Product Manager

As Senior AI Solutions Product Manager you’ll own product strategy and delivery across internal transformation and a growing external AI revenue practice. You’ll lead discovery, design pragmatic tool + custom solutions, enable Business Development with demos/prototypes and pricing, and drive delivery across blended teams. This is a player‑coach role — hands‑on, commercially minded, and technically fluent.

• AI strategy & roadmaps
  : own multi-horizon AI/ML roadmaps that balance internal capability-building with revenue-generating client solutions; prioritize product bets by measurable outcomes (efficiency, adoption, revenue).
• Trend & vendor intelligence
  : continuously evaluate models, vendors, and tools (e.g., OpenAI, Anthropic/Claude, Hugging Face); maintain a technology/vendor watchlist and recommend PoCs.
• Discovery & solution design
  : run structured discovery with technical and non‑technical stakeholders; map workflows, data sources, business rules, and success criteria; translate findings into requirements, acceptance criteria, and phased delivery plans.
• Productize & price
  : design pragmatic solutions combining off‑the‑shelf AI, workflow automation, integrations, and custom development; convert successful client engagements into templated, repeatable offerings; define pricing and packaging (retainer, project, usage, outcome‑based) and pilot commercial terms.
• Sales enablement & prototyping
  : partner with Business Development on pitch narratives, demo flows, quick‑turn prototypes, workshops, and executive presentations to convert pilots into repeatable engagements; co‑own pipeline contribution and help shape the AI service portfolio.
• Partner & channel development
  : identify, activate, and manage strategic partners — including training providers, MSPs, and technology resellers — that extend BERPL’s AI reach and accelerate client acquisition.
• Delivery leadership
  : lead blended onshore/offshore teams (engineers, data scientists, automation specialists, BAs) through discovery → build → onboarding → iteration using agile tooling (Azure Dev Ops, Jira, or equivalent); manage a growing portfolio of concurrent client engagements with disciplined prioritization.
• Production readiness & governance
  : define MLOps/monitoring, retraining/rollback plans, observability, documentation, and responsible‑AI practices; account for privacy/compliance (FERPA/COPPA/vendor risk) as applicable.

• 5+ years product management, solution ownership, or technology delivery experience.
• 2+ years delivering AI/ML, automation, data, or analytics products/solutions (or equivalent hands‑on projects).
• Demonstrated success running discovery with mixed‑technical audiences and delivering prototypes/demos that supported sales or operational decisions.
• Strong technical fluency across the modern AI stack: LLMs/prompting, embeddings/vector search, RAG architectures, and MLOps fundamentals; practical knowledge of leading model families (OpenAI GPT, Anthropic Claude, Google Gemini, Llama, Mistral) and the ability to recommend the right model for cost, latency, accuracy, and compliance requirements.
• Proven ability to define scope, requirements, acceptance criteria, and success metrics tied to measurable business outcomes.
• Experience co‑owning or directly influencing revenue outcomes — not just supporting sales, but shaping what gets sold, how it’s priced, and whether it scales.
• Demonstrated ability to productize services — taking a successful client engagement and turning it into a repeatable, packageable offering.
• Excellent executive communication and consultative sales skills.
• Genuine alignment with a values‑driven, employee‑owned culture where accountability, relationships, and long‑term thinking matter.

• At least two industry‑recognized AI or delivery certifications or equivalent hands‑on experience (examples below).
• Experience leading blended onshore/offshore teams and using Azure Dev Ops/Jira.
• Experience managing a portfolio of concurrent client engagements across multiple accounts or work streams.
• Practical familiarity with workflow automation platforms (Power Automate, n8n, Make), Microsoft Copilot/Power Platform, vector DBs and RAG frameworks.
• Experience building or activating partner channels — resellers, training partners, MSPs, or technology alliances.
• Experience defining pricing/packaging and supporting proposal development.