About the company
Pendo was founded in 2013 by former product managers, who combined their heads and hearts to build something they wanted but never had as product managers: a simple way to understand and attack what truly drives product success.
Responsibilities
- Design and build AI-native systems, including RAG pipelines, agentic workflows, and LLM-powered product features
- Make principled decisions about when to prompt, when to fine-tune, and when to use a different technical approach entirely
- Instrument and evaluate model outputs rigorously by defining evaluation frameworks and identifying hallucinations early
- Own model deployment, monitoring, latency optimization, cost management, and reliability at scale
- Contribute across the stack when needed to get complete AI products in front of users
- Partner closely with product and design to frame problems well before implementation begins
- Stay current on the research and tooling landscape, including transformers, diffusion architectures, orchestration frameworks, and emerging agent patterns
Requirements
- Deep hands-on experience building and shipping LLM-powered systems, including retrieval-augmented generation, tool use, and agent orchestration frameworks
- Demonstrated ability to set technical direction for AI systems across teams, establish architectural patterns, make foundational model strategy decisions, and raise the bar for AI engineering quality
- Experience owning outcomes across team boundaries, including identifying capability gaps, driving alignment across engineering and product, and influencing how a broader organization approaches AI
- Strong command of model evaluation, including designing evaluation suites, reasoning about overfitting and bias-variance tradeoffs, and systematically detecting and mitigating hallucinations
- Solid understanding of modern model architectures, including transformers and diffusion models
- Production AI experience, including model deployment, monitoring pipelines, and latency, cost, and reliability optimization in live environments
- Strong full-stack fundamentals and comfort working across backend and frontend systems
- Exceptional communication skills
- Demonstrated product judgment
Nice-to-haves
- Experience fine-tuning foundation models
- Familiarity with AI safety considerations, guardrail frameworks, and responsible deployment practices
- Experience building agentic or multi-step reasoning systems using tools such as LangChain, LlamaIndex, or custom orchestration frameworks
- Background in a SaaS or product analytics environment
- Prior experience contributing to or launching a net-new team or product area
Conditions
- This role is based in our New York office