Role Description CaptivateIQ is looking for a Director of Product Management to lead the strategy and execution of our Product Platform — the shared foundation that every CaptivateIQ application is built on. This is the connective tissue of the company: the layers that turn a set of products into a single, AI-native system. This role owns one of CaptivateIQ’s highest-leverage areas. A single great primitive shipped here compounds across every product. It demands a leader who is hands-on, deeply curious about the systems beneath the surface, and capable of balancing rigorous platform thinking with decisive product execution. What You'll Own - AI & Agent Platform: - The agent SDK, MCP server, agent portal for authoring and observability, eval framework and runner, and shared chat/agent UI primitives. - Every layer must be API-first and agent-accessible. - Data Platform: - Bi-directional data connectors and the ETL/ingestion and transformation layer. - Workflows & Reporting: - Long-running orchestration with human-in-the-loop approvals and in-house reporting and analytics. - Identity: - Authentication and SSO, policies and permissions, entitlements that drive feature gating. - State Platform: - Versioning and state-transition machine, sandbox, and audit built on top of it. Your job is everything that makes our customer-facing applications interoperable, governable, and agent-ready. Responsibilities - Own the Product Platform strategy and roadmap. - Define how CaptivateIQ’s shared layers evolve to make every product faster to build and every model more connected. - Make the platform an accelerant, not a tax. - Champion interface-first, agent-ready design. - Model hands-on product leadership. - Scale enterprise readiness. - Develop system thinkers. - Drive measurable impact. Qualifications - 4+ years leading product managers, with a track record of shaping complex, multi-tenant systems. - Deep experience with platform or infrastructure products. - Demonstrated ability to build reusable primitives and abstractions. - Strong API-first instincts. - Fluency with and genuine curiosity about the AI/agent stack. - Strong cross-functional instincts. - A coaching mindset. - Clear, structured thinking. - Passion for creating environments where product teams do their best work. Benefits - Comprehensive Healthcare: 100% coverage for medical, dental, and vision for all FTEs, with roughly 75% coverage for dependents. - Flexible Time Off: Flexible vacation days plus quarterly mental health days. - Annual Stipends: Dedicated funds for professional development and caretaking needs. - Work Anniversary Bonuses: Annual bonuses to celebrate milestones and contributions. - Retirement Savings (US-Only): A 401(k) plan to help you invest in your future. - Premium Tools: The latest Apple hardware to empower you. - Inclusive Community: Active Employee Resource Groups (ERGs) that support our DEI goals.

• Own end-to-end decisions on how our platform handles real-time freight events at scale, from event ingestion across dozens of carrier sources, through data normalization, through ML-powered risk and ETA models, to the user-visible recommendations our enterprise customers act on. • Make architecture trade-offs explicit and defensible. When you choose Redis over Postgres for a use case, you can name the specific constraint that made that the right call and you can defend that decision against engineering, data science, and customer success, all of whom have different concerns. • Collaborate closely with our Data and Product team to integrate model outputs into production systems without breaking the latency budget. You decide whether a new prediction lives in real-time inference, batch precompute, or a hybrid and you defend why. • Instrument what you build, find real bottlenecks, and pick fixes that survive the next 10× of growth, not just the next sprint. You measure before you optimize, and your numbers are reproducible. • Raise the engineering bar across the team. You own sub-systems end-to-end, debug production issues across the stack, and participate in architectural decisions that shape the next 12 months of platform evolution. • Help shape a high-performing engineering culture. IC/senior engineers here don't gatekeep, they teach the framing they used to get there. You mentor through code review and design discussions, shape the operating norms the team works by, and model the standard for the engineers around you.

• Design, deploy, and operate Kubernetes clusters (EKS or self-managed) on AWS, ensuring high availability and security • Build and maintain GitHub Workflows and internal developer tooling to improve engineering velocity • Automate infrastructure provisioning and operational tasks using Python and tools like Terraform, OpenTofu, and Helm • Define and enforce platform standards around observability, cost management, resource scaling, and proactive incident management • Partner with application teams to support containerized workloads and resolve infrastructure bottlenecks • Collaborate with Customer Success teams by providing reliable and scalable tooling that supports seamless customer onboarding, integrations, and service delivery

• Design foundational patterns and guardrails for how EarnIn builds, evaluates, monitors, and deploys AI agents in production. • Own agent governance, including model selection, evaluation frameworks, safety guidelines, and production observability. • Establish infrastructure-as-code best practices for agentic systems, ensuring prompts, tools, and evaluation criteria are versioned, reviewed, and tested like critical components. • Serve as architect in agentic cloud infrastructure, establishing best practices for production AI agents. • Mentor senior engineers in advanced agentic patterns, LLM integration, and production prompt engineering. • Lead cross-functional initiatives with engineering, product, security, and business teams to align agentic AI adoption with company objectives. • Oversee large-scale, high-availability distributed systems on AWS, identifying and solving critical performance, scalability, and stability challenges. • Use AI-driven observability and anomaly detection to anticipate failures. • Lead the evolution of infrastructure-as-code and automation standards, incorporating agentic pattern recognition and automated remediation into operations. • Shape the evolution of our developer control plane (Cortex) as an AI-augmented self-service platform where engineers interact with intelligent assistants. • Drive AI-powered golden paths that encode platform standards, security policies, and best practices. • Act as liaison between cloud operations, AI infrastructure, and business stakeholders. • Develop documentation on agentic architecture, best practices, and operational procedures. • Participate in and lead on-call rotations, using post-mortems as feedback loops for improving system reliability and agentic automation.