AI Platform Engineer

Capgemini; Hyderabad, Pune District, Bengaluru; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Capgemini is seeking an AI Platform Engineer to design and scale AI infrastructure powering core AI products for the Banking, Insurance and Financial Services sectors. You will craft scalable GenAI frameworks, agent orchestration, model serving, and evaluation systems on cloud-native platforms.

Responsibilities cover building gateways, agent runtimes, RAG architectures, tool integrations, CI/CD deployments, and governance with emphasis on reliability and observability across multi-tenant SaaS

Responsibilities

• Design scalable GenAI and Agentic AI platforms.
• Build model gateways for routing, failover, cost optimization, and monitoring.
• Develop AI agent runtimes using LangGraph, LangChain, or similar frameworks.
• Implement RAG architectures and evaluation frameworks.
• Build and manage AI agents, tool calling, workflows, and orchestration pipelines.
• Integrate Model Context Protocol and external tools/connectors.
• Design reusable frameworks for multiple AI use cases.
• Develop AI evaluation frameworks and automated testing pipelines.
• Implement AI guardrails for safety, compliance, and governance.
• Monitor model performance, latency, and reliability.
• Deploy cloud-native apps on Kubernetes.
• Develop microservices and APIs using Python and Go.
• Automate deployments via CI/CD pipelines.
• Ensure high availability and observability.
• Build pipelines for fine-tuning and post-training of LLMs/SLMs.
• Work on reinforcement learning and synthetic data generation.
• Support deployment and serving of custom AI models.

Job description

We are looking for a highly skilled AI Platform Engineer to build and scale the core platform powering AI products for Banking, Insurance, and Financial Services. You will design and develop AI infrastructure, agent orchestration frameworks, model serving platforms, evaluation systems, and cloud-native services that support multiple product teams.

Key Responsibilities

• Design and develop scalable GenAI and Agentic AI platforms.
• Build model gateways for routing, failover, cost optimization, and monitoring.
• Develop AI agent runtimes using LangGraph, LangChain, or similar frameworks.
• Implement RAG (Retrieval Augmented Generation) architectures.
• Build and manage AI agents, tool calling, workflows, and orchestration pipelines.
• Integrate MCP (Model Context Protocol) and external tools/connectors.
• Design reusable frameworks supporting multiple AI use cases.
• Develop AI evaluation frameworks and automated testing pipelines.
• Implement AI guardrails for safety, compliance, and governance.
• Monitor model performance, quality, latency, and reliability.
• Build and deploy cloud-native applications on Kubernetes.
• Develop microservices and APIs using Python and Go.
• Automate deployments through CI/CD pipelines.
• Ensure high availability, scalability, and observability.
• Build pipelines for fine-tuning and post-training of LLMs/SLMs.
• Work on reinforcement learning, model evaluation, and synthetic data generation.
• Support deployment and serving of custom AI models.

Good to Have

• Experience in Banking, Insurance, or Financial Services.
• Experience building AI Agent platforms.
• Open-source contributions in GenAI ecosystem.
• Experience with multi-tenant SaaS platforms.
• Hands-on experience with AI coding assistants (GitHub Copilot, Cursor, Claude, GPT).