Senior AI Engineer & Microsoft copilot studio

About Role

Job Title: Senior AI Engineer & Microsoft copilot studio

Experience: 4 to 7+ Years

Location: Hyderabad, India

Employment Type: Full-time

We are looking for a Senior AI Engineer with strong hands-on experience building and deploying enterprise Generative AI applications/agents and Microsoft Copilot Studio solutions .

You will work across LLM applications, RAG, AI agents, tool calling, enterprise copilots, Microsoft Copilot Studio, Python/FastAPI services, integrations, evaluation, security, and observability .

This is a senior individual contributor role where you will own AI solutions from architecture and design through production deployment and operations . You will make engineering trade-offs across quality, latency, scalability, security, reliability, and cost, while establishing reusable patterns for the wider engineering team.

Responsibilities:

AI Engineering

• Design and build enterprise-grade AI applications including copilots, knowledge assistants, and agentic workflows.
• Build RAG pipelines end to end - document ingestion, preprocessing, chunking, embeddings, retrieval, hybrid search, reranking, and context construction.
• Develop AI agent systems with tool calling, state management, memory, human-in-the-loop workflows, and failure recovery.
• Integrate LLMs and AI services into production applications using Python and FastAPI.
• Work with LangChain, LangGraph, or equivalent AI orchestration frameworks.
• Build reusable AI engineering patterns and components for enterprise applications.

Microsoft Copilot Studio

• Design, develop, and deploy enterprise copilots using Microsoft Copilot Studio .
• Build conversational agents, topics, actions, workflows, and enterprise integrations.
• Integrate Copilot Studio with Microsoft 365, Power Platform, Dataverse, APIs, and external enterprise systems .
• Configure and implement authentication, permissions, connectors, and secure access to enterprise data.
• Build custom actions and integrations using APIs, Power Automate, and other Microsoft services.
• Implement grounding and knowledge sources to improve response accuracy and reliability.
• Evaluate and optimize copilots for response quality, latency, usability, and business outcomes.
• Understand and apply responsible AI, security, governance, and access-control practices within Microsoft environments.

Backend & Application Engineering

• Build backend APIs and services using Python and FastAPI .
• Develop supporting application interfaces using React and/or Next.js .
• Design distributed services and integrations for enterprise AI applications.
• Implement authentication and authorization using OAuth2, OIDC, RBAC, and enterprise identity platforms where required.

Evaluation, LLMOps & Observability

• Define evaluation frameworks for groundedness, relevance, accuracy, latency, reliability, and cost .
• Build automated evaluation and regression-testing pipelines for LLM applications.
• Implement telemetry and observability for AI applications and agents.
• Monitor production AI systems for failures, latency, token usage, cost, and model behavior.
• Establish processes for continuous improvement, evaluation, and model/application drift.

Cloud & Production Engineering

• Own deployment and production operations for AI applications.
• Work with Azure, containers, CI/CD, and cloud-native architectures .
• Implement automated testing, deployment, monitoring, debugging, and incident response.
• Collaborate with DevOps/platform teams on production infrastructure and reliability.

Security & Governance

• Implement secure AI application architectures for enterprise environments.
• Apply authentication, authorization, RBAC, and secure API access.
• Understand and mitigate prompt injection, data leakage, insecure tool usage, and sensitive-data exposure .
• Implement appropriate logging, auditing, and governance mechanisms for AI systems.
• Follow responsible AI and enterprise security practices.

Leadership

• Lead technical design and architecture discussions.
• Conduct design and code reviews.
• Mentor engineers and establish engineering best practices.
• Convert ambiguous business requirements into scalable and shippable AI solutions.
• Work closely with product, business, security, and engineering teams.

Required Skills

• 4 to 7+ years of software engineering / AI engineerin…