IT Software Engineer 4

Job Title: IT Software Engineer 4 Chicago (Ideal location), Peoria, Irving, TX, and Broomfield, CO, but open to 100% remote Duration: 12 months Screening interview during the technical interview, then a 2nd round. Typical task breakdown: 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. Work environment: 2-3 days a week in the office and for the other offices, it is as needed basis. A full return could happen at any point. Education & Experience Required: Bachelor’s degree (technology-related field) with 8+ years of experience in this capacity No degree than 10_ years in this capacity. Required Technical Skills (Required) 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. Considerations For Top Candidates: Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, Information Technology, or a related technical discipline; equivalent practical experience may be considered. 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 Qualifications 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. Advanced degree, cloud certification, AI/ML certification, software architecture certification, or demonstrated contribution to technical communities, open-source projects, patents, publications, or internal innovation initiatives.