Senior Product Manager

insightsoftware

. Define and maintain the AI Services strategy, roadmap, and quarterly priorities for agentic workflows, the tool and connector layer, and AI quality infrastructure .

Posted 10/13/2026full-timeRemote • United StatesSenior💰 $124,000 - $156,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI product management, including defining strategies, building evaluation frameworks, and translating business problems into agent designs. Proficient in managing AI quality, technical direction, and cross-functional collaboration in a B2B enterprise SaaS environment.

Highest-signal resume keywords

AI Product ManagementLarge Language Model ApplicationsAgentic ArchitecturesEvaluation Frameworks for AI SystemsAgile Delivery

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Quality InfrastructureModel Context ProtocolTool and Function CallingPrompt EngineeringDataset ConstructionMetric SelectionSystem DesignArchitecture DiscussionsAPI-Based ServicesEvaluation Scores

Soft Skills

Excellent Written CommunicationInfluencing Cross-Functional Teams

Tools & Technologies

Agile MethodologiesRegression HarnessesProduction ObservabilityData HandlingModel Governance

Industry Keywords

Enterprise FinanceAccountingERPBusiness IntelligenceAI SecurityData ResidencyRegulatory Considerations

Tech Stack

Tools & technologies

ERPOpen Source

About the role

Key responsibilities & impact

Define and maintain the AI Services strategy, roadmap, and quarterly priorities for agentic workflows, the tool and connector layer, and AI quality infrastructure
Make trade-off decisions on sequencing, scope, and technical direction, supported by evidence
Specify multi-step agent behavior, including planning, tool selection, memory, human-in-the-loop checkpoints, fallback paths, and guardrails
Translate ambiguous business problems into reliable agent designs for finance users
Own the Model Context Protocol surface and tool-interface roadmap
Decide which company data, actions, and product capabilities are exposed to agents and third-party assistants
Define contracts, versioning, and access controls for tool and connector interfaces
Build and own evaluation frameworks using golden datasets, offline and online evaluations, regression harnesses, accuracy and hallucination measurement, and production observability
Set AI quality bars that gate releases
Support portfolio product managers and engineering teams through intake, integration documentation, reference implementations, adoption guidance, and adoption measurement
Partner with the chief architect and engineering manager on design reviews, technical trade-offs, model and vendor selection, cost, and latency management
Participate in sprint planning and refinement and unblock product decisions
Define metrics including product-line adoption, agent task success rates, evaluation scores, cost per task, latency, and incident rates
Report outcomes and recommendations to senior leadership
Work with security, legal, and compliance on data handling, model governance, auditability, and customer trust concerns

Requirements

What you’ll need

8 or more years in product management
At least two years owning AI products as a hands-on individual contributor
Demonstrated experience shipping large language model applications to production
Working technical fluency in agentic architectures, including orchestration and planning patterns, tool and function calling, retrieval-augmented generation, context management, and prompt engineering
Hands-on experience with the Model Context Protocol or comparable tool and plugin interfaces for connecting agents to enterprise systems
Practical experience building or operating evaluation frameworks for AI systems, including dataset construction, metric selection, and result interpretation
Experience delivering a shared platform or API-based service where other product teams are the primary consumers
Ability to read code, reason about system design, and participate in architecture discussions with senior engineers
Strong command of Agile delivery
Ability to influence cross-functional teams and senior stakeholders without formal authority
Excellent written communication
Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
Preferred: experience taking AI capabilities to market in a B2B enterprise SaaS environment
Preferred: background in enterprise finance, accounting, ERP, or business intelligence domains
Preferred: experience managing inference cost, latency, and model routing across multiple providers at scale
Preferred: familiarity with AI security, data residency, and regulatory considerations
Preferred: prior experience as the first product hire on a team
Preferred: contributions to open source AI tooling, published evaluation work, or an active public presence in the agentic AI community

Benefits

Comp & perks

Additional bonus eligibility may apply
Equal employment opportunity workplace
Confidential handling of applicant information
Background checks required for employment, where permitted by country, state/province