Enabling families to make the best senior living decisions for their loved ones
Lead Product Manager, Organic & AI Discovery
Location
Texas
Posted
21 hours ago
Salary
$165K - $195K / year
Seniority
Senior
Job Description
Lead Product Manager, Organic & AI Discovery
A Place for Mom
• Own the product strategy and roadmap for how APFM's owned properties perform across the traditional, AI-mediated, voice, and agentic search landscape • Translate SEO signals, algorithm shifts, and discovery changes into product decisions and roadmap prioritization; partner with specialist practitioners who own day-to-day execution • Define and evolve how A Place for Mom shows up across the full AI-mediated discovery landscape, including AI search citations, conversational query coverage, structured data for AI grounding, MCP integrations, voice interfaces, and agentic endpoints • Monitor and interpret shifts in AI platform behavior, search landscape changes, and evolving distribution surfaces, and translate them into internal product guidance, guardrails, and prioritization • Evolve existing AI discovery measurement framework and tooling as the ecosystem develops and new channels come online that require new measurement approaches • Build acquisition loops into the product surface: Sharing, comparison tools, decision aids, community-driven content surfaces • Partner with Product peers to embed PLG mechanics in core flows that compound organic acquisition without paid spend • Define metrics, baselines, and targets for organic and AI discovery; size opportunities, set hypotheses, and lead learning agendas • Translate ambiguous, evolving discovery signals into actionable product bets and clear investment recommendations • Embed authority, expertise, and trust signals into product surfaces and content systems • Ensure the signals AI systems use to evaluate credibility, including review integrity, content quality, and decision support depth, are reflected accurately in what we build • Develop and maintain a point of view on AI disintermediation risk and ensure the product roadmap accounts for it
Job Requirements
- 7–10+ years of experience in SEO, organic growth, product strategy, or related roles
- Demonstrated depth in SEO fundamentals and a track record of shipping product surfaces that moved organic acquisition outcomes, not just advising on them
- A working point of view on how the search landscape is evolving: how AI-mediated discovery works, how to instrument and influence it, and where it's heading
- Comfort with ambiguous, evolving data sets and the ability to build measurement approaches where none exist yet
- Strong opinions on trust-sensitive, YMYL content and product systems
- Proven ability to write clear requirements, run experiments, partner closely with engineering, and own delivery end-to-end
- Experience facilitating alignment across senior stakeholders in ambiguous, cross-domain problem spaces
- Experience managing or mentoring other practitioners; a track record of elevating the product intuition and execution quality of the team around you
- Bonus: marketplace or aggregator experience, regulated or health-adjacent domains, prior GEO work, MCP or agentic distribution experience
Benefits
- 401(k) plus match
- Dental insurance
- Health insurance
- Vision Insurance
- Paid Time Off
Related Guides
Related Job Pages
More AI Engineer Jobs
Applied AI Engineer – Finance Super App
BJAKBjak is a technology company focused on making financial services easy, fun and more rewarding for everyone
• Build AI-powered workflows, assistants, agents and automation systems. • Apply AI across customer support, CRM, onboarding, claims, renewals, payments, operations and internal tools. • Work with product and engineering teams to turn manual processes into scalable AI-native systems. • Build integrations with LLMs, internal data, APIs, documents, knowledge bases and business systems. • Design evaluation, monitoring and fallback flows so AI outputs are useful, safe and reliable. • Prototype quickly, test with users or operators, then productionize what works.
Applied AI Engineer – Finance Super App
BJAKBjak is a technology company focused on making financial services easy, fun and more rewarding for everyone
• Build AI-powered workflows, assistants, agents and automation systems. • Apply AI across customer support, CRM, onboarding, claims, renewals, payments, operations and internal tools. • Work with product and engineering teams to turn manual processes into scalable AI-native systems. • Build integrations with LLMs, internal data, APIs, documents, knowledge bases and business systems. • Design evaluation, monitoring and fallback flows so AI outputs are useful, safe and reliable. • Prototype quickly, test with users or operators, then productionize what works. • Improve speed, quality and consistency across workflows using AI where it creates real business value.
Applied AI Engineer – Finance Super App
BJAKBjak is a technology company focused on making financial services easy, fun and more rewarding for everyone
• Build AI-powered workflows, assistants, agents and automation systems. • Apply AI across customer support, CRM, onboarding, claims, renewals, payments, operations and internal tools. • Work with product and engineering teams to turn manual processes into scalable AI-native systems. • Build integrations with LLMs, internal data, APIs, documents, knowledge bases and business systems. • Design evaluation, monitoring and fallback flows so AI outputs are useful, safe and reliable. • Prototype quickly, test with users or operators, then productionize what works. • Improve speed, quality and consistency across workflows using AI where it creates real business value.
Applied AI Engineer – Finance Super App
BJAKBjak is a technology company focused on making financial services easy, fun and more rewarding for everyone
• Build AI-powered workflows, assistants, agents and automation systems. • Apply AI across customer support, CRM, onboarding, claims, renewals, payments, operations and internal tools. • Work with product and engineering teams to turn manual processes into scalable AI-native systems. • Build integrations with LLMs, internal data, APIs, documents, knowledge bases and business systems. • Design evaluation, monitoring and fallback flows so AI outputs are useful, safe and reliable. • Prototype quickly, test with users or operators, then productionize what works. • Improve speed, quality and consistency across workflows using AI where it creates real business value.
