Why This Job is Featured on The SaaS Jobs
This Senior Product Manager role sits at the intersection of enterprise SaaS and applied AI, where product decisions are constrained by real customer workflows and the operational realities of running intelligent systems in production. The focus on agentic AI for contact center environments signals a platform context rather than a single feature area, with success tied to measurable outcomes across high-volume interactions.
For a SaaS product leader, the role offers concentrated exposure to the full loop that matters in modern B2B software: shipping, observing usage, iterating, and formalising repeatable launch and evaluation practices. Working across Engineering, Applied AI/ML, Design, and customer-facing teams also builds the cross-functional operating muscle that transfers well across SaaS companies, especially those integrating LLM-driven capabilities into core product experiences.
The position is best suited to a PM who prefers execution-heavy ownership and is comfortable translating ambiguity into requirements that engineering and ML teams can act on. It will fit someone who values direct customer contact as an input to prioritisation, and who is motivated by the craft of making complex systems reliable, measurable, and safe in real deployments.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Location: US (Remote / Bay Area preferred)
Experience: 4 years of Product Management experience
Reports to: Head of Product
About Level AI :Level AI is an AI-native customer experience intelligence platform helping enterprises deploy agentic AI systems that reason, act, and improve across high-volume customer interactions. Our products power real-world contact center workflows and deliver measurable business outcomes at scale.
Role Overview : We’re looking for a Senior Product Manager to help build and scale agentic AI systems at Level AI. In this role, you will work closely with Engineering, Applied AI/ML, Design, and customer-facing teams to ship production-ready agentic capabilities and make them successful in real customer environments.This role emphasizes execution, customer impact, and production rigor, with opportunities to grow into broader platform ownership over time.
What You’ll Do: Define and execute product initiatives for agentic AI systems, with a focus on measurable customer and business outcomesOwn significant parts of the agentic system lifecycle, including orchestration, decisioning, evaluation, and iterationContribute to building a repeatable framework for launching, evaluating, and improving agentic capabilities across customersHelp define how agentic systems are measured and improved in production, balancing autonomy with safety and reliabilityPartner closely with Engineering, Applied AI/ML, Design, and Solutions teams to ship production-ready systemsWork directly with customers to understand workflows, requirements, and success criteriaDrive customer-informed prioritization by staying close to live deployments and real usage patternsSupport best practices for agent evaluation, iteration, and safe rolloutRepresent the product in customer conversations, demos, and feedback sessions
What We’re Looking For:
Required -
- 4 years of Product Management experience, preferably with AI-driven or platform products
- Experience shipping and iterating on production software systems
- Exposure to LLMs, agentic systems, or AI-powered workflows (hands-on or via close partnership)
- Strong customer-facing skills and comfort working with enterprise customers
- Ability to translate ambiguous problems into clear product requirements
- Excellent collaboration and communication skills
Nice to Have:
- Experience with conversational systems, automation, or real-time decisioning
- Familiarity with AI evaluation concepts, human-in-the-loop systems, or feedback loops
- Experience working in enterprise SaaS or B2B platformsTechnical background or strong comfort working with engineering and ML teams
Why This Role at Level AI
- Work on real production agentic AI systems, not experimentsHigh exposure to customers, data, and real-world outcomes
- Opportunity to grow into broader platform or Principal-level ownership
- Meaningful impact on how enterprises adopt and trust AI
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