Note: The job is a remote job and is open to candidates in USA. Kiewit is building an enterprise AI platform for engineering and business teams to use company knowledge, enterprise tools, and complex workflows. The Senior AI Software Engineer will develop and operate AI capabilities, backend services, user interfaces, and Kubernetes workloads, taking features from design through production and ongoing support.
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
Skills
- 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
- 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
Benefits
- Top-tier medical, dental and vision plans covering eligible employees and dependents
- Voluntary wellness and employee assistance programs
- Life insurance
- Disability plans
- Retirement plans with matching
- Generous paid time off
- Remote opportunities will be considered
- Training and skills development
- Growth opportunities
Company Overview
Company H1B Sponsorship