• Understanding of API security, IAM, encryption, secrets management, privacy, responsible AI and secure enterprise‑data handling.
• Strong debugging and analytical skills across applications, cloud integrations, databases and model responses.

Responsabilités

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Connaissances

Python

REST APIs

Microservices

FastAPI

Flask

Django

Generative AI

Prompt engineering

Model integration

Embeddings

Vector search

RAG

LangChain

LangGraph

LlamaIndex

OpenSearch

Vector stores

GenAI evaluation

MLOps

CI/CD

Docker

AWS

SageMaker

Security

Outils

Git

CI/CD

Docker

Description du poste

SN

Required Information

Details

Role

Primary Skills

Secondary Skills

UI Development; Web-Based Application Development; Agentic AI Knowledge

Location

Detailed Skill and Role Requirements

Must Have Technical / Functional Skills

• Strong hands‑on Python development experience covering object‑oriented programming, reusable modules, exception handling, logging, unit testing, performance optimization and secure coding.
• Production experience developing REST APIs and microservices using FastAPI, Flask or Django.
• Hands‑on Generative AI development using prompt engineering, model integration, embeddings, vector search and Retrieval‑Augmented Generation (RAG).
• Experience integrating Large Language Models through managed platforms or APIs, preferably Amazon Bedrock or approved enterprise model services.
• Practical Agentic AI knowledge, including tool/function calling, workflows, memory, planning, orchestration, guardrails and human‑in‑the‑loop controls.
• Working knowledge of AWS services such as Lambda, API Gateway, S3, ECS/EKS, Bedrock, SageMaker, DynamoDB/RDS, CloudWatch, IAM, Secrets Manager, Step Functions and SQS/SNS.
• Experience with relational or NoSQL databases, Git, CI/CD, Docker and deployment automation.
• Understanding of API security, IAM, encryption, secrets management, privacy, responsible AI and secure enterprise‑data handling.
• Strong debugging and analytical skills across applications, cloud integrations, databases and model responses.

Secondary / Good‑to‑Have Skills

• Web‑based application development and front‑end integration with APIs and AI services.
• Knowledge of LangChain, LangGraph, LlamaIndex or equivalent orchestration frameworks.
• Exposure to OpenSearch, pgvector, Pinecone, Weaviate, FAISS or another vector‑search solution.
• Knowledge of GenAI evaluation covering relevance, groundedness, hallucination control, safety, latency and cost.
• Exposure to observability, MLOps/LLMOps and automated testing of AI‑enabled applications.
• Design, develop, test and maintain scalable Python applications, APIs and cloud‑native services.
• Build GenAI solutions using approved models, RAG patterns, prompt templates, embeddings and vector stores.
• Develop agentic workflows connecting models with approved tools, APIs, data sources and business processes.
• Implement safeguards for confidential data, access control, prompt injection, output validation, auditability and responsible AI.
• Deploy and operate AWS workloads with appropriate security, resiliency, monitoring, logging and cost controls.
• Create reusable components and integrations for web‑based and AI‑enabled applications.
• Write unit, integration and functional tests; perform code reviews and maintain technical documentation.
• Troubleshoot incidents, identify root causes and implement preventive improvements.
• Collaborate with architects, product owners, UI developers, DevOps, data teams and business stakeholders.
• Participate in Agile planning, estimation, stand‑ups, demos, retrospectives and releases.
• For the 8+ year position, lead solution design, review complex implementations and mentor developers.