Full Stack Product EngineerBuild the intelligence layer for revenue.

About Cenara

Cenara is building the intelligence layer for how revenue decisions get made. We sit above conversations, systems, and human judgment to transform raw, unstructured signals into clear, high-leverage decisions: what matters, what's at risk, and what to do next. Our goal is to eliminate reactive selling and replace it with systems that reason, learn, and compound insight over time. For engineers, this is a chance to work on real-world reasoning systems, agentic workflows, and human-AI collaboration at the sharp edge of business impact, where every model decision directly shapes outcomes.

What you'll do

You'll write and ship full-stack features end to end, from frontend UI, to backend AI logic, to the database, and infra. The product is early. You won't just be building features; you'll help shape the trajectory of the company and the future of how orgs make revenue decisions. Examples of what you might work on:

• Build a signal processor that turns unstructured data into actionable insights powered by AI agents.
• Create lightweight interfaces for sales leaders that surface confident actions with one-click workflows.
• Talk to early users, debug live pipeline issues, ship fixes same-day.
• Make product calls on ambiguity, unblock yourself, and own the stack from 0 → 1.

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This role is ideal if you

• Are a strong full-stack, product-minded engineer who enjoys owning products, not just code.
• Love using AI in your work — your dev stack is fully AI-enabled and you've built AI-enabled products or prototypes.
• Like turning messy, high-stakes workflows into clean, usable systems.
• Want to make product and UX decisions directly, without waiting on PMs or designers.
• Are low-ego and comfortable getting along with everyone.
• Are comfortable with ambiguity and making tradeoffs.

Minimum

• 3+ years engineering, with a strong track record of shipping 0 → 1 products (including time shipping production software).
• You've built and deployed agent-like systems: multi-step LLM pipelines, tool-using bots, scripted assistants, or similar.
• Fluent across the stack: backend APIs, frontend UIs, databases. End-to-end ownership.
• RAG pipelines (embeddings, vector DBs, chunking strategies).
• Agent memory systems (scratchpads, history compression, summarization).
• Tool use and orchestration (calling real APIs, using plugins, auth flows).
• Evaluation: success metrics, regression testing, improving agent behavior over time.
• You write production-grade code and can work across systems without needing a spec.
• You thrive in fast-paced, product-first environments where the goal is shipping.
• Comfortable with startup ambiguity: unblock yourself, pragmatic trade-offs, no perfect specs needed.

Backgrounds that tend to succeed

• Product-minded engineers who've built internal tools or workflow systems end-to-end.
• Engineers with experience in building full stack applications or workflow software.
• Former founders or early-stage startup engineers.
• Engineers who have owned both backend systems and frontend / user experience.