Senior Backend Engineer (Agentic AI)

Position Senior Backend Engineer (Agentic AI)

Location: Hartford, CT (5 Days Onsite)

Duration: 6 Months Contract

About the Role:

• We're looking for engineers who can design and build production systems that combine strong software
• fundamentals with hands-on exposure to modern AI/ML tooling - specifically agentic AI workflows and
• Model Context Protocol (MCP) servers. You don't need to come from a pure AI/ML background; what matters is strong core engineering skills, sound architectural judgment, and the ability to pick up (or already know) how to integrate AI agents into real systems. This is a single posting covering both
• Senior and Lead levels - candidates with 4 7 years of experience are encouraged to apply.

Must-Have Skills:

• Python - strong, production-grade proficiency (primary language)
• Databases - solid relational/SQL fundamentals; schema design, query optimization, data modeling
• Cloud platform - strong hands-on experience with at least one of: Google Cloud Platform (GCP)
• (preferred), or AWS (acceptable alternative) 4+ years of professional software engineering experience

Design & Architecture Thinking Required:

• Strong grounding in modular design - clear separation of concerns, well-bounded components/services, low coupling / high cohesion
• Ability to design systems that scale horizontally - statelessness where it matters, partitioning/sharding strategy, load distribution, avoiding single points of contention
• Working fluency in core design patterns and principles (e.g., SOLID, domain-driven boundaries, event-driven/async patterns, idempotency, caching strategies, API versioning) and knowing when to apply vs. avoid them
• Comfortable reasoning about tradeoffs: consistency vs. availability, latency vs. throughput, build vs. buy, synchronous vs. async workflows
• For Lead specifically: expected to drive these principles - set direction in design reviews, push back on
• designs that won't scale, and mentor others toward this way of thinking rather than just applying it.

API & Real-Time Integration Best Practices:

• Strong grasp of RESTful API design - resource modeling, versioning, pagination, idempotency for retries, proper status codes/error contracts
• Practical experience with WebSocket-based real-time communication - connection lifecycle management, reconnection/backoff strategy, heartbeat/keep-alive handling, and graceful degradation when a socket drops
• Understands tradeoffs between REST, WebSockets, and event-driven/streaming integration patterns, and picks the right one for the use case
• Follows security best practices for integrations - authentication/authorization (OAuth2,token scoping), input validation, rate limiting, and safe handling of external payloads
• Designs integrations for observability and resilience - structured logging, timeouts, circuit breakers, and clear failure modes rather than silent drops

What We're Really Screening For:

• Strong in Python + SQL/databases as a baseline
• Solid architectural instincts - modular, scalable design, not just "make it work"
• Proven in one major cloud (GCP strongly preferred, AWS acceptable)
• Comfortable or curious about Java (bonus, not blocker)
• Solid API/WebSocket integration practices - reliability, security, and observability by default
• Open to learning / already exposed to agentic AI + MCP server patterns
• Ideally has touched healthcare/health-tech systems before, but this is a plus, not a gate