Technical Product Manager

Key Requirements 1. Applied AI Product Management • LLM applications • Retrieval-Augmented Generation (RAG) • AI agents • Model evaluations • Feedback loops • Prompt and workflow iteration • Model trade-off analysis • Responsible human-in-the-loop product design 2. Technical Prototyping & Data Fluency • Python • SQL • Notebooks • Figma • Data exploration • Workflow mockups • API concepts • Analytics • Lightweight prototypes that help clarify product direction 3. Enterprise Delivery & Production Systems • Product roadmaps • Release planning • Pilot-to-production transitions • Integration-heavy environments • Adoption metrics • Documentation • Support models • Operational readiness 4. eGRC Product Experience (Strong Preference) • Enterprise GRC (eGRC) products • Risk and control management • Compliance workflows • Evidence collection • Policy management • Audit readiness • Issue remediation • Third-party risk • Reporting • Workflow design for regulated organizations 5. Cybersecurity & Sensitive Environments (Preferred) • Cybersecurity • Security operations • Identity & Access Management (IAM) • Audit logging • Data classification • On-premises deployments • Air-gapped systems • Regulated data environments Show more Show less

1. Applied AI Product Management: LLM applications, Retrieval-Augmented Generation (RAG), AI agents, model evaluations, feedback loops, prompt and workflow iteration, model trade-off analysis, responsible human-in-the-loop product design. 2. Technical Prototyping & Data Fluency: Python, SQL, notebooks, Figma, data exploration, workflow mockups, API concepts, analytics, lightweight prototypes that help clarify product direction. 3. Enterprise Delivery & Production Systems: product roadmaps, release planning, pilot-to-production transitions, integration-heavy environments, adoption metrics, documentation, support models, operational readiness. 4. eGRC Product Experience (Strong Preference): enterprise GRC (eGRC) products, risk and control management, compliance workflows, evidence collection, policy management, audit readiness, issue remediation, third-party risk, reporting, workflow design for regulated organizations. 5. Cybersecurity & Sensitive Environments (Preferred): cybersecurity, security operations, IAM, audit logging, data classification, on-premises deployments, air-gapped systems, regulated data environments.

Own and drive AI-enabled enterprise product initiatives from concept to production. Develop and maintain product roadmaps and release plans for eGRC and cybersecurity-focused solutions. Lead pilot-to-production transitions in integration-heavy environments, define adoption metrics, and ensure documentation and support models are in place. Design workflows and experiences for regulated organizations, with emphasis on evidence collection, policy management, and audit readiness.