Sr. Product Manager

TEKsystems•Raleigh, NC

5d•Hybrid

About The Position

We are hiring a hands‑on Senior Product Manager to lead an AI‑driven competitive intelligence and conversational search offering. This product is designed to go deeper and be more analytical than general‑purpose chat tools—delivering timely, defensible competitive insights powered by structured data, knowledge graphs, and modern AI workflows. You will own end‑to‑end product strategy and execution, from quarterly planning and metrics to shipping production features. The role requires strong commercial instincts, comfort working alongside highly technical teams, and the ability to translate complex AI concepts into clear, business‑ready narratives.

Requirements

7+ years of product management or product ownership experience.
3+ years leading AI, ML, NLP, search, or knowledge‑graph‑based products.
Proven experience spearheading AI or agentic AI product initiatives.
Strong commercial instincts with experience articulating product value to customers and internal stakeholders.
Hands‑on familiarity with LLMs (e.g., Claude, Gemini), embeddings, NLP pipelines, retrieval/search systems, and agentic workflows.
Strong API experience integrating modern AI products with legacy platforms.
Experience operating in quarterly planning cycles using OKRs, KPIs, and experiment roadmaps.
Ability to simplify technical complexity into executive‑ready, customer‑friendly narratives.

Nice To Haves

Experience with Apache Solr or other vector‑based search platforms.
Background in conversational AI UX, knowledge‑graph architectures, or AI data pipelines.
Familiarity with strategies to mitigate commercial data latency via extraction and enrichment.
Experience supporting professional or financial services users, especially M&A or competitive intelligence use cases.

Responsibilities

Own the product strategy and roadmap for an AI/agentic, NLP‑based competitive benchmarking product, including quarterly planning, OKRs, and outcome‑focused metrics.
Lead data extraction and knowledge‑graph creation (top priority), transforming company data, people data, event‑based signals, and open‑web sources into rationalized, factual, LLM‑ready datasets.
Deliver a conversational search experience using embeddings (e.g., vector search with Boolean support); iterate toward tailored competitive benchmarking queries and workflows.
Build SaaS‑based AI capabilities on modern cloud architecture, integrating with an existing product portfolio through connectors and APIs rather than rebuilding legacy systems.
Translate complex technical concepts (LLMs, NLP, embeddings, knowledge graphs, agentic workflows) into clear value propositions, go‑to‑market narratives, and customer outcomes.
Partner with a former data scientist on the team to define data requirements, evaluation frameworks, and AI model choices (initially operating on Claude 4.5, with evaluation of Gemini or alternatives).
Run discovery and validation with professional and financial services users (including M&A teams) to surface actionable competitive insights.
Drive execution across engineering, data, design, and GTM—setting the pace, removing blockers, and holding teams accountable to measurable outcomes.
Evangelize and “sell the story,” partnering with sales and customer success to clearly articulate and land product value.