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# AI / LLM Platform Engineer

- **Company:** SNC LTD
- **Location:** Denver, CO, United States
- **Experience:** Starter
- **Salary:** $52,000.0 - $85,280.0
- **Contract:** Permanent contract
- **Skills:** Adobe InDesign, Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Data Analysis, Computer Vision, Microsoft Azure, Cloud Computing, Configuration Management, Cyber Security, Software Debugging, DevOps, Federal Information Processing Standards (FIPS), Python (Programming Language), Machine Learning, OpenAI, TypeScript, Management of Software Versions, AI Infrastructure, Enterprise Software Applications, Performance Testing, Large Language Models, Prompt Engineering, Llamaindex, Generative AI, Agentic-AI, Containerization, Kubernetes, Information Technology, Machine Learning Operations, Api Design, GPT, Docker
- **Published:** October 13, 2026
- **Apply:** https://www.builtincolorado.com/job/ai-llm-platform-engineer/11623888?handler=ApplyRedirect

## About the Role

* Bachelor's degree in computer science, mathematics, applied statistics, various engineering disciplines, or related STEM discipline
 * 2+ years of experience in a related field.
 * Relevant experience can be considered as a substitute for the required educational qualifications. In the absence of a degree, a minimum of 6 years of related experience is required.
 * Higher level relevant degree may substitute for experience.
 * Practical experience building and operating APIs at scale in a cloud environment (AWS, Azure, or GCP).
 * Hands-on experience integrating with at least one major LLM provider (OpenAI, Anthropic, Cohere, Mistral, etc.). Assisted with deploying software services into production environments.
 * Proficiency in Python and at least one additional language (TypeScript or Go preferred).
 * Familiarity with containerization (Docker, Kubernetes) and GitOps workflows., * Degree in Computer Science or related field. Experience with generative AI models and transformer-based LLM architectures.
 * Working knowledge of Agile or DevOps practices in software/ML project environments.
 * Exposure to LLM orchestration frameworks such as LangChain or LlamaIndex.
 * Experience with prompt engineering and evaluation frameworks.
 * Familiarity with cost optimization and FinOps practices for cloud or API-based platforms.
 * Familiarity with CMMC or FedRAMP compliance requirements.
 * Experience with MLflow or similar experiment tracking tools.

Essential Functions:

 * Work extensively on a computer for coding, debugging, and integrating AI/ML systems.
 * Travel occasionally to testing sites, customer locations, or conferences (up to 10-20%).
 * Ability to work in a hybrid environment and manage multiple tasks effectively.

## Description

Develop and operate enterprise LLM platform services, including gateways, model routing, workflow orchestration, integrations, prompt evaluation, and AI agent deployments. Optimize reliability, cost, scalability, and model performance while testing changes, troubleshooting systems, documenting designs, and supporting compliance. Collaborate with AI, software, and platform teams, monitor SLOs, and participate in on-call support.
The summary above was generated by AI

The AI/ML Engineer II is a mid-level position for individuals with professional experience in designing and implementing machine learning algorithms. In this role, you will independently develop and deploy AI/ML solutions to address complex challenges, such as autonomous systems, predictive maintenance, and computer vision. You will take ownership of specific projects, perform data analysis, and optimize models for performance and scalability. This position requires a combination of technical expertise, problem-solving skills, and the ability to collaborate with multidisciplinary teams to meet mission-critical objectives.

As SNC's corporate team, we provide the company and its business areas with strategic direction and business support spanning executive management, finance and accounting, operations, human resources, legal, IT, information security, facilities, marketing, and communications., * Design, implement, and optimize platform services such as the LLM gateway, model routing, and workflow orchestration systems.

 * Develop and maintain integrations that connect LLMs to enterprise systems, data sources, and APIs. Identify gaps in platform capability and propose solutions.
 * Conduct performance testing and validation of platform services, including prompt evaluation frameworks. Optimize for reliability, cost, and scalability.
 * Write and deploy efficient, modular code to integrate LLMs and AI agents into enterprise systems, ensuring reliability and compatibility with existing platforms.
 * Test platform changes in staging environments to evaluate performance under real-world load. Contribute to system-level debugging and troubleshooting.
 * Collaborate with the Forward Deployed AI team, software developers, and platform architects to align platform capability with business and enterprise requirements"* Keep: "Document technical designs, workflows, and testing procedures for internal and external use. Share findings and best practices with team members.
 * Document technical designs, workflows, and testing procedures for internal and external use. Share findings and best practices with team members.
 * Explore and integrate emerging LLM providers, agent frameworks, and orchestration tools to enhance platform capabilities.
 * Monitor model performance, cost, and usage; continuously optimize routing logic to balance capability vs. spend
 * Execute validation procedures and support platform compliance with CMMC, FIPS, and SNC security policy requirements.
 * Implement prompt management, versioning, and evaluation frameworks to ensure AI output quality and reliability
 * Maintain platform SLOs and participate in on-call rotation for AI infrastructure., Investigates supplier and customer nonconformances, validates supplier responsibility, coordinates root-cause and corrective actions, contains defective products, performs conformity checks, and pursues Material Review Board approval. The role requires manufacturing and quality engineering experience, blueprint and drawing interpretation, inspection expertise, SAP/MES proficiency, and the ability to work in demanding aircraft production environments.
Top Skills: 2D ModelingAccessApqpAsp.NetCatiaClassic AspDaxExcelHTMLLeanM-CodeMesMicrosoft Office 365Model-Based Definition (Mbd)Power AutomatePower BISAPSix SigmaSQLVBA
Boeing, Performs quality inspections for composite fuselage, propulsion, and aircraft systems fabrication and assembly. Interprets drawings, specifications, and inspection procedures; operates testing and precision measurement equipment; records results; verifies tool qualifications; accepts or rejects parts and assemblies; maintains quality records and certifications; and coordinates with internal teams and customers. The role requires shift flexibility, comfort working in tight aircraft spaces, computer proficiency, and the ability to cross-train across manufacturing disciplines.
Top Skills: Dit-McoHirfExcelMicrosoft WordPhotogrammetryPrecision Measuring InstrumentsQuality Management SystemsSAPSkydrol

What you need to know about the Colorado Tech Scene

With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.

Key Facts About Colorado Tech

 * Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
 * Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
 * Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
 * Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
 * Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
 * Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute