Product Manager, Ghostwriter
As Product Manager for Ghostwriter, you will define how humans interact with software in the agent era, owning the end-to-end product experience from prompt to agent to outcome and helping scale Sierra to thousands of customers. You will define how AI augments agent development by shaping the workflows by which CX teams and developers draft journeys, run simulations, analyze conversations, and improve agents using natural language. You will balance autonomy and control by designing the appropriate human-in-the-loop patterns such as approval flows, change review, and workspace isolation to ensure customer trust in Ghostwriter's changes to their agents. You will partner closely with AI/ML and platform engineering teams to collaborate on model selection, harness engineering, execution architecture, and evaluation/testing infrastructure. Additionally, you will act as the voice of the agent builder by deeply understanding the pain points of CX managers, agent developers, and technical teams configuring journeys, integrations, and simulations.
Product Manager (Agents)
Lead the Lovable agent end-to-end by owning quality, roadmap, and feedback loops to improve it. Represent the user by synthesizing findings on agent performance and behavior and communicating these to the team clearly. Run discovery processes including user interviews, competitive research, evaluation analysis, prompt experimentation, and messaging for new agent capabilities. Own the quality bar for agent outputs by driving evaluation infrastructure, monitoring regressions, and ensuring continuous improvement with every release. Scope features carefully to deliver the right functionality, validate through user feedback and metrics, and eliminate non-effective parts. Enable sales, support, and marketing teams with the necessary context to communicate new agent capabilities effectively. Initial projects include rebuilding the agent evaluation framework to catch regressions before release, discovering gaps in agent reliability and trust, and defining and shipping the first iteration of improved agent error recovery and communication.
Senior Product Manager – Agentic AI Systems
Define and execute product initiatives for agentic AI systems focusing on measurable customer and business outcomes. Own significant parts of the agentic system lifecycle, including orchestration, decisioning, evaluation, and iteration. Contribute to building a repeatable framework for launching, evaluating, and improving agentic capabilities across customers. Help define how agentic systems are measured and improved in production, balancing autonomy with safety and reliability. Partner closely with Engineering, Applied AI/ML, Design, and Solutions teams to ship production-ready systems. Work directly with customers to understand workflows, requirements, and success criteria. Drive customer-informed prioritization by staying close to live deployments and real usage patterns. Support best practices for agent evaluation, iteration, and safe rollout. Represent the product in customer conversations, demos, and feedback sessions.
AI Product Manager
The AI Product Manager is responsible for rapidly prototyping and shipping new security features using AI coding tools and modern development workflows, leveraging internal data, threat intelligence, and market signals to identify high-impact opportunities and validate product direction. They build and scale features across cloud platforms, APIs, and security infrastructure using GenAI while maintaining high standards for reliability and security. They own product definition end-to-end by translating ambiguous problems into clear requirements and shipped solutions, balancing trade-offs across security effectiveness, performance, usability, and operational complexity. The role involves partnering cross-functionally with engineering, security researchers, and business stakeholders to deliver impactful outcomes, identifying opportunities to automate workflows using agentic AI systems and internal tooling, and contributing to the evolution of next-generation AI-driven cybersecurity capabilities including detection, response, and analysis systems.
Product Manager, Agent Harness & Modelling
Define and own the roadmap for North's agent harness, including the agent loop, context engineering layer, tool orchestration, sandbox execution, and sub-agent delegation. Serve as the primary interface between North engineering and Cohere's Modeling team, ensuring new harness capabilities are validated before being built and that neither team limits future possibilities. Own North's agentic evaluation framework, ensuring evaluations are compatible with both the North harness and Modeling's training infrastructure, serving as a reliable bridge between product and research. Engage enterprise customers to identify real-world agentic failures and translate findings into product and model requirements. Stay current with the open-source and commercial agent ecosystem and drive adoption decisions that align North's architecture with emerging standards.
Insurance Product Manager
The Insurance Product Manager is responsible for owning the full lifecycle of AI extraction workflows on the platform, including scoping, architecture, prototyping, evaluation, and iteration. They will design and build complex insurance workflows such as submission intake, policy comparison, underwriting audits, and claims workflows into structured, testable AI workflows from scratch. The role includes defining ground truths and evaluation sets to measure accuracy and quality, running continuous benchmarks, and identifying quality gaps before customers do. They will work directly with customers and Forward Deployed Engineers to configure, test, and iterate workflows toward production, bringing insurance process expertise and technical judgment to every deployment. The Insurance Product Manager acts as the bridge between domain expertise and engineering teams by translating insurance needs into technical solutions.
Investment Summer Associate - AI Tooling
Design and build a proprietary AI-powered sourcing tool for the Investment Team; work cross-functionally with investors to understand sourcing workflows and pain points; attend founder events, hacker house demo days, accelerators, and technical meetups to identify emerging builders; conduct calls with founders and support active deal diligence; contribute research that informs ongoing investment thesis development; serve as a thoughtful and professional ambassador for M13 within technical communities; build a sourcing tool that meaningfully improves how the team identifies and evaluates opportunities; develop structured documentation for tool handoff and iteration.
Product Manager, Safety Research
Serve as the product bridge between Cohere's safety research teams and North, ensuring that findings from model evaluations, red-teaming, and behavioral research translate into product-level guardrails, controls, and safeguards. Own the safety product roadmap for Cohere and North, prioritizing features based on research findings, observed misuse patterns, evolving threat vectors, and customer requirements. Partner with modeling teams to scope and interpret safety evaluations, understanding how Cohere’s underlying models behave across adversarial inputs, edge cases, and high-stakes use cases. Define and drive evaluation frameworks for assessing how safety properties hold up as models and product capabilities evolve, ensuring regressions surface before they reach customers. Coordinate the development of guardrails and intervention mechanisms by working across research, engineering, and policy to determine where and how safety controls should be implemented within North's product layer. Monitor the AI safety research landscape and ensure North's roadmap reflects current research on prompt injection, jailbreaks, and emerging misuse patterns in agentic systems. Build processes for scaling safety review as North's surface area grows, including assessing safety risks of new features before launch.
Product Manager, Personalization
As a Product Manager for Memory & Personalization at OpenAI, you will define how ChatGPT learns from and adapts to individual users over time by working at the intersection of product, research, and engineering to design systems that capture meaningful signals from user interactions and translate them into personalized experiences. You will spearhead the development and implementation of AI features by crafting the vision, strategy, roadmap, and execution plan, convert user feedback into detailed product requirements, narratives, and technical specifications, utilize data to understand user needs and guide product development, and collaborate closely with research, product design, and engineering teams to bring new capabilities to life. This role also involves balancing product innovation with safeguards around user control, privacy, and transparency.
Senior Product Manager – Data & Quality
The Senior Product Manager – Data & Quality at Snorkel AI is responsible for partnering with frontier AI research labs to design datasets and environments that enhance model performance. They lead technical conversations with customer researchers to understand model capabilities, failure modes, data requirements, and success criteria. The role involves probing model behavior through systematic evaluation to identify weaknesses and high-impact data interventions, designing evaluation frameworks, calibration processes, and quality rubrics to establish measurable project success metrics. Additionally, they develop technical specifications for data projects balancing research rigor with operational feasibility, serve as a thought partner to customer research teams throughout the sales cycle to build trust and credibility, and stay current on frontier AI research, RL environment design, post-training techniques, and evaluation methodologies.
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