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BENCH+ PROFILE

Vadim

Technical Product Manager
AI, analytics, automation, and developer-tooling product delivery

Senior technical product profile with a strong fit for AI-enabled B2B products, analytics platforms, automation workflows, and developer-facing initiatives that require discovery, roadmap ownership, stakeholder alignment, and prototype-to-MVP delivery.

BEST-FIT USE CASE

Technical product ownership for AI-assisted automation, analytics, API/SDK, or internal developer-tooling products where the role bridges business discovery, engineering collaboration, user research, backlog shaping, and measurable rollout planning.

Not the primary fit: Pure software implementation, pure people management, production MLOps ownership, or deep platform infrastructure roles would be less aligned than technical product and product-led automation work.

EVIDENCE HIGHLIGHTS

What supports the assessment

01

Established product processes for an AI and developer-tooling startup as the sole product manager, combining discovery with hands-on automation prototyping.

02

Built an internal documentation and reporting automation workflow using MCP and RAG to analyze codebase activity and generate operational outputs.

03

Built a competitive monitoring and reporting workflow for marketing and leadership stakeholders.

04

Led discovery for API, SDK, and no-code AI platform concepts, including user interviews and user-story preparation.

05

Built and led a product function from the ground up for an early-stage AI product and launched it to first users.

06

Owned roadmap and product scope for a portfolio of enterprise analytics and reporting products.

07

Managed deployment and expansion of an enterprise analytics platform for an energy-sector client.

08

Earlier engineering work included automation tools for calculation, data processing, and stress-analysis workflows.

WORKING STYLE

How they show up

  • Structures product work from business problem to technical framing, prototype, validation, rollout, and user enablement.
  • Chooses solo prototyping for fast exploration and brings in specialists when the task requires deeper expertise.
  • Uses LLMs for brainstorming, research, solution comparison, prototyping, feature development, and tool-enabled workflows.
  • Discusses technical choices in terms of maintainability, total cost, team capability, scalability, integrations, and lifecycle constraints.