Lifesight Product Lead
4 days ago
About :
We're an AI studio within Lifesight that rapidly builds, launches, and scales AI native products. We operate in focused weeks long build cycles to ship MVPs, validate value, and iterate quickly.
Role Summary :
What You'll Do :
- Map incumbents/workarounds; identify where AI gives a 10x edge (personalization, automation, prediction, UX).
- Prioritize ruthlessly for a 6 week MVP; maintain a lean roadmap and cut scope aggressively to hit outcomes.
Hands On AI Prototyping :
- Stand up lightweight scripts/notebooks or small services to test feasibility (Python/TypeScript + LangChain/LlamaIndex).
- Assemble RAG spikes : data scoping, chunking strategy, embeddings, vector search, context windows, eval sets.
- Create prompt/eval repos; run side by side model tests; instrument quality/latency/cost telemetry.
Product Execution :
- Write crisp specs : user stories, acceptance criteria, data contracts, analytics events, safety/guardrail requirements.
- Drive design with low fi wireframes and clickable prototypes (Figma); specify UX for streaming and error states.
- Partner with engineers to sequence delivery; unblock daily; manage risk via spikes, flags, and phased rollouts.
- Ensure observability from day 1 (events taxonomy, funnels, cohorting); define experiment plans (A/Bs) and launch checklists.
AI Quality, Safety & Compliance :
- Define guardrails and evaluation protocols (red team prompts, refusal/citation policies, safety filters, fallbacks).
- Track AI quality signals (accuracy, coverage, helpfulness, CSAT); iterate prompts/models and retrieval strategy.
- Coordinate privacy/security reviews; ensure PII handling, data retention, and vendor usage meet studio standards.
Go to Market & Outcomes :
- Craft positioning and messaging with the marketer; align activation/onboarding to the AI
value moments.
- Set adoption/engagement targets (activation %, WAU, task success, LLM cost per task) and runweekly metric reviews.
- Close the loop with qualitative feedback (surveys, interviews, support/chat logs) to inform the next iteration.
Minimum Qualifications :
years in product management delivering 0 to 1 or growth iterations; startup or studio experience preferred.
- Hands on with AI : can design prompts/system instructions, wire up function/tool calling, and build quick RAG spikes.
- Working proficiency in Python, Nextjs or TypeScript for prototyping; comfortable with APIs/SDKs and basic CLI/git.
- Strong fluency with product analytics (PostHog/Mixpanel/Amplitude), events taxonomies, and
experiment design.
- Experience specifying and shipping AI powered UX (streaming, uncertainty, fallbacks, human in the loop).
- Excellent written specs, prioritization, and cross functional facilitation; bias to ship and learn.
Nice to Have :
- Knowledge of vector search (pgvector/Pinecone/Weaviate), embeddings, and retrieval strategies.
- Prompt/model evaluation tooling (Langfuse/Humanloop), LLM observability (Helicone), and OpenTelemetry.
- SQL for self serve analysis; dashboarding (Metabase/Looker); familiarity with data privacy frameworks.
- Light design skills (Figma) and comfort running user interviews and usability tests.
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