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 (LangChain/LangGraph/AutoGen/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 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.

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.