Lead Java Backend Developer (AI) - 439

DSM-H Consulting is seeking a Lead Java Backend Developer (AI) to provide architectural and technical leadership across multiple scrum teams and repositories. The role focuses on reviewing and improving Java codebases, integrating generative AI and agentic systems, advancing security and cloud practices, mentoring engineers, and improving developer productivity and engineering excellence.

Responsibilities:

• Design and orchestrate multi-agent workflows and stateful AI systems using modern frameworks like LangChain, LangGraph, AutoGen, or CrewAI
• Integrate foundation models (e.g., Anthropic Claude, OpenAI GPT, Google Gemini) via secure API gateways, managing token limits, costs, and rate-limiting
• Architect data models optimized for AI-native structures, integrating relational databases with vector databases for semantic search and Retrieval-Augmented Generation (RAG)
• Implement robust white-box testing and continuous evaluation metrics to monitor AI outputs for factual correctness, hallucinations, and safety compliance
• Champion secure, reliable, and scalable software solutions through architectural leadership, risk management, and continuous improvement of engineering practices
• Mentor and scale an engineering team, establishing engineering standards, best practices and architectural governance for secure coding, continuous integration, and cloud-native deployment
• Drive AI-assisted engineering velocity by integrating next-gen development tools (e.g., Cursor, Claude Code, Windsurf) into the team's daily Software Development Life Cycle (SDLC)
• Establish governance policies and coach developers on the responsible use of AI, focusing on input data sensitivity, license compliance, and security guardrails
• Evaluate existing systems, services, APIs, and data models to identify opportunities for modernization, scalability, and performance improvements
• Facilitate technical leadership forums with Product Owners, Technical Leads, Architects, and Engineering Managers
• Drive conversations around architecture, engineering health, technical debt, AI adoption, and continuous improvement
• Mentor engineers and technical leaders on system design, software architecture, and engineering excellence
• Foster collaborative decision-making through architecture reviews, RFCs, and technical discussions
• Promote self-service engineering capabilities and platform enablement
• Drive automation initiatives that improve productivity and software quality
• Lead architectural designs and able to work across teams to come up with solutions