Lead AI Software Engineer

Role: Lead AI Software Engineer (507554) Location: Chicago, IL (Hybrid – 2 Days a week onsite) Duration: 12 Month Contract Must Have Skills/Attributes: AI, API, AWS, Java, LLM (Large Language Model), Microservices, RAG (Retrieval-Augmented Generation) Experience Desired:

• Java Backend Development
• Microservices & API Architecture (10+ Years)
• Software Architecture & Large-Scale Distributed Systems (8+ Years)
• AWS Cloud, Docker & Kubernetes (Cloud-Native Development) (8+ Years)
• Generative AI, LLMs, AI Agents, Prompt Engineering & RAG (Lang. Chain/Lang. Graph/Auto. Gen/CrewAI) (3+ Years)
• Technical Leadership, Engineering Governance & Mentoring Multiple Teams (2+ Years) Required Minimum Education: Bachelor’s Degree Job Description Required Education/Experience:
• Bachelor’s degree in Computer science or Electrical engineering or related field Required Technical Skills:
• 8+ years of professional software engineering experience and 2+ years in a technical leadership role.
• Proven experience designing and delivering large-scale distributed systems.
• Strong expertise in software architecture, APIs, microservices, cloud-native applications, and modern engineering practices.
• Experience influencing multiple engineering teams and leading organization-wide technical initiatives.
• Strong communication, collaboration, and stakeholder management skills.
• Demonstrated ability to mentor engineers and drive technical excellence.
• Experience with Generative AI, AI agents, LLM-powered applications, or intelligent automation platforms.
• Experience with AI development tools, coding assistants, and modern developer productivity platforms.
• Knowledge of security architecture, application security, and cloud security best practices.
• Experience establishing technical governance and engineering standards across multiple teams. Required Soft Skills:
• Ability to work under pressure and within time constraints
• Passion for technology and an eagerness to contribute to a team-oriented environment
• Lead architectural designs and able to work across teams to come up with solutions. Summary of Role:
• Design and orchestrate multi-agent workflows and stateful AI systems using modern frameworks like Lang. Chain, Lang. Graph, Auto. Gen, 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. Technical Leadership & Workflow Optimization:
• 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. Influence Across Teams & Champion Developer Experience:
• 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. Interaction with team:
• Significant interaction required with Scrum team. Interaction during all scrum ceremonies such as Daily Standups, Sprint Planning, Grooming, Retro, Demo etc
• Also need to interact with team for PR Reviews, also need to engage with other teams as needed. Core Software Engineering:
• Backend Systems: Deep proficiency in backend environments, microservices architectures, and API design using Java.
• Cloud & DevOps: Extensive experience with containerization (Docker, Kubernetes) and public cloud infrastructure like AWS AI & LLM Infrastructure
• Orchestration & Tooling: Hands-on experience with production-level AI agents, prompt engineering, and advanced Agentic PDLC patterns.
• Vector Databases: Practical knowledge of vector technologies such as Pinecone, Milvus, Chroma, or pgvector.
• AI Tool Fluency: Demonstrated mastery of AI coding assistants and a firm understanding of Model Context Protocol (MCP) to mediate agent connections with external databases.