Director, AI Engineering

This is not a traditional Director of Engineering role. You will not be managing teams at a distance or overseeing narrow R&D projects. As Director, AI Engineering, you are a senior technical leader at the forefront of private equity–backed transformation.

You will collaborate directly with Brightstar’s portfolio companies to lead high-stakes AI interventions—partnering with executives, building cross-functional pods, and ensuring delivery of production-grade AI systems that create measurable enterprise value. You will architect the strategy and technical roadmap, lead engineering execution, and mentor the next generation of AI engineers.

Your success will be measured not by activity, but by tangible P&L impact—EBITDA uplift, margin expansion, operational efficiency, and sustained competitive advantage. This is a rare opportunity for a transformational builder who can both lead from the front and scale from the center.

Lead Enterprise-Grade AI Engineering

• Architect and oversee the design, build, and deployment of scalable AI systems (e.g., RAG systems, agentic AI, predictive models, fine-tuned LLMs) that solve mission-critical challenges.

• Ensure systems are stable, secure, maintainable, and ready for enterprise-grade adoption.

Direct AI Interventions

• Serve as the technical lead for multiple initiatives within portfolio companies, translating strategic objectives into measurable use cases and robust engineering solutions.

• Reimagine workflows from first principles to embed AI as the digital backbone of operations.

Build and Scale Pods

• Stand up and mentor cross-functional pods (engineers, data scientists, SMEs, designers) that are aligned to Hero Missions and accountable for business KPIs.

• Ensure pods follow agile rhythms, own end-to-end outcomes, and operate with embedded governance.

Partner with C-Suite & Investment Teams

• Engage directly with portfolio company CEOs, CIOs, and operating executives to align on strategy, size-of-prize, and technical execution.

• Collaborate with Brightstar’s investment professionals to track ROI and ensure interventions deliver sustainable value.

Institutionalize AI Engineering Excellence

• Capture lessons learned from deployments and translate them into reusable best practices, frameworks, and playbooks that can be applied across companies.

• Evaluate and introduce emerging technologies, tools, and vendors to ensure companies stay at the frontier of AI innovation.

• Drive knowledge sharing and talent development, building AI fluency across engineering teams, business leaders, and operators to ensure adoption is sustainable.

10–15+ years of software engineering / ML experience, with a track record of building and deploying production AI systems at scale.

Deep technical expertise in system design, data pipelines, cloud infrastructure (AWS/GCP/Azure), and containerization (Docker, Kubernetes).

Hands-on experience with AI/ML systems: building RAG frameworks, deploying agentic AI, fine-tuning LLMs, reinforcement learning loops, and integrating with enterprise systems.

Proven ability to lead technical teams and manage complex projects across multiple stakeholders.

Strong business acumen: able to translate engineering decisions into financial outcomes and communicate effectively with executives and investors.

Exceptional communication skills, with the ability to influence at the boardroom level while still diving into the technical trenches.

Experience as a forward-deployed technical leader (e.g., Solutions Architect, Engineering Director, CTO in a transformation context).

Background in private equity, venture capital, or high-growth startups, where speed and value creation are paramount.

Experience with AI governance, compliance, and risk frameworks.

Advanced degree in Computer Science, Engineering, or a related field.