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Product Development Engineer I (AI-Native) (Onsite role)

Phenom People Pvt Ltd

Ambler, PA, United States
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Ambler, PA, United States
Location
On-site
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Phenom People Pvt Ltd
Employer
Ai Engineer jobs
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Job Requirements Product Development Engineer I (AI-Native) (Onsite role) Job Description Our purpose is to help a billion people find the right work! Phenom is an AI-Powered talent experience platform that is redefining the HR tech space. We have grown into a global organization with offices in 6 countries and over 1,500 employees. As an HR tech unicorn organization, innovation and creativity is within our DNA.

Come help us make every talent moment Phenomenal! We are looking for a Product Development Engineer (AI-Native) who takes ideas and customer needs and turns them into working, validated product features and agentic capabilities — owning them from first prototype to production. Here, everyone wears multiple hats: the same person who builds a feature also ships it, supports the people using it, and debugs issues directly.

You own outcomes end-to-end, not a narrow slice. What You’ll Do ●      Build innovative products on the Phenom platform — prototype fast, then harden what proves valuable into something customers can rely on. ●      Take ideas to production — design, build, and validate features end-to-end, then keep improving them after they ship. ●      Build and improve reusable agentic skills — packaged, versioned capabilities anyone in engineering can compose and re-run, so the next build starts from a proven asset, not a blank page.

●      Practice AI-assisted, increasingly agentic engineering — drive PRs with coding agents and your own custom skills, and wire each PR to also update the observability it depends on. ●      Run a controlled debugging loop — work from logs, traces, and prior incidents to find and fix root causes quickly. ●      Own delivery to customers — deployment gates and hypercare, partnering with reliability engineers on deep platform issues.

●      Keep rich context for agents — maintain the structured, per-customer context that every agent and skill draws on before it acts. ●      Respect the guardrails — analysis is separated from action, high-risk changes require human approval, and every decision is logged for audit. What You’ve Done ●     1-4 years of software development experience. ●     Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related technical field required; Master's degree preferred.

●      Strong fundamentals and critical thinking — AI raises the bar on judgment, it doesn’t replace it. ●     Comfortable across the stack and building with modern AI coding tools and agents. ●      Customer empathy — you can sit with a customer, ask the right questions, and decide which problems are worth solving. ●      End-to-end ownership — you finish what you start and keep improving it. ●      Adaptable — eager to adopt new tools and reinvent your workflow as the tooling changes (often weekly).

●     A strong communicator who aligns quickly with colleagues and customers. ●      You thrive on variety — building, debugging, shipping, and customer calls in the same week. ●      Bonus: experience building AI / agent products, workflow orchestration, observability, or building agent workflows on an Agent SDK. Technical Skills ●      Programming proficiency — write clean, maintainable code in at least one modern language (e.g., Python, Java, JavaScript / TypeScript, or Go).

●      Computer science foundations — strong understanding of data structures, algorithms, complexity (Big-O), and decomposing problems into clean, testable components. ●      Software design principles — object-oriented and functional concepts, clean-code practices, and sensible code and API design. ●      Version control & collaboration — day-to-day fluency with Git, branches, pull requests, and code review.

●      APIs & databases — working knowledge of REST APIs and JSON, plus basic SQL and data modeling with relational and/or NoSQL stores. ●      Testing & debugging — writing unit and integration tests and diagnosing issues methodically from logs, traces, and stack traces. ●

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