AI Engineer

Pendo•New York, NY

6h•Hybrid

About The Position

Emergent AI Products is a new team at Pendo, built 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 bolted onto existing product; it is a deliberate bet on what product intelligence looks like next. The team moves fast, operates with high autonomy, and builds products without clear precedents. As an AI Software Engineer, you will build applied AI systems that move from prototype to production. You will bring deep technical capability, strong product judgment, and clear communication to decisions across prompting, fine-tuning, RAG, MLOps, and full-stack product delivery. You will partner closely with product and design to frame the right problems and ship AI-native experiences that hold up for real users. This role is based in our New York office.

Requirements

Deep hands-on experience building and shipping LLM-powered systems, including retrieval-augmented generation, tool use, and agent orchestration frameworks.
Demonstrated ability to apply established AI engineering patterns to well-scoped problems and ship them reliably in production.
End-to-end ownership of features from design through deployment and monitoring within a defined problem space.
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 MLOps experience, including model deployment, monitoring pipelines, and latency, cost, and reliability optimization in a live environment.
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 thinking, including the judgment to ask whether something should be built before deciding how to build it.
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 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.

Nice To Haves

Experience fine-tuning foundation models and a clear point of view on when fine-tuning outperforms prompting 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 design.
Prior experience contributing to or launching a net-new team or product area.

Responsibilities

Design and build AI-native product experiences, including RAG pipelines, agentic workflows, and LLM-powered features. You will take work from prototype through production and ensure systems are reliable enough for real users.
Make principled decisions about when to prompt, when to fine-tune, and when to use a different technical approach. You will explain those tradeoffs clearly to engineers and non-engineers.
Instrument and evaluate model outputs rigorously by defining evaluation frameworks and identifying failure modes early. You will catch hallucinations, measure quality, and implement guardrails that hold up under real-world load.
Own model deployment, monitoring, latency optimization, cost management, and reliability at scale. You will ensure AI systems operate effectively in live production environments.
Contribute across the stack when needed because the team ships products, not just models. You will help get complete user-facing AI experiences into customers’ hands.
Partner closely with product and design to frame problems before implementation begins. You will push back when the framing is wrong and help the team focus on what should be built, not only how to build it.
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 apply them thoughtfully.