What are the responsibilities and job description for the Associate, AI Product Strategy & Operations position at Brightstar.ai?
The Opportunity: Learn to Drive AI at the Intersection of Tech & Finance
- At Brightstar.AI, Associates under the CAIO are apprentice product leaders. You will work directly with AI Product Managers and Engineers on high-stakes transformation projects inside portfolio companies — building AI systems that create millions in EBITDA uplift and measurable ROI.
- This role is designed for early-career professionals (3–5 years) with a mix of technical grounding, exposure to AI/ML, and experience in private equity, venture capital, or consulting environments. Associates are expected to learn fast, contribute immediately, and grow into full Product Manager or Engineer roles within 24 months.
- Support Product Strategy: Assist in building AI product roadmaps, business cases, and financial models.
- Contribute to AI Builds: Work with engineers to define requirements, test prototypes, and support deployments.
- Bridge Business & Tech: Translate business challenges into structured product requirements and user stories.
- Analyze Impact: Track performance of deployed AI systems and link results directly to P&L impact.
- Shadow & Learn: Work alongside senior Product Managers and Engineers to learn full-lifecycle product delivery.
- Stakeholder Support: Participate in C-suite workshops, capturing insights and translating them into action items.
- 2–5 years in consulting, product, investment, or engineering roles.
- Exposure to AI/ML concepts (LLMs, RAG, predictive analytics) and business applications.
- Strong financial literacy (ROI, P&L, EBITDA) with the ability to build Excel or SQL-based models.
- Experience with digital product workflows (agile sprints, user stories, testing).
- Strong communication skills, especially for translating complex technical topics into business terms.
- Background in private equity, VC, or digital transformation consulting.
- Hands-on coding or scripting ability (Python preferred).
- Familiarity with cloud/ML platforms (AWS Sagemaker, Azure ML, Databricks).
- MBA or MS in a technical field is a plus.