Lead Backend Engineer – Agentic AI

Location: Hartford CT 3 Days Onsite
Employment Type: Contract
Experience: 57 Years
Visa: H1B Only

Virtusa is looking for a Lead Backend Engineer Agentic AI with strong backend software engineering experience and hands-on exposure to modern Agentic AI workflows and Model Context Protocol (MCP) servers.

The ideal candidate will have production-grade Python development strong relational database/SQL expertise and solid experience designing scalable backend systems. Candidates do not need to come from a pure AI/ML research background; strong software engineering fundamentals architecture skills and practical AI-agent integration experience are the primary focus.

The selected candidate will also provide technical leadership by driving architecture and design decisions conducting design reviews establishing engineering standards and mentoring other engineers.

• Design develop and maintain scalable production-grade backend services using Python.

• Own technical direction for a workstream or service area.

• Design modular maintainable loosely coupled services with clear domain boundaries.

• Build horizontally scalable systems using stateless architecture partitioning/sharding load distribution and resilient service patterns.

• Design and integrate Agentic AI workflows and MCP-based solutions into production systems.

• Lead technical design reviews and establish software engineering standards.

• Evaluate architecture tradeoffs involving consistency availability latency throughput scalability and maintainability.

• Implement event-driven and asynchronous processing patterns where appropriate.

• Apply strong practices around idempotency caching API versioning and fault tolerance.

• Work closely with product architecture and engineering stakeholders on technical decisions.

• Mentor engineers on software architecture coding practices and system design.

• Drive adoption of Agentic AI/MCP patterns across engineering teams.

• 57 years of professional software engineering experience.

• Strong Python development experience as the primary programming language.

• Strong SQL and relational database fundamentals.

• Experience with:

  • Database schema design

  • Data modeling

  • Query optimization

  • Relational databases

• Hands-on experience with Agentic AI workflows and/or MCP servers.

• Strong understanding of backend architecture and distributed systems.

• Experience designing scalable and resilient production systems.

• Strong knowledge of SOLID principles modular design and separation of concerns.

• Strong understanding of domain-driven boundaries and service-oriented architecture.

• Experience with event-driven and asynchronous architectures.

• Strong technical communication and leadership skills.

Preferred:

• Google Cloud Platform (GCP)

Acceptable:

• AWS

Candidates should have practical cloud experience deploying or supporting production backend applications.

Candidates should demonstrate experience with:

• Modular architecture

• High cohesion / low coupling

• Bounded components and services

• Stateless application design

• Horizontal scalability

• Partitioning and sharding

• Load distribution

• Avoiding single points of failure/contention

• Event-driven architecture

• Asynchronous processing

• Idempotency

• Caching strategies

• API design and versioning

• Distributed-system reliability

• Performance and scalability optimization

• Technical tradeoff analysis

Hands-on exposure to Agentic AI is highly important.

Relevant experience may include:

• AI agent workflows

• Multi-step agent orchestration

• Tool-using AI agents

• LLM-integrated backend services

• Agent-to-tool integrations

• MCP servers / Model Context Protocol

• AI-driven automation workflows

• Production integration of AI agents with enterprise systems

Strong backend engineers with practical Agentic AI/MCP experience are preferred over candidates whose experience is primarily AI/ML research.

The candidate should be capable of:

• Owning technical direction for a service or workstream.

• Making architecture and design decisions.

• Leading design/code reviews.

• Establishing technical standards and best practices.

• Mentoring engineers.

• Communicating architecture decisions to technical and non-technical stakeholders.

• Partnering with product and architecture teams.

• Driving adoption of Agentic AI and MCP patterns.