Software Engineer (AI products & data engineering)

About Indigo

Indigo is building the AI Operating System for real estate. Within months of our first pilot, we already process more > 300,000 documents a month and > 1% of all US home transactions. And we haven’t even announced this broadly yet.

• We’re a second-time founding team whose last company reached $100M annualized revenue in the same industry.
• We’re building cutting edge technology that no one else in real estate has seen before, to power a scalable platform with multiple products on top of it.
• We’re building infrastructure so AI can handle the tedious parts of real estate, so that people can enjoy the fun parts.

About this role

We’re hiring a Senior or Staff-level backend‑leaning engineer who can design and ship elegant, reliable services. If you have < 5 years of professional software experience but feel you are a great fit, please still apply! We care about your productivity more than how many years you’ve worked.

• Backend work will be your primary lane (services, data, queues, durable execution), but you’re comfortable jumping into data pipelines, infra, and the occasional frontend task when the team needs it. Of course, you’ll have claude-code/codex/AI tools to help.
• You’ll push the boundaries of LLM‑powered backends (prompt/tooling infra, evals, latency/cost controls) while holding a high bar for software craftsmanship.
• We use TypeScript on both frontend and backend. We don’t expect you to have experience in everything we use, but we do expect strong TypeScript fundamentals and experience building robust, scalable systems.

Location

• Ideal location is in NYC. Our engineering and product team is in NYC, where we go to an office 3-5d a week in Soho.
• We’re open to hiring in Berkeley, CA where one of our founding engineers is based.

What you’ll do

• Design and ship backend services in TypeScript/Node + NestJS that power agent, team, and brokerage workflows
• Build reliable data pipelines (batch and streaming) to ingest, normalize, and validate large volumes of documents and events (OLTP→OLAP handoffs, schema evolution, idempotency)
• Architect event-driven systems with queues (e.g., SQS) and durable execution (e.g., Step Functions/Temporal-style patterns) to orchestrate long-running workflows
• Own LLM operations: prompt/tool versioning, function/tool use, caching, cost/latency budgets, evaluation harnesses, and guardrails
• Develop offline/online evals for model quality (golden sets, canary traffic, regression alerts) and wire them into CI/CD and runtime telemetry
• Expose clear, stable APIs (GraphQL Federation/REST) and evolve them safely with contracts and compatibility tests
• Instrument services for observability (tracing/metrics/logging), reliability (SLOs, retries/backoff, dead-letter handling), and performance
• Collaborate across functions (eng, product, design, ops, GTM) to translate customer feedback & fuzzy requirements into real products

What you’ll bring

• T-shaped generalist with depth in backend systems; breadth across data engineering, infra/DevOps, and enough frontend to collaborate and debug
• TypeScript/Node experience building production backends and APIs
• Strong data engineering fundamentals: data modeling, ETL/ELT, stream processing, and storage trade-offs (Postgres/OLTP, columnar/OLAP)
• Hands-on experience with queues and workflow orchestration (SQS/SNS; familiarity with durable execution patterns)
• Solid testing discipline (unit/integration/property tests), CI/CD, and observability
• Growth mindset: you learn unfamiliar domains quickly and enjoy picking up whatever the team needs next
• Founder-like mindset: ownership, scrappiness, and clear written/spoken communication

Our stack today

• TypeScript across the stack; NestJS services; GraphQL (Apollo Client/Federation) for APIs
• We use tons of AWS services, Postgres, Clickhouse, Kafka, BullMQ, Redis, etc.
• Observability: Sentry, CloudWatch, tracing/metrics
• LLM providers & tools: Closed & open sourced models, LangSmith

What we believe

• Small, highly talented teams with high ownership and low coordination overhead will run circles around larger, mediocre teams because of the power law of software. Even more true with AI coding tools.
• Quality compounds—well-designed software ships faster over time. Leverage AI to such as possible, but apply taste so you get speed not slop.
• AI and tools are improving at the fastest rate in history. Curiousity helps us keep up with the cutting edge and knowing what works vs what doesn’t yet.
• Broad skillsets amplify impact: the same person doing full-stack, data, AI/LLM, dev-ops dramatically increases impact and speed. Also true beyond engingeering skills–product & business sense give you judgement to build the right things
• We’re building something huge and the reality is that takes a lot of hard work and time. We support each other to sustain the pace (many of us have families—flexibility matters)

Equal Opportunity. Indigo is an equal opportunity employer and create an inclusive environment for all employees.