Lead Backend Engineer - Agentic AI

We are looking for a Lead Backend Engineer who can design and build production systems that combine strong software engineering fundamentals with hands-on exposure to modern AI/ML tooling - specifically Agentic AI workflows and Model Context Protocol (MCP) servers., Set direction in design reviews, push back on designs that will not scale, and mentor others toward strong architectural thinking. Lead Responsibilities Own technical direction for a workstream or service area. Drive modular, horizontally scalable design decisions across the team - not just follow them. Lead design reviews, establish technical standards, and mentor engineers on architectural thinking. Drive adoption of Agentic AI / MCP patterns across the team. Partner with product and architecture stakeholders on technical tradeoffs., Our client, a IT Services and Consulting company, is looking for a Senior AI/ML Engineer - Java, Python & Generative AI for their Hartford, CT location. Requirements: 5+ years …

• 14 hours ago, 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 …
• 21 hours ago
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You do not need to come from a pure AI/ML background. What matters is strong core engineering skills, sound architectural judgment, and the ability to integrate AI agents into real-world production systems. This role requires an engineer who can not only apply strong architectural principles but also drive technical direction, lead design decisions, and mentor other engineers. Must-Have Skills Python - strong, production-grade proficiency; primary programming language. Databases - solid relational/SQL fundamentals, including schema design, query optimization, and data modeling. Cloud platform - strong hands-on experience with Google Cloud Platform (GCP) preferred; AWS is an acceptable alternative. 6+ years of professional software engineering experience. Design & Architecture Strong grounding in modular design - clear separation of concerns, well-bounded components/services, and low coupling/high cohesion. Ability to design systems that scale horizontally - statelessness where appropriate, partitioning/sharding strategy, load distribution, and avoiding single points of contention. Working fluency in core design patterns and principles, including SOLID, domain-driven boundaries, event-driven/async patterns, idempotency, caching strategies, and API versioning. Comfortable reasoning about tradeoffs: consistency vs. availability, latency vs. throughput, build vs. buy, and synchronous vs. asynchronous workflows.