In today's complex digital economy, making optimal purchasing decisions requires analyzing hundreds of variables across multiple platforms. CaelumenAI makes this effortless.

CaelumenAI

CaelumenAI revolutionizes how businesses and individuals make purchasing decisions.

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Agent Engineering

AI Agent Engineer — Early Career

Build and verify the agent-native developer systems that help people and coding agents plan, implement, test, and ship real software together.

Applications open

Location Remote / San Francisco, CA

Work model Remote-first

Employment Full-time

Compensation Salary range shared in process

Application window Open until filled

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01 / The role

Build the system, then prove it works.

CaelumenAI is building the governed production layer for agent-native software. PERCO, our flagship product, turns agent output into a reviewable plan, a controlled release, and evidence of what happened. As an AI Agent Engineer — Early Career, you will own small, real product slices across agent workflows, developer tools, APIs, browser experiences, and deployment verification. You will work with coding agents as collaborators, review their output, trace failures to root causes, and carry changes from a clearly scoped problem through implementation and real-world evidence. This role is open to new graduates and other early-career engineers with roughly zero to two years of professional experience. Strong project evidence can come from coursework, open source, internships, personal products, or paid work. Compensation is discussed during the interview process. Applicants must have valid authorization to work in the United States when employment begins. We welcome candidates working under valid OPT and support eligible H-1B sponsorship.

02 / Your work

What you’ll do

Build agent-native product and developer workflows across Python, JavaScript or TypeScript, APIs, CLI, MCP, and browser surfacesTurn product problems into small end-to-end implementations with clear acceptance evidenceUse coding agents effectively by preparing context, reviewing output, and retaining human ownership of consequential decisionsCreate automated coverage with pytest, Playwright, integration tests, and agent evaluationsInvestigate failures to root cause and ship durable fixes with regression coverageImprove the reliability, clarity, and safety of PERCO's human-controlled release workflows

03 / The signal

What we’re looking for

Evidence over pedigree

Show us something you scoped, built, tested, and debugged—and tell us what the evidence changed.

Approximately zero to two years of professional software engineering experience, or equivalent evidence through substantial projectsWorking proficiency in Python, JavaScript, or TypeScript, plus Git and web or API fundamentalsOne project you scoped, built, tested, and debugged that you can explain in detailHands-on experience using or evaluating coding agents in a real development workflowComfort reading logs, testing real user journeys, and iterating until a system works end to endClear written communication, careful judgment, and a bias toward ownership

04 / Bonus signal

Useful, not required

Experience with MCP, tool schemas, agent frameworks, or agent evaluationExperience building CLIs, developer tools, or browser-based productsFamiliarity with cloud services, containers, CI/CD, or infrastructure as codeOpen-source contributions or a deployed product used by other people

05 / What we offer

What you get

Direct mentorship on real agent-native product workHigh ownership over scoped, end-to-end engineering projectsFlexible remote collaboration with an option to work from San FranciscoWork across the complete loop from agent interaction through verified production deliverySupport for candidates working under valid OPT and eligible H-1B sponsorship

Application

Apply for this role

Tell us what you have built and how you know it worked. A concise application with real evidence is enough.

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