People Programs and Total Rewards Architect
LangChainSan Francisco, CA$150k – $215kPosted 7 April 2026
Job Description
People Programs and Total Rewards Architect
ABOUT US
At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.
Today, LangChain, LangGraph, LangSmith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500.
With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.
ABOUT THE TEAM:
The People team at LangChain is architecting the operating system for the team behind the agents. Our charter is to make LangChain the best place to work, building the foundational infrastructure—from recruiting and global rewards to performance systems and AI upskilling—that empowers our team to achieve our mission of making agents ubiquitous. We treat the entire employee lifecycle as a product: modular, intentional, and designed for high-velocity iteration. We act as our own internal lab, dogfooding LangChain to automate the mundane and ensure our team stays focused on the high-judgment, high-impact work that moves the needle for our mission.
ABOUT THE ROLE:
We are looking for a foundational People Programs & Total Rewards Architect to build the engine that will power LangChain’s next phase of growth.
This isn't a traditional HR administer and maintain role. This is a high-agency, technical builder role for someone who views People programs as a product to be engineered. You will architect and operationalize how LangChain rewards, recognizes, and retains elite talent in a world where the future of work is being rewritten by AI. You will partner closely cross-functionally to build a global rewards and performance infrastructure that is competitive, equitable, and modular.
The systems you build today will define how we scale tomorrow.
WHAT YOU’LL DO:
- Architect the Reward Engine: Design and deploy a global compensation philosophy from first principles. You’ll build the frameworks for salary bands, leveling, and promotion guidelines that stay ahead of the hyper-competitive AI talent market.
- AI-Native Operations: Lead the charge in integrating AI agents and LLM-driven workflows into People Programs and Total Rewards. Your goal is to automate and leverage agents to handle the tactical (internal FAQs, synthesizing performance feedback, building job architecture) so you can focus on the complex underlying strategy, philosophy, and change management. Use our own tech stack to automate the "ops" out of People Ops.
- Future of Work Lab: Partner with our Applied AI team to drive company-wide adoption of AI tools, rethinking how AI-augmented roles change our definitions of performance, upskilling, and career velocity.
- Equity Strategy & Education: Own the evolution of our global equity programs. You’ll manage forecasting and modeling while ensuring every LangChain team member deeply understands the value of their stake in our mission.
- Performance Engineering: Design and run high-velocity performance and development programs that emphasize impact over activity, ensuring talent density remains elite as we scale.
- Data-Driven Influence: Build real-time dashboards and predictive analytics to help leadership make future-proof decisions on workforce planning and pay equity.
WHAT YOU’LL BRING:
- 6- ... (truncated, view full listing at source)
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