Senior Product Manager - Agentic AI Platform

Duck Creek Technologies•Remote, CA, CA

1d•$132,000 - $235,200•Hybrid

About The Position

Duck Creek Technologies is seeking a Senior Product Manager for their Agentic AI Platform. This role is responsible for executing the roadmap and defining major platform capabilities for Duck Creek’s Agentic AI Platform. The position involves translating AI platform strategy into product requirements, prioritized roadmap items, and reusable capabilities that support the safe deployment, orchestration, monitoring, and governance of AI agents across Duck Creek products and customer environments. The role requires collaboration with various teams including Product, Engineering, Architecture, Data Science, Security, Data, Legal, Compliance, Customer Success, Professional Services, and customer-facing teams to align platform capabilities with technical feasibility, governance expectations, and customer value. The Senior Product Manager will exercise significant judgment in prioritizing complex platform requirements, defining measurable outcomes, and recommending trade-offs across innovation, reliability, security, compliance, and operational readiness. The company emphasizes authenticity, purpose, and transparency, aiming to revolutionize how consumers interact with insurance companies through modern SaaS solutions. Duck Creek operates as a Flexible-First employer, empowering employees with the choice to work from an office, home, or a hybrid schedule, fostering productivity, inclusion, and collaboration.

Requirements

Bachelor’s degree, master’s degree, or equivalent experience in Computer Science, Information Systems, Engineering, Data Science, Business, Insurance, Product Management, or a related discipline.
6+ years of experience in technical product management, platform services, software engineering, AI product management, infrastructure management, PaaS, or related roles.
Experience owning complex product capabilities that require alignment across product teams, engineering teams, architects, data teams, security teams, customer-facing teams, and business stakeholders.
Experience working with AI, machine learning, generative AI, large language models, agentic AI, automation platforms, workflow systems, data platforms, integration platforms, or enterprise application platforms.
Knowledge of agentic AI concepts, including agent orchestration, tool use, prompt and instruction management, context grounding, evaluation, observability, and lifecycle management.
Knowledge of AI assurance and governance concepts, including explainability, interpretability, traceability, auditability, model lineage, monitoring, policy enforcement, and access controls.
Knowledge of platform product management practices, including roadmap execution, product discovery, requirements definition, backlog prioritization, and release planning.
Knowledge of enterprise SaaS platform considerations, including scalability, reliability, security, compliance, configurability, and operational supportability.
Knowledge of data grounding approaches, including approved knowledge sources, business rules, metadata, documents, system data, and governed data access.
Skill in translating complex technical concepts into clear product requirements, use cases, user stories, and acceptance criteria.
Skill in evaluating trade-offs across innovation, customer value, technical complexity, security, compliance, and operational readiness.
Skill in using product metrics to assess adoption, performance, reliability, safety, quality, cost, and customer value.
Skill in partnering with engineering, architecture, data science, security, legal, compliance, and customer-facing teams to resolve complex dependencies.
Ability to define product specifications for reusable, configurable, observable, secure, explainable, and governed AI agent capabilities.
Ability to influence cross-functional stakeholders without relying on direct reporting authority.
Ability to communicate AI platform decisions in clear business terms for technical and non-technical stakeholders.
Ability to operate in an emerging technology area where requirements, risks, standards, and implementation patterns continue to evolve.

Nice To Haves

Experience in P&C insurance, general insurance, InsurTech, financial services, or another complex regulated industry.
Experience with AI development tools and model-assisted product or prototyping workflows.
Experience working with enterprise-grade platform capabilities, multi-tenant SaaS environments, cloud-native platforms, or governed AI systems.
Knowledge of insurance technology environments across domains such as underwriting, claims, policy, billing, distribution, rating, reporting, or customer servicing.

Responsibilities

Own roadmap execution and product requirements for major capabilities within Duck Creek’s Agentic AI Platform, including agent orchestration, lifecycle management, governance, observability, and platform scalability.
Translate AI platform, agentic workflow, data, and architecture problems into epics, features, use cases, requirements, and user stories that support measurable business and customer value.
Partner with Engineering and Architecture to define scalable platform patterns for creating, deploying, coordinating, monitoring, evaluating, versioning, and retiring AI agents.
Define reusable agentic platform capabilities, including agent templates, tool and API access, agent registry, prompt and instruction management, task orchestration, human-in-the-loop controls, escalation, fallback, and approval patterns.
Partner with semantic data, data orchestration, AI, and product teams to support agent grounding in approved insurance context, including core system data, business rules, documents, configurations, metadata, and knowledge sources.
Establish product requirements for AI assurance capabilities, including explainability, traceability, audit logs, model lineage, evaluation, guardrails, access controls, security, compliance, and responsible AI governance.
Measure adoption, reliability, safety, and business impact of assigned Agentic AI Platform capabilities, including time to value, agent performance, task completion rates, human override rates, output quality, latency, cost, audit coverage, and customer value delivered.
Prioritize roadmap items and backlog decisions within assigned scope, balancing customer value, technical complexity, security, compliance, operational readiness, and delivery capacity.
Partner with Product and Engineering leaders to recommend roadmap trade-offs, sequencing decisions, and platform investments based on data, customer needs, technical feasibility, and risk.
Collaborate with Customer Success, Professional Services, and customer stakeholders to understand implementation needs, adoption barriers, operational requirements, and measurable value outcomes.
Communicate complex AI platform decisions in clear business and technical terms for product, customer-facing, technical, and leadership stakeholders.
Monitor emerging agentic AI, AI governance, observability, orchestration, and platform technology trends to inform assigned roadmap recommendations and product requirements.