About Arlo:

At Arlo, we're passionate about creating innovative and reliable solutions that help people protect what matters most to them. Our team is dedicated to delivering products that exceed our customers' expectations, while always pushing the boundaries of what's possible in the world of protection technology. We believe that everyone deserves to feel safe and secure, whether they're at home or away, and we're committed to providing our customers with the peace of mind they need to live their lives without worry. Arlo’s deep expertise in AI- and CV-powered analytics, cloud services, user experience, product design, and innovative wireless and RF connectivity enables the delivery of a seamless, smart security experience for Arlo users that is easy to set up and interact with every day.

What You'll Do

- Build and improve the autonomous coding loop: task understanding, code generation, test execution, self-repair, and code review.

- Design the agent's context layer — codebase semantic index, retrieval, and knowledge base so the agent knows our systems as well as we do.

- Leverage LLMs to automate repetitive engineering work and provide smart developer assistance.

- Build scalable Python services and APIs powering internal developer tooling.

- Integrate the agent with the tools we actually use — GitHub, Jira, Slack, Buildkite, Confluence, AWS — via MCP and direct APIs.

- Measure agent quality: evals, benchmarks, and regression suites for agent behavior.

- Work closely with platform and product teams to find high-impact automation opportunities.

What You Bring

- 5+ years of experience in software engineering.

- Strong Python skills and hands-on experience with LLMs (Claude, OpenAI, etc.) — prompting, tool use, and agent orchestration.

- AI-driven development workflow. You use AI coding agents as your primary implementation method — not autocomplete, but the main worker.

- Strong testing discipline — you know that a coding agent is only as good as its feedback loop.

- Solid understanding of CI/CD pipelines and developer workflows.

- Working knowledge of cloud infrastructure (AWS) and IaC (Terraform, Helm).

- Autonomous, self-driven — can own an area end-to-end.

- A drive to use AI to transform how developers build, test, and deploy software.

Bonus Points

- Experience building internal tools or developer platforms.

- RAG and knowledge base work — embeddings, vector DBs, chunking strategies, keeping an index fresh against a moving codebase.

- Model fine-tuning / post-training (LoRA, SFT, preference tuning) and eval design.

- Observability and incident workflows (Datadog, Splunk, PagerDuty).

- Kubernetes and container orchestration.

- Contributions to open-source devtools or AI/ML projects.

Why This Role

- You build the agent, then use the agent to build the agent. Fast feedback, visible impact.

- Small team, high autonomy, direct ownership of the roadmap.

- Applied AI on a real codebase with real users — not a demo.

We’re committed to inclusivity and selecting the strongest candidate—no matter their background. Even if you don’t meet every listed qualification, we encourage you to apply. We’re happy to support growth in areas essential to the role. Interested in learning more about our workplace? Visit and follow our LinkedIn, and Glassdoor pages to read employee insights and get updates of what it’s like to be part of Arlo.

Arlo is proud to be an Equal Opportunity Employer. We value inclusion and are committed to inclusive, and harassment-free workplace. We prohibit discrimination and harassment based on all legally protected statuses in all hiring and employment.

We provide reasonable accommodations to applicants and employees with disabilities, who are pregnant or have a related medical condition, or who have sincerely held religious beliefs, observances, and practices. Pursuant to applicable state and municipal Fair Chance Laws and Ordinances, the Company will consider for employment qualified applicants with arrest and conviction records.