Full Stack Developer

Who we are: Magellan AI gives brands, agencies and publishers visibility into the podcast advertising market and proof that it works. Our audio analysis and NLP track ad placements across thousands of shows. Our measurement and attribution tools connect those ads to the traffic and conversions they drive, so buyers can optimize campaigns and sellers can prove performance. We are looking to hire an experienced full-stack developer to join our team of seven engineers, to help launch a major new feature and continue to enhance our core product. The job has changed shape over the past year: most of our code is now drafted by AI agents — Claude Code and Codex — working under close supervision. We ship considerably more than we used to, and the scarce skill is no longer typing speed. It is knowing what to build, specifying it precisely, and being able to tell a correct answer from a convincing one. We are seeking someone who can handle many responsibilities, including: Adding new features to our Ruby on Rails application from top-to-bottom, full stack. You will work with operations and sales to help creatively design ‘good enough’ yet professional solutions. Directing AI coding agents through real work: framing the problem and its constraints, reviewing what comes back line by line, pushing back when a solution has outgrown the problem, and starting over simpler when that is the right call. You own the result regardless of who typed it. Increasing system/code quality by using practices such as TDD and refactoring. Quality around the core of the system has become more important as we scale up — and more important still now that the volume of code we produce has gone up. Writing the design down before the code: specs, architecture decision records, and product documentation for our operations team. Precise writing is a core engineering skill here, because it is both how we align with each other and how we brief our agents. Extending our own tooling — the skills, subagents and CLI helpers that encode how we work. Codifying a workflow so the whole team, and their agents, can repeat it is ordinary, reviewed work here. Building AI-facing product surfaces, like our Ad Intelligence MCP server, where the consumer of the API you design is a language model rather than a browser — with the authentication, policy gates and audit logging that implies. Enhancing usability of existing features via Turbo/Stimulus and other front-end improvements. Troubleshooting and fixing performance issues and complicated logic across Postgres and ClickHouse. Help simplify the system by bringing in smart design decisions. Experimenting and providing stopgap solutions for potential opportunities. Sometimes this involves quick and dirty solutions such as scripting, SQL exports, web scraping and the like. Sharing in providing operational support to make sure the system stays running and address any bugs. (Most usage is during normal business hours…we don’t do pagers.) Experimenting via internal hackathons to produce novel solutions and feature enhancements. Software Development at Magellan AI We adhere to a lightweight Agile development process. Every week, we have one formal product meeting with the revenue and operations team to reset priorities. The rest of the time is self-directed, with developers figuring out how to best solve any problems. In general, we are not working against any deadlines and make sure we take the time to do the job right. We practice Collective Code Ownership so that anyone can change any line of code and anyone can introduce new libraries or tools. We deploy code on a regular basis, usually every day. IOW, we ship fast and learn fast. A typical recent week is around 45 pull requests merged. Claude Code and Codex do most of the typing. Engineers spend their time deciding what to build, writing the spec, and judging what comes back. We work one task per git worktree, which lets each of us keep several agent sessions running in parallel on isolated branches. Managing that parallelism is a skill in itself, and we will teach it. Every change runs a review gauntlet before it merges: a local pre-PR review, a cross-agent review where Codex critiques Claude’s work, GitHub Copilot’s automated review (our branch rules will not let us merge until every thread is resolved), and a human reviewer. Different models catch different things. We invest heavily in the context our agents read: a repository-level conventions file, roughly two dozen project-specific skills, and purpose-built subagents. When someone learns something the hard way, it gets written down where the next agent will find it. Decisions get recorded as ADRs — we are up to 159 — and business rules live in a shared documentation repository linked into every worktree, so both people and agents can find out why the system works the way it does. We usually host a biweekly team retrospective to discuss ways to improve communication and collaboration. We make it easy for the tech-adjacent team members to run QA with clear documentation and steps to test our work. Tools and Technologies The main application is Ruby on Rails, hosted on Heroku, with Postgres as the primary database and ClickHouse behind our measurement and attribution product. Background work runs on Sidekiq. JavaScript in the application is minimal, and is mostly Turbo and Stimulus with some Bootstrap. A separate Python application handles all of the machine learning. Infrastructure is managed in Terraform across AWS, GCP and Cloudflare. Day to day we work in Claude Code and Codex, with MCP servers wired into ClickHouse, Postgres, New Relic, Rollbar, CircleCI and Trello so our agents can gather their own evidence. Qualifications: 3+ years of software development experience Expertise with Agile web development, with practices such as TDD and Refactoring Fluency working with AI coding agents day to day, or the obvious appetite for it. You do not need our exact toolchain, but you should be someone who reviews what an agent hands you rather than trusting it. Clear writing. You will be writing specs, ADRs and documentation read by people who are not engineers. Nice to Have: Ruby on Rails ClickHouse Python NYC-based Experience designing MCP servers or other LLM-facing APIs Background in ad tech Interest in the podcasting world Compensation and benefits: Competitive base salary and bonus structure Medical, dental, and vision coverage - individual coverage is free Company-subsidized family coverage Home office improvement reimbursement up to $500 per year Company laptop and external monitor 11 company holidays 20 PTO days for vacation, illness, and personal time More about Magellan AI Magellan AI is a first mover, early-stage SaaS startup funded by Brooklyn Bridge Ventures, C2 ventures and a few independent investors. The company was founded in 2016 by Cameron Hendrix (formerly Goldman Sachs) and Rex Madden (formerly Stride Consulting NYC). Magellan AI is the all-in-one platform for audio advertising intelligence, media planning, and measurement. Advertiser and agency media buyers rely on Magellan AI's audio media planning and measurement platform to discover, connect with, and analyze the performance of broadcast radio, podcasts, streaming audio, and YouTube. Publishers trust Magellan AI to grow audio ad sales with intelligence and performance measurement, powered by the world's largest database of podcast advertising data, covering over 60,000 podcasts. You will have the chance to shape the direction of a popular product in a rapidly evolving industry. We’re a remote-first company (though we’re still based in NYC). We offer great benefits for our size (medical, dental, equipment stipend, vacation), off-site retreats, as well as a generous options grant. Magellan AI is an equal opportunity employer; in keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on gender, sexual orientation, race, color, ancestry, national origin, religion, age, marital domestic partner status, physical ability, gender identity, disability status, or veteran status. Above and beyond discrimination and harassment based on 'protected categories,' we also strive to prevent other, subtler forms of inappropriate behavior (e.g., stereotyping) from ever gaining a foothold in our company culture. Whether blatant or hidden, barriers to success have no place at Magellan AI. #J-18808-Ljbffr Magellan AI