Lead Software Engineer Emerging Tech and AI Cloud Solutions

Job Title: Lead Software Engineer Emerging Tech and AI Cloud Solutions

Job Location: Chicago, IL (Preferred) 60661, Peoria, IL 61629, Irving, TX 75039 Hybrid Onsite 2-3 Days/Week

Estimated Duration: 13+ Months

Visa: USC, GC, H1-B, H4-EAD, GC-EAD, L2-EAD

Experience: 10+ Years and Above

Must Have Skills/Attributes:

API, Product Design, Software Development

Experience Desired:
Software Development (8 yrs),
Software Integration (8 yrs),
Software Product Design and Architecture (8 yrs),
Software Product technical knowledge and testing (8 yrs)

Education Requirements:
- Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Technology, or related field

Preferred Education:
- Master's degree

Preferred Certifications:
- Cloud certification
- AI/ML certification
- Software Architecture certification

Required Skills for the Lead Software Engineer:
- 8+ years of experience
- Decision Making and Critical Thinking: Knowledge of the decision-making process and associated tools and techniques; ability to accurately analyze situations and reach productive decisions based on informed judgment
- Software Development: Knowledge of software development tools and activities; ability to produce software products or systems in line with product requirements
- Software Development Life Cycle: Knowledge of software development life cycle; ability to use a structured methodology for delivering and managing new or enhanced software products to the marketplace
- Software Integration Engineering: Knowledge of software integration processes and functions; ability to design, develop and maintain interfaces and linkage to alternative platforms and software packages
- Software Product Design/Architecture: Knowledge of software product design; ability to convert market requirements into the software product design
- Software Product Technical Knowledge: Knowledge of technical aspects of a software products; ability to design, configure and integrate technical aspects of software products
- Software Product Testing: Knowledge of software product testing; ability to design, plan, and execute testing strategies and tactics to ensure software product quality and adherence to stated requirements
- Progressive professional experience in software engineering, including hands-on development of complex applications, distributed systems, APIs, platforms, or cloud-native services
- Demonstrated ability to lead technical work across the full software development lifecycle, including requirements analysis, architecture, design, coding, testing, deployment
- Strong proficiency in one or more modern programming languages such as Python, Java, JavaScript/TypeScript, C#, Go, or similar languages
- Experience designing scalable, secure, observable, and maintainable software using modern architecture patterns, APIs, automated testing, CI/CD, and DevOps practices
- Working knowledge of cloud platforms, containerization, infrastructure automation, integration patterns, and production support practices
- Ability to communicate complex technical topics clearly to engineering, product, architecture, security, and business stakeholders
- Demonstrated analytical, problem-solving, and decision-making skills in ambiguous or rapidly evolving technical environments

Preferred Skills:
- Experience building or integrating AI, machine learning, generative AI, large language model, Agentic, retrieval-augmented generation, vector database, or prompt-based solutions
- Experience taking emerging technology concepts from proof of concept through pilot, production hardening, governance review, adoption, and operational support
- Familiarity with responsible AI practices, model evaluation, guardrails, data privacy, cybersecurity, compliance, and enterprise risk management considerations
- Experience with modern cloud services, serverless architectures, Kubernetes, microservices, event-driven architecture, API management, observability platforms, and infrastructure-as-code
- Experience partnering with product, design, data, security, architecture, and business teams to identify high-impact use cases and deliver measurable business outcomes
- Proven ability to mentor engineers, influence technical direction without direct authority, and establish reusable engineering standards, patterns, frameworks, or accelerators

Lead Software Engineer Overview:
The Lead Software Engineer in the Emerging Technology group is a hands-on technical leader responsible for designing, building, piloting, and scaling next-generation software solutions that apply emerging technologies to high-value business problems. This role combines deep software engineering expertise with practical innovation, helping translate exploratory concepts into secure, reliable, maintainable, and production-ready capabilities

Responsibilities:
- Lead the architecture, design, development and testing of modern software solutions, prototypes, pilots, and reusable platform capabilities
- Evaluate, prototype, and apply emerging technologies such as generative AI, Agentic workflows, retrieval-augmented generation, cloud-native services, APIs, automation, and data-driven application patterns
- Translate business opportunities, product goals, and technical requirements into scalable software designs, solution patterns, technical roadmaps, and implementation plans
- Mentor engineers, provide technical direction, facilitate design reviews, and promote a culture of experimentation, learning, engineering excellence, and responsible technology adoption
- Collaborate with product managers, architects, data scientists, cybersecurity, infrastructure, UX, and business stakeholders to deliver solutions aligned to organizational goals and risk expectations
- Define and implement technical evaluation methods, including proof-of-concept success criteria, model or system performance measures, quality gates, automated testing, monitoring, and production readiness reviews
- Identify technical risks, dependencies, integration needs, security considerations, and operational constraints early in the solution lifecycle and recommend practical mitigation strategies