Sr. AI Product Manager

TEKsystems•Raleigh, NC

1d•$65 - $70•Hybrid

About The Position

We are hiring a hands-on Senior Product Manager to lead an AI-driven competitive intelligence and conversational search offering that goes deeper and is more thoughtful than general-purpose chat products. You’ll own strategy and execution—from quarterly planning and metrics to shipping features that extract event services, create derivative datasets, and assemble them into a usable knowledge graph. This role demands commercial instincts (you’ve sold/marketed or articulated product value before), the ability to push and align cross-functional teams, and comfort translating highly technical concepts into crisp, business-ready narratives.

Requirements

5–8+ years in product management with at least 3+ leading AI/ML/NLP or search/knowledge-graph products.
Proven commercial instinct: you’ve sold/marketed or clearly articulated product value and outcomes to customers and internal stakeholders.
Strong experience driving teams and shipping; you set clear goals, push for results, and foster collaboration.
Hands-on familiarity with LLMs (Claude, Gemini), embeddings, NLP, retrieval/search (e.g., vector + Boolean), and agentic patterns/workflows.
Comfortable planning by quarterly cycles with metrics that drive product work (OKRs, KPIs, experiment roadmaps).
Ability to simplify technical concepts into executive-ready narratives, PRDs, and customer-facing content.
Team player, highly impactful; skilled at triangulating company & people data to generate insights.
Experience with professional/financial services users, especially M&A and competitor landscape analysis.

Responsibilities

Own the product strategy & roadmap for an AI/agentic, NLP-based competitive benchmarking product, including quarterly planning cycles, OKRs, and outcome-focused metrics.
Lead data extraction & knowledge graph creation (priority): turn company and people data, event-based signals, and open-web sources into rationalized, factual LLM-ready datasets.
Deliver a conversational search experience leveraging embeddings (e.g., Solr) and Boolean search; iterate toward more tailored competitive benchmarking queries and workflows.
Build SaaS AI capabilities on modern architecture—link to legacy portfolio via connectors & APIs rather than rebuilding into legacy products; drive joint ecosystem integrations.
Translate complex technical concepts (NLP, embeddings, knowledge graphs, LLM orchestration, agentic patterns) into clear value propositions, GTM narratives, and customer outcomes.
Partner with an ex–data scientist on the team (you don’t need to be a data scientist) to define data requirements, evaluation frameworks, and model choices (e.g., Claude 4.5, potential switch to Gemini).
Run discovery and validation with professional & financial services users (incl. M&A teams), triangulating company and people data to surface competitive insights.
Drive execution across engineering, data, design, and GTM; set pace, remove blockers, and hold teams to measurable outcomes.
Evangelize and sell the story—you’ve previously marketed or articulated product value and can partner with sales/CS to land the value with customers.