AI & Data Platform Engineering Manager

Sierra Nevada Corporation is a global leader in aerospace and national security, providing technologies and solutions for critical security needs. The AI & Data Platform Engineering Manager leads AI/LLM Platform and MLOps teams, provides technical oversight for generative AI architectures and enterprise integrations, and drives platform strategy, compliance, resourcing, and delivery.

Responsibilities:

• Lead the AI/LLM Platform and MLOps engineering team delivering the enterprise AI platform
• Provide deep 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 capability into enterprise systems and business platforms
• Establish strong 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 long-term technical roadmap for the platform
• Lead multi-team engineering operations in a hybrid environment
• Participate in integration events, customer reviews, and working groups
• Travel up to 20% for program execution and external coordination
• Provide technical escalation support for complex ML challenges

Requirements:

• Bachelor's degree in computer science, mathematics, statistics, engineering, or related STEM field
• 6-8+ years of experience in AI/ML or software engineering, including 2+ years in a management role
• Relevant experience can be considered as a substitute for the required educational qualifications
• In the absence of a degree, a minimum of 13 years of related experience is required
• Higher level relevant degree may substitute for experience
• Demonstrated success leading engineering teams and delivering complex technical programs
• Expertise in generative AI/LLM techniques; 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 (CMMC, data classification)
• Ability to drive cross-functional execution across software, data, and business platform teams
• AWS Machine Learning Specialty, Google Professional ML Engineer, or 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
• Travel up to 20% for program execution and external coordination
• To conform to U.S. Government international trade regulations, applicant must be a U.S. Citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State or U.S. Department of Commerce
• Degree in AI/ML, data science, engineering, or related discipline
• AWS Solutions Architect (Associate or Professional) or Azure Solutions Architect Expert
• Databricks ML Professional, Snowflake SnowPro, or comparable data engineering certifications
• Advanced Generative AI or MLOps certifications (DeepLearning.AI, 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