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Open nowPosted 170 days ago

Staff Software Engineer (AI)

Pendo24 open roles

Pay
$300,000 – $325,000 a year
Where
New York, NY
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Your applicationOpen nowStaff Software Engineer (AI)Pendo · New York, NY
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The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market. Pendo postings stay open a median of 41 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 170 days ago

Pendo median: 41 days open

The posting

The Team + The Role

Our Engineering Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents.

As a Staff Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and build production-grade AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, while making clear tradeoffs across prompting, fine-tuning, architecture, evaluation, and deployment. You will also partner closely with product, design, and engineering stakeholders to frame the right problems and communicate technical decisions clearly.

This role is based in our New York office.

What this looks like day-to-day

  • Applied AI systems: Design and build AI-native systems, including RAG pipelines, agentic workflows, and LLM-powered product features. You will take ideas from prototype through production and ensure they can support real users.
  • Model strategy: Make principled decisions about when to prompt, when to fine-tune, and when to use a different technical approach entirely. You will explain those tradeoffs clearly to engineers and non-engineers.
  • Evaluation and guardrails: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and identifying hallucinations early. You will implement guardrails that hold up under real-world usage and load.
  • Productionize AI ownership: Own model deployment, monitoring, latency optimization, cost management, and reliability at scale. You will ensure AI systems are observable, performant, and production-ready.
  • Full-stack delivery: Contribute across the stack when needed to get complete AI products in front of users. This team ships products, not just models, and you will help close the gap between technical capability and user experience.
  • Product partnership: Partner closely with product and design to frame problems well before implementation begins. You will push back when the framing is wrong and help the team stay focused on what is worth building.
  • Technical leadership: Stay current on the research and tooling landscape, including transformers, diffusion architectures, orchestration frameworks, and emerging agent patterns. You will bring relevant advances back to the team and help raise the technical bar.

Who You Are

Beyond the qualifications, we hire through a specific lens. These aren't buzzwords; they're the things we'll actually look for in how you talk about your work.

You're a builder, not a maintainer.

You're most energized when there isn't a clear path yet, and you get to define it. You don't wait for direction; you identify gaps, shape solutions, and drive them forward. At Pendo, great Staff AI Software Engineers don't just follow instructions; they operate as strategic advisors, influencing decisions, guiding stakeholders, and elevating how we work.

You're AI-curious - genuinely.

You're not using AI tools occasionally. You're rewiring how you work around them. You're faster, sharper, and more prolific because of it, and you bring that energy to everything — how you approach your work, how you prep, how you communicate, how you think. We want someone who sees AI as a multiplier, not a shortcut.

Must-haves

  • 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, with the ability to make informed decisions about when and how to apply them.
  • Production Productionize 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 to ship complete, user-facing AI products.
  • Exceptional communication skills, with the ability to explain complex technical decisions clearly to engineers, product managers, and executives.
  • Demonstrated product judgment and the ability to evaluate whether something should be built before determining how to build it.

Nice-to-haves

  • Experience fine-tuning foundation models and a clear point of view on when fine-tuning outperforms prompting-based approaches.
  • 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 where user behavior data informs AI product design.
  • Prior experience contributing to or launching a net-new team or product area.

About Pendo

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. Our mission is to improve society's experience with software. Come join one of the fastest-growing startups, supported by best-in-class institutions like Battery Ventures, Salesforce Ventures, Spark Capital and Meritech.

Pendo Core Values: Bias to Act, Hone Your Craft, The Team is Pendo, and Maniacal Focus.

Location: Pendo is a hybrid culture. In-office 3 days per week unless designated remote.

Compensation: The expected salary range for this role to be performed in New York, NY is $300,000 - $325,000.

Benefits: Highly competitive, employer-heavy coverage, including $0 premium options, strong 401(k) match, equity, and flexible time off.

EEOC: We are an equal opportunity employer and believe having diverse teams where everyone brings their whole self to Pendo is key to our success. We welcome all people of different backgrounds, experiences, abilities and perspectives.

Accessibility: Pendo is committed to working with, and providing access and reasonable accommodation to, applicants with mental and/or physical disabilities. If you think you may require an accommodation for any part of the recruitment process, please send a request to: [email protected]. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.

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