Senior Technical Product Manager

Responsibilities

• As a Senior Technical Product Manager for the Data Platform, you will have the following responsibilities:
• Define and Execute Roadamp: Own the product roadmap for transitioning legacy data architectures into an "agent-native" intelligence layer. Lead the normalization of disparate data sources into standardized data models optimized for LLM querying.
• Drive Protocol Standardization: Champion the adoption of standardized communication protocols, such as the Model Context Protocol (MCP), to seamlessly bridge the gap between AI models and enterprise data sources.
• Establish Evaluation Flywheels: Define and obsess over metrics that reflect the probabilistic nature of AI. Track system performance (e.g., tail latency, throughput), intelligence quality (e.g., Precision, Recall, hallucination rates), and business impact.
• Build the Trust Posture: Implement robust data governance, role-based access controls (RBAC), and observability to ensure autonomous agents operate securely and transparently without compromising enterprise trust.
• Partner Cross-Functionally: Collaborate closely with engineering, data science, and UX teams in an agile environment, acting as a credible technical partner to dive into the details of model training, validation, and shipment.

Requirements

• 4+ years of Technical Product Management experience , with a proven track record of taking zero-to-one products from inception to launch in fast-moving, competitive spaces.
• Big Data & Cloud Native Infrastructure: Professional experience in big data environments, distributed systems, and cloud-native databases.
• AI Fluency: Deep, hands-on understanding of Large Language Models (LLMs), prompt engineering, vector embeddings, and multimodal processing. You use AI daily to accelerate your own work.
• Data Modeling & Management: Expertise in data governance, data catalogs, and access management. Strong Python and SQL skills to prototype prompts and analyze product usage data.
• Protocol & API Design: Experience delivering developer-facing products such as SDKs and APIs, with knowledge of container management (Docker) and orchestration platforms (Kubernetes).
• Customer Empathy & Influence: Proven ability to uncover the "jobs to be done" by engaging directly with customers across roles: data leaders, scientists, and practitioners, while aligning executive stakeholders on a multi-year vision.
• Domain Expertise: Experience in risk management, cybersecurity, or highly regulated data environments is strongly preferred.
• Culture. We put our people first. Bitsight offers best in class benefits. We devote the same energy to nurturing our company's inclusive culture as we apply to serving our customers' needs. Working at Bitsight will give you the opportunity to fulfill your professional goals and expand your skills.
• Open-minded. If you got to this point, we hope you're feeling excited about the job description

Benefits

Additional Information

Bitsight is a cyber risk management leader transforming how companies manage exposure, performance, and risk for themselves and their third parties. Companies rely on Bitsight to prioritize their cybersecurity investments, build greater trust within their ecosystem, and reduce their chances of financial loss. Built on over a decade of technological innovation, its integrated solutions deliver value across enterprise security performance, digital supply chains, cyber insurance, and data analysis. We invented the cyber ratings industry in 2011 Over 3000 customers trust Bitsight Over 750 teammates are dispersed throughout Boston, Raleigh, New York, Lisbon, Singapore, and remote The Data Engine team powers the core intelligence that drives Bitsight's cyber risk solutions. As the paradigm of enterprise data management shifts from "Data for Humans" to "Data for Agents," we are looking for a Technical Product Manager to sit at the critical intersection of big data infrastructure and agentic tooling. In this role, you will be tasked with solving the "data mechanics" problem, architecting the evolution of our massive data repositories into "agent-ready" intelligence layers. You will ensure that our internet-scale data provides the rich context, semantic precision, and real-time accessibility required for advanced AI agents to perform complex workflows autonomously. The ideal candidate is a product leader who thrives navigating extreme ambiguity and possesses a "scale mindset." You can translate probabilistic AI outcomes into concrete business value and are equally comfortable debating data schemas, embeddings, and architecture tradeoffs with engineers as you are shaping commercial strategy.

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