AI & Data Platform Engineering Manager

Sierra Nevada Corporation•Lone Tree, CO

2d•$199,250 - $273,969•Hybrid

About The Position

The AI & Data Platform Engineering Manager leads the AI/LLM Platform and MLOps engineering team responsible for delivering an enterprise AI platform. The role provides technical direction for LLM and generative AI architectures, including LLM gateways, model routing, and agent/workflow orchestration, and oversees integration of ML models and AI capabilities into enterprise systems and business platforms. The manager establishes validation, verification, and compliance processes; manages resources, budgets, schedules, and risks; mentors senior engineers and technical leads; and owns the platform’s long-term technical roadmap. The position leads multi-team engineering operations in a hybrid environment, participates in integration events, customer reviews, and working groups, provides technical escalation support for complex ML challenges, and may require travel up to 20%.

Requirements

Bachelor’s degree in computer science, mathematics, statistics, engineering, or a related STEM field; relevant experience may substitute for education, with at least 13 years of related experience required in the absence of a degree. A higher-level relevant degree may substitute for experience.
6–8+ years of experience in AI/ML or software engineering, including 2+ years in a management role.
Demonstrated success leading engineering teams and delivering complex technical programs.
Expertise in generative AI/LLM techniques and familiarity with supervised and unsupervised ML for data platform use cases.
Experience architecting and optimizing ML pipelines and high-performance systems.
Strong understanding of security, compliance, and data governance requirements, including CMMC and data classification.
Ability to drive cross-functional execution across software, data, and business platform teams.
AWS Machine Learning Specialty, Google Professional ML Engineer, Azure AI Engineer Associate, or equivalent hands-on experience with a major cloud AI/ML platform.
CMMC/NIST SP 800-171 awareness or equivalent compliance training.
Applicant must be a U.S. citizen, lawful permanent resident, protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain required authorizations from the U.S. Department of State or U.S. Department of Commerce.

Nice To Haves

Degree in AI/ML, data science, engineering, or a related discipline.
AWS Solutions Architect (Associate or Professional) or Azure Solutions Architect Expert certification.
Databricks ML Professional, Snowflake SnowPro, or comparable data engineering certification.
Advanced Generative AI or MLOps certification, such as DeepLearning.AI or NVIDIA DLI.
Experience with LLM gateways, vector databases, agent orchestration frameworks, or prompt evaluation tooling.
Experience building or operating an internal LLM gateway, model routing layer, or enterprise AI API platform.

Responsibilities

Lead the AI/LLM Platform and MLOps engineering team delivering the enterprise AI platform.
Provide technical guidance on LLM and generative AI architectures, including the LLM gateway, model routing, and agent/workflow orchestration.
Oversee integration of ML models and AI capabilities into enterprise systems and business platforms.
Establish validation, verification, and compliance processes.
Manage resourcing, budgeting, schedules, and risk mitigation.
Mentor senior engineers and technical leads.
Drive AI/LLM platform capability development and own the platform’s long-term technical roadmap.
Lead multi-team engineering operations in a hybrid environment.
Participate in integration events, customer reviews, and working groups.
Provide technical escalation support for complex ML challenges.
Travel up to 20% for program execution and external coordination.