IT Software Engineer 5 (Lead Software Engineer – AI Systems, Architecture & Developer Experience)

Role

IT Software Engineer 5 (Lead Software Engineer – AI Systems, Architecture & Developer Experience)

Location

Peoria, IL and/or Chicago office (Chicago preferred) - Hybrid; must go in office 2 days a week

Duration

12 Months, possibility to be extended

Exp

10-12 Years not more than 15 yrs

Description

We are seeking a visionary Lead Software Engineer to architect and deliver next-generation software platforms driven by Artificial Intelligence and Agentic workflows. In this senior leadership role, you will bridge the gap between core full-stack application development and cutting-edge Large Language Model (LLM) integration. You will work with several high-performing engineering teams, championing the adoption of AI coding assistants to radically accelerate our internal developer velocity while designing reliable, production-grade AI systems for our customers.

Position’s Contributions to Work Group

Technical Architecture & AI Integration

• 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, and 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.

Typical task breakdown

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.

Education & Experience Required

• Bachelor’s degree in Computer science or Electrical engineering or related field, Plus 10+ years exp
• Master Degree plus 8+ years exp

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.

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.

Experience Requirements

Overall Experience

• 10+ years of experience with a Bachelor's degree.
• With a Master's degree, the requirement can be reduced to 8+ years.
• Candidates with significantly more experience are acceptable; the hiring manager explicitly confirmed that more experience is fine/preferred.

Leadership

• 2+ years of technical leadership experience required.
• The role is primarily a technical leadership position, with hands-on technical involvement.
• Leadership experience does not necessarily need to come from formal people management.

Java Development – Critical Requirement

A strong Java development background is required.

The hiring manager clarified that candidates should not simply be strong AI/GenAI leaders with limited Java exposure.

The individual needs to

• Understand the existing Java codebase.
• Be able to evaluate AI-generated recommendations involving Java.
• Determine whether AI-generated recommendations are technically appropriate.
• Make or drive the necessary changes.
• Understand the implications of changes to the Java codebase.
• Be comfortable working with Java repositories hosted in GitHub.

A candidate who is highly experienced in AI but primarily codes in Python or another language without strong Java knowledge would likely not be suitable.

GenAI / AI Experience

Strong practical experience with Generative AI is a major requirement.

The role requires experience with areas such as

• Generative AI
• AI agents
• LLM-powered applications
• Intelligent automation platforms
• AI development tools
• AI coding assistants
• Modern developer productivity platforms

The hiring manager indicated that approximately 2 years of production AI experience is expected.

The candidate should have practical experience using and applying AI, rather than simply having theoretical knowledge.