Senior Product Manager
Junior AI LondonGBP 110,000–125,000 / yearJunior
Key requirements
- Llm
- Consulting
👶 About Junior
We're building cutting-edge LLM-powered tools that supercharge investment research for the world's most demanding deal teams. Our clients include several of the top 10 global private equity firms, Big 4 professional services firms, and leading consulting practices: organisations responsible for deploying billions of dollars annually.
We're profitable, bootstrapped, and past $20M in revenue after growing 10x in 2025. We're on track for 2–3x growth this year, and our product saves clients an average of 30 hours per week. We're expanding fast into investment banking, hedge funds, and research firms. Our PM team is currently 2 strong - we're looking for PMs #3-6 to own the core research workflow and help build out the product org as we scale from 60 to 120 people.
💡 The role
You'll own the core research workflow end to end - problem discovery, MVP scoping, shipping, and driving adoption. You'll run the day-to-day execution loop: partnering with engineering and design on specs and tradeoffs, talking to customers (PE firms, consultancies) on regular calls to understand their workflows and priorities, driving QA and release readiness, and keeping founders and leadership aligned with lightweight, high-signal communication.
You ship frequently - we measure success by shipping 1 major feature per week and driving measurable adoption of everything that ships. This is a high-ownership IC role; as the org grows, you'll have the opportunity to transition into a leadership role.
✅ What you'll do
Own the roadmap and execution for the core research workflow
Join customer calls with CS and users weekly; understand their workflows, pain points, and what "great" looks like
Partner with engineering + design to prioritize, scope, and ship quickly - your bar is MVP done, not perfect
Drive QA and launch readiness: testing plans, bug triage, launch checklists, iteration plans
Keep stakeholders (founders, engineering, design, CS) aligned through direct conversation, not documents
Demo new features on sales and CS calls; translate customer feedback into product priorities immediately
Measure impact: usage metrics, adoption curves, feature engagement - and iterate based on data
📈 What success looks like
Shipping velocity increases: 1 major feature per week, high-quality releases, fast iteration loops
Adoption improves: users discover new features, use them regularly, and tell us what to build next
Customer responsiveness: feedback lands in your hands → you make a call → it ships in days, not sprints
🔧 Sample projects
Interview guide generation - understand how teams currently create structured interview guides at project kickoff; work with customers to define the right workflow; partner with design and engineering on an AI-assisted guide creation experience; iterate with users on a prototype; roll out and measure adoption.
Live transcription - work with CS and customers to validate demand for faster transcript access during calls; align with engineering on feasibility; partner with design on how to surface live transcripts elegantly; pilot with early users; QA the release; launch; track usage.
Call anonymization - dig into how consulting clients manually create anonymized versions of transcripts; define what must be anonymized; work with design and engineering on a delightful anonymization flow; test with customers; run QA; launch; measure adoption.
🔥 About you
You've built something 0→1 from problem discovery through launch, iteration, and impact. Walk us through what you owned end to end - the decisions you made, the tradeoffs, how you knew it worked. We want to hear the details, not a highlight reel.
You have roughly 5+ years of product experience shipping fast. You come from a startup or scaling company where you shipped weekly or monthly, not quarterly. Bonus if you built at a high-bar company (Amazon, Palantir, top startup) or worked at a leading consulting firm while shipping re
See your match score for this role.
Xecodai maps the interview stages and shows what is preventing a 95% match.
