IT Software Engineer 4 – Lead Software Engineer – Generative AI & Platform Engineering
Requisition ID: 119604-1
Duration: 12 Months
Location: Chicago, IL (Preferred); Peoria, IL; Irving, TX; Broomfield, CO
Work Arrangement: Hybrid (2–3 days onsite per week); Candidates must be open to an increased onsite requirement in the future.
Interview Process: 2 rounds – Virtual/Phone (technical screening and second-round interview)
Focus : Candidates with strong hands-on software engineering, architecture, technical leadership, and practical AI/GenAI implementation experience. Stable employment history is important. Chicago-based candidates are preferred, but candidates near the other listed hubs may also be considered.
Ideal Candidate Profile
The ideal candidate is a hands-on Lead Software Engineer who combines strong software development and architecture capabilities with experience evaluating and implementing emerging technologies. The candidate should be comfortable leading technical initiatives, mentoring engineers, building prototypes, and taking innovative solutions into production.
Strong experience in Python/Java, cloud-native engineering, software architecture, APIs, and Generative AI/Agentic AI will be particularly valuable.
Position Overview
Client is seeking a Lead Software Engineer to join its Emerging Technology group. This individual will serve as a hands-on technical leader responsible for designing, developing, piloting, and scaling next-generation software solutions that address high-value business challenges.
The role combines strong software engineering expertise with practical innovation, translating emerging technology concepts into secure, scalable, reliable, and production-ready solutions. The ideal candidate will have experience with modern software architecture, cloud-native development, APIs, automation, and emerging technologies such as Generative AI, Agentic AI, and Retrieval-Augmented Generation (RAG).
Key Responsibilities
- Lead the architecture, design, development, and testing of modern software solutions, prototypes, pilots, and reusable platform capabilities.
- Evaluate, prototype, and implement emerging technologies, including Generative AI, Agentic AI, RAG, cloud-native services, APIs, and automation.
- Translate business requirements and product objectives into scalable software architectures, technical roadmaps, and implementation plans.
- Lead technical initiatives across the full Software Development Lifecycle (SDLC), including requirements analysis, design, coding, testing, deployment, and production support.
- Mentor engineers, provide technical direction, conduct design reviews, and promote engineering best practices.
- Collaborate with product managers, architects, data scientists, cybersecurity, infrastructure, UX, and business stakeholders.
- Establish proof-of-concept success criteria, performance metrics, quality gates, automated testing, monitoring, and production-readiness standards.
- Identify technical risks, dependencies, integration requirements, security considerations, and operational constraints.
- Drive reusable engineering standards, architecture patterns, frameworks, and technical accelerators.
- Help transition emerging technology concepts from experimentation to enterprise adoption and production environments.
Required Qualifications
- Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Technology, or a related technical discipline, with 8+ years of relevant experience.
- Candidates without a bachelor's degree must have 10+ years of relevant professional experience.
- Progressive experience in software engineering, including hands-on development of complex applications, distributed systems, APIs, platforms, or cloud-native services.
- Demonstrated experience leading technical initiatives across the full SDLC.
- Strong programming proficiency in one or more modern languages: Python, Java, JavaScript/TypeScript, C#, Go, or similar modern programming languages.
- Experience designing scalable, secure, observable, and maintainable software solutions.
- Strong understanding of software architecture, integration patterns, APIs, automated testing, CI/CD, and DevOps practices.
- Working knowledge of cloud platforms, containerization, infrastructure automation, and production support.
- Strong analytical, problem-solving, decision-making, and critical-thinking skills.
- Ability to communicate complex technical concepts to engineering, product, architecture, security, and business stakeholders.
Preferred Qualifications
- Experience developing or integrating AI/ML, Generative AI, Large Language Models (LLMs), Agentic AI, RAG, vector databases, or prompt-based solutions.
- Experience taking emerging technology concepts from proof of concept through pilot, production deployment, governance review, and operational support.
- Familiarity with responsible AI practices, model evaluation, AI guardrails, data privacy, cybersecurity, compliance, and enterprise risk management.
- Experience with: cloud-native and serverless architectures; Kubernetes and microservices; event-driven architecture; API management and integration; observability and monitoring platforms; Infrastructure as Code (IaC).
- Experience working with cross-functional teams across product, design, data, security, architecture, and business functions.
- Proven ability to mentor engineers, influence technical direction, and establish reusable engineering standards and frameworks.
- Advanced degree or certifications in cloud computing, AI/ML, or software architecture.
- Contributions to open-source projects, technical communities, patents, publications, or enterprise innovation initiatives.
Key Technical Competencies
- Software Development & Engineering
- Software Architecture & Product Design
- Full Software Development Lifecycle (SDLC)
- Software Integration Engineering
- Modern Programming Languages
- Cloud-Native Application Development
- API Development & Integration
- Generative AI, Agentic AI & RAG
- Microservices & Distributed Systems
- CI/CD & DevOps
- Automated Testing & Quality Engineering
- Technical Leadership & Mentoring
- System Performance & Production Readiness
- Security, Scalability & Maintainability
