Senior Software Engineer, Data & AI

Overview Holly is the HR platform built for city and county government. We help local governments modernize how they hire, classify, and manage their workforce — work that directly shapes public services for millions of people. Our platform is live across 12 states with 60+ jurisdictions representing over 10% of the US population, including major counties like Santa Clara and Contra Costa in the Bay Area, Orange County in LA, and Snohomish County in Washington State. Demand is outpacing our team, and we're building to meet it. Overview Holly is a seed-stage team of 20+ operators with deep roots in public service, civic tech, and AI. We’ve raised $10M from leading investors in government technology and the future of work and have grown over 100X in the last year. We center public servants and impact in every decision, and we bring that same care to how we work here at Holly. About The Role We're hiring a Senior Software Engineer, Data & AI to build Holly's Data Platform. Local governments publish enormous amounts of public information salary schedules, job classifications, MOUs (Labor Union Agreements), budgets but it's scattered across thousands of websites and buried in messy formats: scanned PDFs, inconsistent HTML, spreadsheets, and everything in between. Turning that chaos into clean, searchable, trustworthy data is one of our biggest product challenges and deepest moats. What You'll Do You’ll own major parts of the Data Platform end to end, make high-leverage technical decisions, and build the data and AI infrastructure the rest of the product depends on. Own and Build the Data Platform Own the data platform end-to-end from raw public sources to clean, canonical datasets the product consumes Design the architecture, schemas, and standards for how Holly ingests, models, and trusts its data Partner with the founders to scope work, make tradeoffs, and drive delivery on our highest-leverage data initiatives Help set the long-term direction for our data foundation Build Ingestion & Normalization Pipelines Build systems that collect large volumes of public government data from thousands of local-government sources across the web Turn messy, heterogeneous inputs scanned PDFs, inconsistent HTML, spreadsheets into structured, normalized data (parsing, extraction, OCR, dedupe, entity resolution, schema mapping) Where it adds leverage, incorporate LLM-assisted extraction and embeddings into the pipeline Build for freshness, reliability, and scale so data stays current and trustworthy Model & Serve Data for the Product Design canonical data models and domain schemas that product engineers build on Expose clean, versioned, well-documented datasets the main app can reliably consume Own data quality, validation, lineage, and observability so downstream teams can trust what they're building on Build Search & AI Infrastructure Build semantic search and retrieval over large, changing government datasets Design inference APIs for extraction, classification, matching, and other AI-powered data processing Build evals, tracing, and fallbacks so model behavior is measurable and dependable Give product engineers clear interfaces for using data and AI capabilities Make It Automated & Intelligent Evolve pipelines from manual/one-off toward automated, self-healing, monitored systems Establish data-quality checks, alerting, and standards that keep the platform reliable as it grows Raise the bar on how we collect, validate, and serve data across the company How We Work Six principles drive how we build: Work on What Matters, Default to No every yes has a cost, so we save them for what moves the business and spend time on what matters. Question Everything, Be Opinionated titles don't settle arguments, the better case wins. Feel empowered to push back to everyone from the Head of Engineering to one of the founders. Obsess Over Craft quality first, and we don't trade it for a date. If you wouldn't put your name on it, it shouldn'''t end up in the codebase. Own It End to End if you build it, you own it: to production, in tests, and when it breaks. With great power comes great responsibility, with autonomy comes responsibility to make sure you own your work. Ship Small, Ship Often the smallest thing that stands on its own, kept reversible. Small ships compound, are easier to review and easier to fix if there are issues. Automate the Hurt, Not the Itch automate the recurring pain, the Toil aka things you do repeatedly that waste time, not the one-off annoyances or what seems ''"fun''" to automate. What You'll Have We'd love to talk if you're a senior engineer who can build data infrastructure and production AI systems, and knows how to turn messy real-world inputs into dependable product capabilities. The Essentials Have 5+ years building and shipping production software (or equivalent experience) Have a strong track record building and operating production data systems Have worked with large-scale, high-volume data ideally where lots of sources, users, or records make volume and reliability matter Are strong at data modeling and SQL, with experience designing schemas that others build on (Postgres a plus) Have built and owned ETL/ELT pipelines that handle messy, heterogeneous, real-world inputs (scraped data, PDFs, HTML, spreadsheets) Have built production search, retrieval, inference, or AI-assisted data-processing systems Know how to evaluate model quality and operate model-backed systems when outputs are probabilistic Bring a strong data-quality mindset validation, testing, monitoring, lineage, and reliability are core to how you work Take ownership and move fast you work independently, ship often, and thrive in early-stage ambiguity Have a growth mindset you learn quickly, and raise the bar through collaboration and clear standards Are pragmatic about tooling and comfortable working in (or ramping quickly into) a modern TypeScript/Postgres codebase Bonus Points Open source contributions to or maintainer of a widely used tool. Experience with large-scale web scraping / crawling, document extraction (OCR), or LLM-assisted parsing Experience with embeddings / vector search or supporting ML/AI data workflows Experience with analytical/columnar or warehouse stacks (ClickHouse, BigQuery, Snowflake) and/or streaming pipelines Experience in government, public sector, or civic tech Prior early-stage startup experience What You’ll Get End-to-end ownership. Architect and build data systems that define how the product works. Technical influence. Make the high-leverage calls on data architecture, standards, and how we scale. Commitment to Open Source. We are big believers in supporting open source, and provide a monthly day of Open Source where you can work on your favorite tool. In addition to internal hackathons and other projects Direct access. Work directly with the founders, with autonomy to drive major initiatives end-to-end. High-impact scope. Build the data foundation the entire product depends on, and see its power features customers rely on quickly. Public-service impact. Your work improves how local governments operate, helping millions of Americans access public-service careers. Competitive package. $170k-$216k base, 0.15-0.40% equity (L3), comprehensive health benefits (platinum plan with vision and dental), 401(k), paid parental leave, and a professional development stipend. Ready to Join Us? A few important notes: Location: This is an onsite role based out of our New York City HQ, four days a week (typically Mondays Thursdays), with some flexibility depending on the role and the candidate. Candidates must reside in New York or be able to commute to our NYC office. Applicants must be authorized to work in the U.S. without requiring sponsorship. Work Philosophy: We'''re an early-stage startup serving government clients with hard deadlines. There may be occasional off-hours work around launches or critical issues (rare and typically planned). We value flexibility and trust you to manage your schedule while maintaining a high bar for responsiveness and customer outcomes. Team Holly Holly is committed to building a diverse company and working with the broadest talent pool possible. We encourage applications from all races, religions, national origins, genders, sexual orientations, gender identities, gender expressions, and ages, as well as veterans and individuals with disabilities. If you need a reasonable accommodation during the application or interview process, let us know. The Pay Range For This Role Is 170,000 - 216,000 USD per year (hq) #J-18808-Ljbffr Tech Jobs for Good