Senior Technical Product Manager
New
P
PAXAFEPharmaceutical logistics
Source API remote eligibility restrictions: United StatesFull-TimeSenior
SalaryUSD 140000 - 180000 / year
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Job Details
- Experience
- 5+ years in product management (or related technical role), with at least 2 years building AI/ML-powered B2B/SaaS products or data-intensive applications.
- Required Skills
- Product Management
Requirements
- Have 5+ years in product management or a related technical role.
- Have at least 2 years building AI/ML-powered B2B/SaaS products or data-intensive applications.
- Have a track record of launching and iterating on SaaS and/or B2B products.
- Bring technical fluency in AI/ML concepts, LLMs, and agentic workflows, and apply them to enterprise software.
- Have experience building products using LLMs, conversational AI, or autonomous agent systems.
- Understand how to design AI-powered features that improve user productivity and deliver measurable outcomes.
- Have experience collaborating with data science, ML engineering, software engineering, and design teams in a B2B/SaaS environment.
- Gather, interpret, and prioritize quantitative data, user research, and direct customer feedback.
- Develop product vision, strategy, roadmaps, and business performance metrics.
- Bonus: experience in pharmaceutical logistics, cold chain management, life sciences supply chain, or GxP-regulated environments.
- Bonus: familiarity with IoT integration, telemetry processing, and real-time data streaming architectures.
- Bonus: experience with prompt engineering, RAG architectures, or building LLM-powered applications.
Responsibilities
- Own product strategy and roadmaps for Lane Qualification, Data-Agnostic Visibility Command Center, Temperature Release, and Insights.
- Prioritize features that deliver measurable customer value for pharmaceutical supply chain operations.
- Engage pharmaceutical logistics teams, QA managers, and supply chain operations leaders to understand workflows and pain points.
- Translate logistics, GxP compliance, temperature excursion, and lane qualification requirements into product features.
- Collaborate with engineering to deliver solutions that process data from IoT providers and 3PL systems.
- Integrate LLMs and agentic AI workflows to enable natural-language queries, automated insights, and autonomous decision-making.
- Define and ship AI-powered features, including conversational interfaces, root-cause analysis, predictive recommendations, and intelligent alerting.
- Partner with data science and ML teams to apply the semantic data layer and ontology to LLM responses and agent actions.
- Define success metrics for AI feature adoption, accuracy, and business impact.
- Present product vision, roadmaps, and progress to customers, executives, and stakeholders.
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