GenAI Adoption - Platform

Tata Consultancy Services; Bengaluru; On-site; INR 3,000,000 - 5,000,000; Full time

Job summary

Tata Consultancy Services in Bengaluru seeks a Platform Engineer with Python and Generative AI expertise to design, build, and scale AI-first platforms and infrastructure. The role focuses on enabling GenAI application development at scale, creating reusable frameworks, and integrating LLM capabilities across enterprise systems using AWS/GCP/OpenAI ecosystems.

You will design multi-tenant, scalable AI platforms, manage IaC with Terraform, and ensure cost, security, and governance across GenAI

Qualifications

• Experience designing and scaling GenAI platforms and frameworks.
• Ability to build reusable components for LLM integrations.
• Proficiency in Python-based backend services and API design.
• Strong understanding of MLOps/LLMOps practices and CI/CD for AI workloads.
• Familiarity with cloud AI services (AWS/GCP) and IaC tooling.

Responsibilities

• Design and build scalable GenAI platforms and frameworks for enterprise use.
• Develop reusable components for LLM integrations and AI tooling.
• Enable internal teams to rapidly build GenAI applications.
• Standardize GenAI usage with templates, SDKs, and APIs.
• Build CI/CD pipelines and observability for AI models and platform services.

Skills

Python

GenAI

MLOps

LLMOps

APIs

Tools

AWS Bedrock

SageMaker

Lambda

Terraform

FastAPI

Flask

Vector databases

Job description

Skill set : Platform Engineer with strong Python and Generative AI expertise to design, build, and scale AI-first platforms and infrastructure

Role descriptions / Expectations from the Role

This role focuses on enabling GenAI application development at scale, building reusable frameworks, and integrating LLM capabilities across enterprise systems using AWS/GCP/OpenAI ecosystems.

GenAI Platform Engineering (Core Focus)

• Design and build scalable GenAI platforms and frameworks for enterprise use
• Develop reusable components for:
• LLM integrations
• Enable internal teams to rapidly build GenAI applications
• Standardize GenAI usage across the organization (templates, SDKs, APIs)

GenAI Application Enablement

• Support development of AI-powered applications such as:
• Chatbots and copilots
• Integrate with:
• Implement:
• Prompt engineering frameworks
• LLM guardrails and evaluation layers

Python Development (Core Skill)

• Build backend services, libraries, and APIs using Python
• Develop platform tooling using:
• FastAPI / Flask
• Create SDKs/microservices for GenAI feature reuse
• Optimize system performance, scalability, and reliability
• Architect and deploy platform services on:
• AWS: Bedrock, Lambda, S3, SageMaker, EKS
• Design multi-tenant, scalable AI platforms
• Manage infrastructure as code (IaC) with Terraform or similar tools
• Monitor usage, cost, and performance of GenAI workloads
• Build and maintain RAG pipelines with vector databases:
• Manage embeddings, indexing, and retrieval systems
• Handle structured and unstructured data pipelines
• Ensure data security and governance in AI workflows

DevOps, MLOps & LLMOps

• Build CI/CD pipelines for platform services and AI models
• Implement LLMOps practices:
• Evaluation pipelines
• Set up observability:
• Logging, tracing, monitoring for AI systems
• Ensure system reliability, scaling, and failover strategies