Role: IT Software Engineer 4 – Lead Software Engineer – Generative AI & Platform EngineeringRequisition
Location: Chicago, IL (Preferred); Peoria, IL; Irving, TX; Broomfield, CO
Pay rate: $69-$76/hr
Position Overview
Our client, a global leader in the industrial and manufacturing industry, is seeking an experienced Lead Software Engineer – Generative AI & Platform Engineering to join its Emerging Technology group.
This is a hands-on technical leadership opportunity for an engineer who combines strong software development expertise, modern architecture capabilities, cloud-native engineering, and practical experience implementing emerging technologies.
The selected candidate will lead the design, development, prototyping, and deployment of scalable software solutions that address complex business challenges. The role requires someone who can translate innovative technology concepts into secure, reliable, maintainable, and production-ready enterprise solutions.
The ideal candidate will bring strong programming experience in Python and/or Java, expertise in software architecture and APIs, and practical exposure to Generative AI, Agentic AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
Key Responsibilities
Lead the architecture, design, development, testing, and deployment of modern software applications, prototypes, and reusable platform capabilities.
Evaluate, prototype, and implement emerging technologies, including Generative AI, Agentic AI, RAG, cloud-native services, APIs, and automation frameworks.
Translate business requirements and product objectives into scalable architectures, technical roadmaps, and implementation strategies.
Drive end-to-end Software Development Lifecycle (SDLC) activities, including requirements analysis, design, development, testing, deployment, and production support.
Provide hands-on technical leadership, mentor engineers, conduct architecture and code reviews, and establish engineering best practices.
Collaborate with product managers, architects, data scientists, cybersecurity specialists, infrastructure teams, UX professionals, and business stakeholders.
Define proof-of-concept objectives, success criteria, performance benchmarks, automated testing strategies, and production-readiness standards.
Identify technical risks, dependencies, integration challenges, security requirements, and operational considerations.
Develop reusable architecture patterns, engineering frameworks, technical accelerators, and platform standards.
Drive the transition of emerging technology initiatives from experimentation and proof of concept into enterprise-scale 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 professional experience.
Candidates without a bachelor's degree must have 10+ years of relevant professional experience.
Strong hands-on software engineering experience developing complex applications, distributed systems, APIs, platforms, or cloud-native solutions.
Demonstrated experience leading technical initiatives across the complete Software Development Lifecycle (SDLC).
Strong programming proficiency in one or more modern programming languages:
Python
Java
JavaScript/TypeScript
C#
Go
Other comparable modern programming languages
Strong understanding of software architecture, design patterns, system integration, API development, and distributed systems.
Experience designing scalable, secure, observable, maintainable, and high-performing software solutions.
Knowledge of automated testing, CI/CD pipelines, DevOps practices, and software quality engineering.
Working knowledge of cloud platforms, containerization, infrastructure automation, and production support.
Strong analytical, problem-solving, decision-making, and critical-thinking capabilities.
Excellent communication skills, with the ability to explain complex technical concepts to engineering and non-technical stakeholders.
Preferred Qualifications
Practical experience developing or integrating AI/ML solutions, Generative AI applications, Large Language Models (LLMs), Agentic AI, or Retrieval-Augmented Generation (RAG).
Experience working with vector databases, embeddings, prompt engineering, AI agents, and LLM integration frameworks.
Demonstrated ability to move emerging technology solutions 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 AI governance.
Experience with cloud-native and serverless architectures, Kubernetes, microservices, and event-driven architecture.
Knowledge of API management, enterprise integration, observability, monitoring, and Infrastructure as Code (IaC).
Experience collaborating with cross-functional teams across product, design, data, security, architecture, and business functions.
Proven ability to mentor engineers, influence technical decisions, and establish reusable engineering standards.
Advanced degree or relevant 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
Hands-on Software Development and Engineering
Software Architecture and System Design
Python and/or Java Development
Generative AI, Agentic AI, and LLM Integration
Retrieval-Augmented Generation (RAG)
Cloud-Native Application Development
API Development and Integration
Microservices and Distributed Systems
Full Software Development Lifecycle (SDLC)
CI/CD and DevOps Engineering
Automated Testing and Quality Engineering
System Performance and Production Readiness
Technical Leadership and Engineering Mentorship
Security, Scalability, and Maintainability
Ideal Candidate Profile
We are looking for a hands-on technical leader who can balance software engineering excellence with innovation and emerging technology adoption.
The ideal candidate should demonstrate:
Strong, recent hands-on software development experience.
Practical implementation experience with Generative AI or related emerging technologies.
Proven ownership of architecture and end-to-end engineering initiatives.
Experience building prototypes and successfully transitioning them into production.
Ability to mentor engineers and influence technical direction.
A consistent professional career history demonstrating sustained contributions and increasing technical responsibility.
