Director, AI & ML Engineering

Location: Broomfield

We will be accepting applications through April 5, 2026 or until filled.

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- Gogo, a leading satellite connectivity reseller, is seeking a Director of AI & ML Engineering to lead the engineering, delivery, and operationalization of AI/ML capabilities across our software products and internal platforms. This role will build and mentor a high-performing AI/ML engineering team and partner closely with Product, Operations, Support, Sales, IT, Security, and Data to identify and deliver practical AI/ML solutions that improve business efficiency, enhance customer experience, and increase the value of our core products.

The ideal candidate is a hands-on technical leader who understands how to take AI/ML initiatives from opportunity discovery through production deployment and long-term lifecycle ownership (monitoring, retraining, governance, and cost/performance optimization).

COME ON BOARD THE GOGO SAAS ENGINEERING TEAM!


How will you make a difference?

• Execute the company's AI strategy, aligning with Gogo's business objectives and the evolving needs of the satellite connectivity industry
• Lead the design, build, and deployment of AI/ML solutions that improve customer experience and operational outcomes, including areas such as network/service insights, predictive maintenance, anomaly detection, support automation, and sales enablement
• Own the end-to-end delivery lifecycle for AI/ML initiatives: problem framing, data readiness, experimentation, production-ization, monitoring, and continuous improvement
• Partner with Product to translate business goals into actionable AI/ML roadmaps and measurable outcomes tied to customer and operational value
• Establish and mature ML Ops and LLM Ops practices: model versioning, CI/CD, evaluation, monitoring, drift detection, retraining workflows, and production support
• Define engineering standards for AI/ML systems including quality, reliability, security, latency, cost-to-serve, and scalability
• Collaborate with platform and data teams to ensure strong foundations for data pipelines, feature management, and model-ready datasets
• Work with cross-functional stakeholders (Product, Operations, Support, Sales, IT, Security, Legal/Compliance) to identify high-value AI/ML opportunities and integrate solutions into business workflows and customer-facing experiences
• Ensure AI/ML capabilities are delivered as durable product features and operational tools.
• Communicate plans, tradeoffs, progress, and outcomes clearly to both technical and non-technical audiences
• Establish best practices for data governance, privacy, security, and responsible AI usage, ensuring compliance with internal policies and applicable regulations

• Implement guardrails and review processes for model risk, bias, explainability (where needed), and appropriate use of customer and operational data
• Build, lead, and develop a team of AI/ML engineers and applied scientists; set expectations, coach performance, and foster a culture of execution and continuous learning
• Manage vendor relationships and partnerships related to AI/ML platforms, tooling, and services
• Support budgeting and capacity planning for AI/ML programs and platform investments.

Qualifications

• Bachelor's Degree in Computer Science
  , Engineering
  , Data Science
  , or related field (Master's preferred)
• 10+ years of engineering experience with 6+ years delivering ML/AI solutions
• 3+ years in a technical leadership role

Required Skills, Talents, & Experience

• Demonstrated success taking AI/ML systems into production and owning operational performance (monitoring, reliability, retraining, cost)
• Strong experience with modern ML tooling and frameworks (e.g.,
  Py Torch ,
  Tensor Flow
  ) and cloud-based AI services (
  Azure
  , AWS
  , or GCP
  )
• Proven ability to lead cross-functional execution and communicate effectively with engineering, product, and business stakeholders
• Strong understanding of data privacy
  , security
  , and governance practices in production systems
• Experience delivering AI/ML capabilities in connectivity, telecommunications, aviation, or other high-reliability industries
• Familiarity with RAG
  , LLM
  integration
  , and evaluation practices for AI assistants and automation use cases
• Experi…