aimlroles

AI Engineer, AI Platform

Kharon kharon.com Open · verified Oct 22, 2026
Hybrid Denver Full-time Mid-level ML Platform & Ops

At a glance

Mid-level ML Platform & Ops role at Kharon. Denver · full-time · no salary stated · we estimate $144,980–$225,625 across the United States.

Estimated pay

Kharon has not published a salary for this role. The figure below is our estimate, not theirs.

$144,980 – $225,625
What the middle half of mid-level ML platform & ops roles in the United States paid, among postings that did state a salary.
Worked out from 132 postings that stated pay, median $191,000. Last updated Oct 22, 2026.
RoleML Platform & Ops
SeniorityMid-level
LocationDenver
WorkplaceHybrid
EmploymentFull-time
PostedSep 8, 2026 · 6w ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build AI proofs of concept quickly, then test them with users and improve the models and interfaces
  • Move AI features from initial design into production by shaping data flows, coding, packaging services, and deploying to secure cloud environments
  • Create production data pipelines and internal development tools, including CI/CD scripts, evaluation systems, dashboards, and secure sandboxes
  • Work with product, design, engineering, and data science colleagues to turn business needs into scalable AI systems
  • Monitor AI systems for explainability and alignment with ethical, regulatory, and performance standards

What you bring

  • At least four years in software engineering or machine learning, focused on applied AI
  • Strong Python development skills and experience with AI libraries or agent frameworks
  • Hands-on familiarity with production AI systems, including RAG, memory, MCP servers, and model tradeoffs
  • Experience with containers and cloud deployment, with AWS preferred

Who this fits

This role suits a mid-level engineer who can ship production AI systems through rapid development cycles and work across product and technical teams. You’ll need to work from the Denver office at least three days each week.

From the employer

TL;DR Kharon is seeking a full-time AI Engineer based in Denver. This role requires in-office attendance at least 3 days a week.
  • Design, develop, and ship proof-of-concept AI applications within days or weeks. Work in fast, agile cycles to test ideas, gather feedback, and refine models and interfaces.
  • Build and integrate advanced AI components, including Model Context Protocol clients and servers, foundation model fine-tuning, and multi-agent orchestration frameworks (eg. Claude Agent SDK, LangChain, AutoGPTI)
  • Take features from idea to production, including architecting data flows, writing high-quality code, containerizing services, and deploying them in secure cloud environments (e.g., AWS).
  • Partner closely with product managers, designers, engineers, and data scientists to translate abstract business problems into concrete, scalable AI systems.
  • Develop production-grade data pipelines integrating data to/from AI systems.
  • Develop and maintain internal tools to speed up development cycles, CI/CD scripts, evaluation harnesses, dashboards, and secure sandbox environments.
  • Ensure AI systems are monitored, explainable, and aligned with ethical, regulatory, and performance standards.
  • Stay at the forefront of AI/ML advancements, evaluate open-source frameworks, and share best practices across the team.
  • Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Engineering, or a related field preferred.
  • 4+ years of software engineering or machine learning experience, with a focus on applied AI.
  • Strong software development skills in Python and experience with libraries like Langchain/Langgraph, Agent SDKs, Pydantic, SQLAlchemy/Alembic, PySpark/Polars/Pandas.
  • Experience with tracing systems (MLFlow, Sentry), RAG Systems, Memory Systems, MCP Servers, Agent Skills, and knowledge of different models and tradeoffs.
  • Strong understanding of how to make use of AI tools for rapid development (Cursor, Claude Code, etc)
  • Familiarity with containerization (Docker), cloud deployment (AWS preferred, Github Actions)
  • Demonstrated ability to ship high-quality, production-ready ML/AI systems under tight iteration cycles.
  • Passion for solving complex problems with real-world impact, especially in high-stakes or regulated domains.
  • Excellent communication skills and the ability to thrive in cross-functional, mission-driven environments.