Senior AI Platform Engineer

Job Description: Senior AI Platform Engineer (Enterprise Integrations & Agent Platform)

Location: Hyderabad / Indore / Gurgaon (Hybrid)
Experience: 7-12 Years
Employment Type: Full-Time

About the Role

We are seeking a highly skilled Senior AI Platform Engineer to design, develop, and scale enterprise-grade AI platforms, intelligent agents, and integrations that transform Software Engineering and Quality Engineering workflows. The ideal candidate will have strong expertise in Python, Generative AI technologies, cloud-native applications, and enterprise tool integrations.

In this role, you will be responsible for building AI-powered solutions that drive automation, enhance developer productivity, and enable seamless integration across engineering ecosystems.

Key Responsibilities

• Design, develop, and deploy scalable AI/LLM-powered applications and AI agents.
• Build and maintain enterprise integrations with engineering and collaboration tools such as Jira, Azure DevOps, GitHub, ServiceNow, Confluence, Jenkins, and SonarQube.
• Develop REST APIs and microservices using Python and FastAPI.
• Design and implement RAG (Retrieval-Augmented Generation) solutions and knowledge retrieval systems.
• Create reusable Agent SDKs, AI frameworks, and shared platform capabilities.
• Develop and manage MCP Servers and enterprise connectors.
• Build, deploy, and manage applications using Kubernetes, Docker, and cloud platforms (Azure, AWS, or GCP).
• Implement observability, monitoring, logging, and telemetry capabilities for AI platforms.
• Collaborate with cross-functional teams to deliver secure, reliable, and scalable AI solutions.
• Drive continuous improvements in engineering productivity through intelligent automation.

Required Skills & Experience

• 7-12 years of experience in software development and platform engineering.
• Strong proficiency in Python programming.
• Hands-on experience with Generative AI, Large Language Models (LLMs), and AI-powered applications.
• Expertise in FastAPI, REST API development, and Microservices architecture.
• Experience with Kubernetes, Docker, and cloud-native application deployment.
• Strong understanding of Prompt Engineering, Tool Calling, and Function Calling.
• Experience implementing RAG architectures, vector databases, and knowledge retrieval systems.
• Experience integrating with enterprise platforms and development tools.
• Knowledge of CI/CD pipelines, DevOps practices, monitoring, and observability frameworks.
• Excellent problem-solving and system design skills.

Good to Have

• Experience with LangGraph, CrewAI, Semantic Kernel, AutoGen, or similar AI frameworks.
• Knowledge of Model Context Protocol (MCP) and MCP Server development.
• Experience designing and implementing Multi-Agent Systems.
• Exposure to workflow orchestration and automation platforms.
• Experience with Microsoft Teams integrations and VS Code extensions.
• Background in Platform Engineering, DevOps, Software Engineering Productivity, or Quality Engineering.