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Kiewit · 9 hours ago

Applied AI Lead, Kiewit Infrastructure Engineers

Lone Tree, CO

Full-time

Onsite

Mid, Senior Level

$140K/yr - $146K/yr

Kiewit is a leading construction and engineering company, and they are seeking an Applied AI Lead to enhance data and software architecture to support AI and machine learning workflows. The role involves building scalable data pipelines, managing cloud storage, and developing tools for data extraction and transformation.

Building MaterialConstructionIndustrial EngineeringMiningOil and GasTransportation

H1B Sponsor Likely

Responsibilities

Data Pipeline Development: Maintain and enhance scalable Python-based data pipelines to process, synchronize, and structure robotic perception data for ML workflows

Database & Cloud Storage Management: Manage PostgreSQL AWS RDS instances and AWS S3 buckets to track and store raw and processed multimodal data

Tooling & Automation: Build custom Python tools for data extraction and transformation to support internal and downstream ML users. Automate pipeline execution via scheduled batch jobs, transitioning from manual processes to nightly workflows

Web Application Development: Contribute to a full-stack internal web application (FastAPI backend, React/Next.js TypeScript frontend) for data visualization, search, and cloud job triggering

Infrastructure-as-Code & DevOps: Manage AWS infrastructure (EKS, ECR, S3, RDS) using Terraform, integrated with GitLab CI/CD for reproducible deployments

Design workflows and tools to interface with external data annotation vendors, including REST API uploads and quality checks

Testing & Reliability: Implement unit testing frameworks using Python to ensure reliability and maintainability of internal tools

Agile Collaboration: Actively participate in Agile ceremonies including sprint planning, daily stand-ups, and sprint reviews

Qualification

PythonAIMachine LearningData Pipeline DevelopmentPostgreSQLAWSTerraformAnalytical SkillsProblem-SolvingCommunication SkillsTeam Player

Required

Ph.D. in Algorithms, Combinatorics, and Optimization with research focused and applications

Bachelor's degree in engineering or computer science

Proven track record of experience in systems and software development, supporting innovation in North American technology and engineering sectors

Experience in working on complex projects and/or projects relating to AI, data and machine learning with multiple disciplines

Strong proficiency in Python and experience with data pipeline development

Must be proficient with AI, Machine Learning, ML workflows and tools

Strong analytical, problem-solving, and communication skills (oral and written)

Proven ability to self-direct work efforts and lead others

Highly motivated, with a demonstrated passion for excellence and taking initiative

Team player with the ability to work independently to meet deadlines, goals and objectives

Regular, reliable attendance

Work productively and meet deadlines timely

Communicate and interact effectively and professionally with supervisors, employees, and others individually or in a team environment

Perform work safely and effectively. Understand and follow oral and written instructions, including warning signs, equipment use, and other policies

Work during normal operating hours to organize and complete work within given deadlines. Work overtime and weekends as required

Benefits

Top-tier medical, dental and vision plans covering eligible employees and dependents

Voluntary wellness and employee assistance programs

Life insurance

Disability

Retirement plans with matching

Generous paid time off

Company

Kiewit

Glassdoor3.8

At Kiewit, the projects we deliver make a difference, and we offer opportunities for you to make one, too.

Founded in 1884

Omaha, Nebraska, USA

10001+ employees

http://www.kiewit.com

H1B Sponsorship

Kiewit has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)

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2025 (18)

2024 (13)

2023 (19)

2022 (23)

2021 (17)

2020 (30)