AI Engineer

12 days ago

Centennial, CO, USAEntry Level / Mid Level

Base Salary

$95k - $130k/yr

Responsibilities

Design, build, and deploy LLM-powered agents using tool use, orchestration, multi-step reasoning, and human-in-the-loop patterns.
Operate production agents by monitoring behavior, diagnosing failures, tuning prompts and tools, and managing model and dependency upgrades.
Build evaluation suites with offline test sets, LLM-as-judge scoring, regression testing, and online metrics.
Instrument agents and use observability data covering traces, tool calls, token usage, latency, cost, and outcome quality.
Design retrieval and context strategies including RAG, structured data access, caching, chunking, and ranking.
Build and maintain tools, APIs, and connectors for safe and reliable interaction with internal systems and data.
Develop scalable AI pipelines and services on AWS using Terraform and automated deployment practices.
Implement safety controls, validation, access boundaries, and audit trails for a regulated environment.
Partner with teams to identify agent use cases, create reusable frameworks and standards, document systems, track agent tooling, and mentor team members.

Bachelor’s or master’s degree in computer science, machine learning, artificial intelligence, or a related field, or equivalent experience.
U.S. citizenship and the ability to obtain a U.S. 6C Security Clearance.
At least 2 years of experience in machine learning engineering, AI engineering, software engineering, or related roles.
Demonstrated experience building multi-step agentic systems with large language models, including tool calling and orchestration.
Hands-on experience evaluating LLM and agent systems through evaluation-set design and result interpretation.
Experience deploying and supporting AI or machine learning systems in production environments.
Experience with retrieval-augmented generation and other methods for grounding models in enterprise data.
Strong Python programming skills and working knowledge of AWS AI services, agent frameworks, Terraform, Docker, and Kubernetes.
Strong machine learning fundamentals, statistical reasoning, analytical problem-solving, communication, organization, and ability to lead end-to-end product development.

Hybrid work environment with a standard 24/16 in-office/work-from-home schedule for associates within 30 miles of an office, subject to manager discretion.
Medical, dental, vision, HSA and FSA benefits, earned time off, 401(k) and student loan repayment, life and AD&D insurance, employee assistance, employee stock purchase, tuition reimbursement, incentive pay, disability coverage, and wellness programming.
The role is currently unavailable to external candidates residing in Alabama, California, Connecticut, Hawaii, Illinois, Maine, Massachusetts, Michigan, New Jersey, New York, Oregon, Rhode Island, Vermont, or Washington.

51-200 employees