Senior AI Software Engineer - Kiewit Infrastructure Engineers

Position Overview

Kiewit is building an enterprise AI platform that helps engineering and business teams work with company knowledge, use enterprise tools, and complete complex workflows. We are looking for an experienced Senior Software Engineer who has strong development skills, a passion for quality and wants to build engineering solutions that make a measurable difference to our business. 

This is a hands-on role spanning AI capabilities, backend services, user interfaces, and Kubernetes workloads. You’ll have a primary area of ownership and contribute across the product, working with the team’s technical lead on architecture and priorities and with platform, security, and data owners on shared systems. 

You’ll work directly with engineers and business specialists from early design through production delivery, combining their domain expertise with your software engineering judgment. You’ll build new features, take prototypes into production, and improve the systems people already depend on. 

AI development tools are a significant part of how we work. We expect engineers to understand the code they deliver, recognize flaws in generated implementations, and validate that changes meet the intended requirements. Independent judgment, constructive challenge, and responsibility for the result are central to this role. 

District Overview

2025 ENR National Contractor Rankings #1 for Transportation and #3 Top 100 design build firms

Kiewit Infrastructure Engineering's Design Build Management team are driving clients to turn to Kiewit during all stages of design-build projects to manage their multi-disciplined design teams to improve schedule, control costs, and minimize risk. Our construction-driven engineers analyze root causes and resolve design issues before they impact schedule and budget. Particularly on large design-build projects, clients benefit from the proven processes and tools used by Kiewit to minimize project risk. We are an in-house resource that supports projects throughout the company. Our staff shares experiences gained, innovative concepts, and design best practices for all projects that we support.

Our participation leads to safe, cost effective, and innovative designs that achieve client expectations and further Kiewit’s legacy of excellence.

On our team, you’ll have the opportunity to see more, touch more, and do more than you ever imagined. Working hard will not only bring you satisfaction from a job well done, but it will help propel your career forward faster than you might expect. We will train you, develop your skills, and allow you to take on projects that impact millions across North America. With top-notch health benefits, a wealth-building 401k plan, and unbeatable growth opportunities, by joining Kiewit, you’re ensuring a lifetime of success.

Location

This position will be based at one of Kiewit’s primary campus locations. Remote opportunities will be considered.

Responsibilities

• Own features and services through production. Clarify requirements and acceptance criteria, design and implement changes across the relevant AI, backend, data, and UI components, and support their operation after release. 
• Build and evaluate AI workflows. Integrate language models, retrieval, and enterprise tools. Work with domain experts to define task success and use representative evaluations to assess quality, failure behavior, latency, and cost. 
• Help domain experts deliver their ideas. Participate early in design, pair on implementation, and guide prototypes through architecture review, hardening, integration, and delivery. Explain tradeoffs clearly and help contributors develop stronger software practices. 
• Work directly with Kubernetes. Deploy, troubleshoot, and improve containerized application workloads, including configuration, networking, storage, resource usage, observability, and rollout and recovery behavior. Coordinate with platform teams on shared infrastructure. 
• Review and improve implementation quality. Review human-written and AI-generated code for correctness, security, reliability, and maintainability. Trace changes across components, challenge assumptions in the code and its tests, and address underlying causes of defects. 
• Protect company data and user access. Build integrations that respect user permissions, preserve data integrity, and handle AI-driven actions and failures safely, in partnership with security and data owners. 
• Strengthen software engineering practices. Improve existing workflows through meaningful automated tests, code review, error handling, CI/CD, documentation, and operational visibility. Keep solutions understandable and proportionate to the problem. 
• Make capabilities clear and usable. Carry features through UI integration and documentation, and keep ownership, dependencies, readiness, rollout status, and known limitations visible to the team. 

Qualifications

• 5+ years of professional software engineering experience designing, building, and maintaining production applications or services, including independent ownership of substantial features or services from design through deployment and ongoing support. 
• Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or a related technical field, or equivalent practical software engineering experience. 
• Hands-on Kubernetes experience deploying, operating, and troubleshooting containerized applications. 
• Strong programming and debugging skills, with depth in Python or TypeScript and the ability to contribute across Python services and TypeScript/React web applications. 
• The ability to read unfamiliar code, identify consequential defects and architectural weaknesses, and explain why a proposed correction is sound. 
• Practical experience integrating large language models (LLMs) or agent workflows into applications, including evaluating their behavior and limitations. 
• Experience using AI-assisted development tools while independently reviewing, debugging, and validating the resulting code. 
• Solid software engineering fundamentals across API design, data modeling, distributed systems, authentication and authorization, testing, version control, and CI/CD. 
• Experience moving prototypes into maintained production systems, with attention to security, failure handling, performance, and operability. 
• Clear communication and the ability to support contributors with different technical backgrounds. You should be comfortable questioning assumptions, offering a better approach, and adjusting your position when the evidence changes. 

PREFERRED QUALIFICATIONS 

• Experience with Azure and Azure Kubernetes Service (AKS), Helm, FastAPI, PostgreSQL, graph or vector retrieval, Model Context Protocol (MCP), and enterprise integrations would be especially relevant. We value depth in relevant areas and the ability to learn across the stack; familiarity with every technology in this section is not expected. 

WHAT SUCCESS LOOKS LIKE 

You independently deliver and support useful capabilities in your area of ownership, demonstrate their quality through software tests and AI evaluations, reduce recurring failures, and help other contributors become more effective. The result is a product the team can confidently understand, operate, and extend, with reusable practices that support additional use cases. #LI-JP1