---
title: 'Technical Project Manager at Reinforce Labs, Inc.'
canonical: 'https://feeny.ai/job/technical-project-manager-reinforce-labs-inc-palo-alto-rtery9n389nb'
type: 'job'
last_seen: '2026-09-09'
---

# Technical Project Manager at Reinforce Labs, Inc.

- **Company:** Reinforce Labs, Inc.
- **Location:** Palo Alto, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-06-03
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.ashbyhq.com/reinforce-labs-inc/b5fc286d-fc9e-4fda-91e7-ce5bd1b6ba17

## Job description

## About Reinforce Labs

We're an early-stage startup disrupting how companies evaluate their AI systems. Our customers care deeply about safety, trust, compliance, and revenue impact. We help them launch AI confidently: catching regressions before customers do, measuring if their systems meet the bar and tying it to business outcomes.

We're small, technical, and agile. The eval space is changing weekly, and we intend to define the category. If you want to take part in something from the early stages, read on.

## About the Role

We're hiring a Technical Project Manager to drive execution across the engineering organization. You'll own the delivery of high-stakes, cross-functional programs that span engineering, AI/ML infrastructure, data, and product, keeping multiple teams aligned, dependencies unblocked, and leadership informed at every step.

This is not a process-for-process's-sake role. We're looking for someone who can sit in a room with engineers, understand the technical tradeoffs being debated, identify the real risks, and drive the team to a decision. You'll be measured on outcomes: did the program ship, did it ship on time, and did it ship at the quality bar our users deserve.

## What You'll Do

- Own end-to-end delivery of cross-functional engineering programs from kickoff through launch and post-launch measurement.
- Build the plan, then defend it. Break ambiguous objectives into milestones, dependencies, and clear owners. Pressure-test scope with engineering and product leads. Re-plan when reality changes.
- Drive rhythm. Run sprint planning, standups, demos, retros, and steering committees for the programs you lead. Make every meeting earn its place on the calendar.
- Surface and unblock risks before they become slips. Track dependencies across teams (engineering, data, vendors), escalate cleanly, and propose mitigations rather than just flagging problems.
- Improve how we work. Identify patterns across programs and propose changes to tooling, process, or org design. Pilot, measure, scale what works, kill what doesn't.
- Partner on incident response and post-mortems for the programs you own and make sure we learn and the fix actually ships.

## What We're Looking For

Required

- Curiosity and ambition
- Program/project management experience in a high-growth software environment.
- Track record of shipping concrete examples of programs you owned end-to-end, the constraints you operated under, and what you delivered.
- Technical fluency: ask the right follow-up questions, and call out unrealistic estimates.
- Outstanding written communication. You can compress a complicated status into a paragraph and a complicated plan into a page.

Bonus

- Experience at a AI/ML product company.
- Background in software engineering, data engineering, or technical product management before moving into TPM.
- Familiarity with AI/ML delivery such as agent orchestration, eval pipelines, data labeling workflows.d
- Experience standing up a TPM function or program from scratch.

## About Reinforce Labs, Inc.

## Company Overview
- **One-liner**: Reinforce Labs provides an AI safety platform that catches how AI fails, generates data and fixes to close gaps, and guards models in production.
- **Entity Type**: Private (Seed Stage)
- **Headquarters**: Palo Alto, California, United States
- **Founded**: Not publicly available
- **Founders**: Anish Das Sarma (Founder and CEO)

## Core Business
- **Primary industry**: AI Safety, Enterprise AI, AI Evaluation & Red-Teaming
- **Target customers**: Enterprise and regulated industries (banking, telecom, retail, healthcare, insurance, logistics, investment banking); also serves AI model builders and researchers
- **Mission or purpose**: Making the internet a safer place using AI.

## Products & Services
- **Flint (Evaluation Platform)**: An evolutionary multi-turn red-teaming system that simulates real and adversarial users across models, chatbots, and agents, grading every turn against the customer’s policy. Produces severity-weighted, model-card-ready reports.
- **Data (Synthetic Datasets)**: Frontier-grade, verifiable datasets built in-house (e.g., MATH Core, Lean 4, Chart-VQA, GIS, Spatial) for training and evaluation. Benchmarked against frontier models.
- **Guardrails (Production Protection)**: Runtime guardrails that redeploy the same scorers from evaluation into live traffic, providing real-time risk scoring, inline blocking, and integration with existing OTel/Grafana observability.
- **Forward-Deployed Engineering (FDE)**: Full-service deployment where Reinforce engineers design, build, evaluate, and ship production AI agents for customers lacking in-house ML/AI capacity.

## Market Standing
- **Valuation**: Not publicly available
- **Key Metric**: Total funding — Not publicly available; stage is Seed
- **Notable Investors/Partners**: Not publicly disclosed on main sources
- **Growth Signals**: Headcount grew 450% year-over-year (to 16 employees). Published research at KDD 2026, ICML 2026, NeurIPS 2025, and TrustCon 2026. Has delivered production AI engagements across regulated industries.

## Competitive Advantages
- **Model-agnostic**: Tests and guards any model (Claude, GPT, open-weight) — the company does not sell its own model.
- **Continuous loop**: Build → Evaluate → Fix → Deploy → Guard, with each pass becoming cheaper.
- **Independent evaluation**: Customers keep every artifact (datasets, prompt fixes, reports); no platform lock-in.
- **Published research**: Peer-reviewed papers at top ML conferences validate the methodology.
- **Self-hosted option**: Can run in the customer’s own environment for data residency compliance.

## Strategic Focus
- Scaling the platform to serve more enterprise customers in regulated industries (healthcare, BFSI, insurance).
- Expanding the synthetic dataset catalog and maintaining frontier-grade benchmarks.
- Growing the forward-deployed engineering team to handle full-stack AI agent delivery.
- Continuing to publish research and build thought leadership in AI safety.

## Why Work Here
- **Culture**: High-caliber, research-driven team with backgrounds from mathematics and computer science at the University of Pennsylvania, with a network of PhDs and faculty. Emphasis on shipping production-grade AI safety.
- **Remote/Hybrid**: Not explicitly stated, but headquartered in Palo Alto, CA.
- **Notable perks/engineering culture**: Opportunity to work on cutting-edge AI safety problems with top researchers. Small team (16 people) with 450% YoY growth, offering significant ownership and impact. Technical roles make up 36% of the workforce. Published research at top conferences (NeurIPS, ICML, KDD). Access to a network of academic experts.

## Sources
1. [reinforcelabs.ai](https://www.reinforcelabs.ai/)
2. [jobs.ashbyhq.com](https://jobs.ashbyhq.com/reinforce-labs-inc)
3. [linkedin.com](https://www.linkedin.com/company/reinforcelabs)

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