Chicago, United States | Posted on 10/30/2026
Role: Lead AI Software Engineer ( 507554 )
Location: Chicago,IL (Hybrid – 2 Days a week onsite)
Duration: 12 MonthContract
Must HaveSkills/Attributes : AI, API, AWS, Java, LLM (LargeLanguage Model), Microservices, RAG (Retrieval-Augmented Generation)
Experience Desired
- JavaBackend Development
- Microservices& API Architecture (10+ Years)
- SoftwareArchitecture & Large-Scale Distributed Systems (8+ Years)
- GenerativeAI, LLMs, AI Agents, Prompt Engineering & RAG(LangChain/LangGraph/AutoGen/CrewAI) (3+ Years)
- TechnicalLeadership, Engineering Governance & Mentoring Multiple Teams (2+ Years)
Required MinimumEducation : Bachelor’s Degree
Job Description
RequiredEducation/Experience
- Bachelor’s degree in Computer science orElectrical engineering or related field
Required TechnicalSkills
- 8+ years of professional software engineeringexperience and 2+ years in a technical leadership role.
- Proven experience designing and deliveringlarge-scale distributed systems.
- Strong expertise in software architecture,APIs, microservices, cloud-native applications, and modern engineeringpractices.
- Experience influencing multiple engineeringteams and leading organization-wide technical initiatives.
- Strong communication, collaboration, andstakeholder management skills.
- Demonstrated ability to mentor engineers anddrive technical excellence.
- Experience with Generative AI, AI agents,LLM-powered applications, or intelligent automation platforms.
- Experience with AI development tools, codingassistants, and modern developer productivity platforms.
- Knowledge of security architecture,application security, and cloud security best practices.
- Experience establishing technical governanceand engineering standards across multiple teams.
Required Soft Skills
- Ability to work under pressure and withintime constraints
- Passion for technology and an eagerness tocontribute to a team-oriented environment
- Lead architectural designs and able to workacross teams to come up with solutions.
Summary of Role
- Design and orchestrate multi-agent workflowsand stateful AI systems using modern frameworks like LangChain, LangGraph,AutoGen, or CrewAI.
- Integrate foundation models (e.g., AnthropicClaude, OpenAI GPT, Google Gemini) via secure API gateways, managing tokenlimits, costs, and rate-limiting.
- Architect data models optimized for AI-nativestructures, integrating relational databases with vector databases for semanticsearch and Retrieval-Augmented Generation (RAG).
- Implement robust white-box testing andcontinuous evaluation metrics to monitor AI outputs for factual correctness,hallucinations, and safety compliance.
- Champion secure, reliable, and scalablesoftware solutions through architectural leadership, risk management, andcontinuous improvement of engineering practices.
Technical Leadership& Workflow Optimization
- Mentor and scale an engineering team,establishing engineering standards, best practices and architectural governancefor secure coding, continuous integration, and cloud-native deployment.
- Drive AI-assisted engineering velocity byintegrating next-gen development tools (e.g., Cursor, Claude Code, Windsurf)into the team's daily Software Development Life Cycle (SDLC).
- Establish governance policies and coachdevelopers 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, andperformance improvements.
Influence Across Teams& Champion Developer Experience
- Facilitate technical leadership forums withProduct 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 onsystem design, software architecture, and engineering excellence.
- Foster collaborative decision-making througharchitecture reviews, RFCs, and technical discussions.
- Promote self-service engineering capabilitiesand platform enablement.
- Drive automation initiatives that improveproductivity and software quality.
Interaction with team
- Significant interaction required with Scrumteam. Interaction during all scrum ceremonies such as Daily Standups, SprintPlanning, Grooming, Retro, Demo etc
- Also need to interact with team for PRReviews, also need to engage with other teams as needed.
Core SoftwareEngineering
- Backend Systems: Deep proficiency in backendenvironments, microservices architectures, and API design using Java.
- Cloud & DevOps: Extensive experience withcontainerization (Docker, Kubernetes) and public cloud infrastructure like AWSAI & LLM Infrastructure
- Orchestration & Tooling: Hands-on experiencewith production-level AI agents, prompt engineering, and advanced Agentic PDLCpatterns.
- Vector Databases: Practical knowledge ofvector technologies such as Pinecone, Milvus, Chroma, or pgvector.
- AI Tool Fluency: Demonstrated mastery of AIcoding assistants and a firm understanding of Model Context Protocol (MCP) tomediate agent connections with external databases.