Lead Engineer- Copilot (NCS/Job/ 3762)

Lead Engineer – AI-Native Enterprise Platform 

Experience:Agentic AI | LLM | FastAPI | Azure/Multi-Cloud | ITSM

About the Role

We are looking for a Lead Engineer with 7–10 years of experience to drive the development and implementation of an AI-native enterprise platform enabling intelligent automation, agentic workflows, and IT operations transformation. This role requires strong hands-on expertise in Agentic AI, LLM integrations, microservices, and cloud technologies, along with the ability to lead modules, mentor teams, and ensure high-quality delivery.

Key Responsibilities

• Design and develop key modules of the platform including AI agents, APIs, and backend services
• Contribute to implementation of Agentic AI workflows, LLM integrations, and RAG pipelines
• Build and enhance FastAPI-based microservices and REST/GraphQL APIs
• Work on data integration and storage layers (PostgreSQL, Redis, MongoDB, vector DBs)
• Support deployment and operations across Azure / multi-cloud environments
• Implement integrations with ITSM tools like ServiceNow, Jira, Remedy
• Follow and enforce secure coding practices including OAuth2/JWT and API security
• Contribute to CI/CD pipelines and containerization (Docker/Kubernetes)
• Collaborate with architects to align development with platform standards
• Troubleshoot issues, optimize performance, and ensure reliability
• Mentor junior developers and support knowledge sharing

Required Skills

• Python 3+, FastAPI, REST APIs
• LLMs (GPT, Claude, Llama), LangChain/LangGraph exposure
• Vector DB basics (pgvector/Weaviate), prompt engineering
• PostgreSQL, MongoDB, Redis
• Azure (preferred), AWS/GCP
• Docker, Kubernetes
• ServiceNow/Jira integrations
• OAuth2, JWT, RBAC
• CI/CD, Git, Terraform

Preferred Qualifications

• Experience in AI/GenAI enterprise applications
• Exposure to agentic workflows or automation platforms
• ServiceNow or ITSM experience
• Agile/Scrum delivery experience
• Telco/NOC/IT Operations exposure

Key Expectations

• Strong ownership of deliverables and timelines
• Ability to drive modules independently
• Proactive risk identification and problem solving
• Ensure code quality and best practices
• Act as bridge between architecture, development, and operations