Director, AI Engineering

Role Summary

• 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.

What You'll Do

• 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.

What You'll Need

• 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.

Nice-to-Haves

• 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.