Senior Software Engineer, Full Stack

Osano builds a data privacy platform that helps organizations manage consent and comply with privacy regulations. The Senior Software Engineer will own product work end to end, build and operate full-stack systems, use AI tools responsibly, and help strengthen engineering practices across the team.

Responsibilities:

• Lead multi-sprint projects from design through rollout: turn a loosely defined problem into a plan, break it into work that you and others can action, and deliver close to estimate
• Design systems that hold up, and write design docs and decision records that weigh the alternatives
• Partner with Product on scope: propose MVP cuts, phasing and tradeoffs, and measure whether what we shipped actually helped customers
• Use AI coding agents and assistants across the whole development lifecycle: exploring codebases, scaffolding, writing tests, debugging, refactoring, migrations and code review
• Stay accountable for every line you ship. You understand and can explain AI-generated code, and you know where AI shouldn't be trusted
• Turn repetitive engineering work into automation: scripts, agent workflows, and checks that save your team time every week
• Share what works: help define how our teams use AI tools, and how we review and verify AI-assisted work
• Use AI responsibly. Customer and personal data stays out of AI tools except through approved, privacy-safe paths. This is non-negotiable at a privacy company
• Build observability, feature flags and rollback paths into your work from the start
• Take turns on our triage and on-call rotation. Lead incident response for your team's systems, and see postmortem follow-ups through to completion
• Identify tech debt, size it, and make the case to get it into the plan
• Apply data minimization, residency, retention and access controls to the systems you design, especially those that handle customer and personal data
• Write secure code and fix vulnerabilities in your area as part of normal work
• Give code and design reviews that change outcomes, not just approvals
• Mentor engineers earlier in their careers, and make your team better at testing, reviewing and operating software
• Interview candidates and help us hire well

Requirements:

• This role is for an engineer who treats AI tooling as a real force multiplier
• You use coding agents and AI-assisted workflows to explore unfamiliar code faster, ship more and remove repetitive work
• You also have the judgment to verify everything that goes out under your name
• This is a remote role. You must be based in, and authorized to work in, the United States
• You care about the customer problem, not just the ticket, and you push for what actually helps
• You take full responsibility for outcomes, from the first design doc to how the feature behaves in production at 2 a.m
• You put team success ahead of individual wins, give direct and kind feedback, and treat documentation and async communication as first-class work
• You're curious and keep learning, especially as AI changes how software gets built
• You're excited about what it can do without overselling it or ignoring its limits
• You're comfortable with ambiguity and create clarity for others through good design and clear writing
• Typically 5+ years building and shipping production software. We care more about what you've owned than the number of years
• A track record of leading multi-sprint projects from design to production in a team setting
• Strong JavaScript/Node.js and React experience, and solid relational database skills (PostgreSQL preferred)
• Strong system design fundamentals: data modeling, API design, and naming the tradeoffs
• Experience owning production systems: on-call, incident response, observability
• Hands-on, day-to-day use of AI coding tools such as Claude Code, Cursor or Copilot, with concrete examples of how they made you or your team more effective, and how you verify their output
• Experience mentoring other engineers
• Strong written communication in a remote, async environment
• AWS experience (ECS/Fargate, Lambda, S3, RDS), especially multi-region or data-residency work
• Privacy, security or compliance-sensitive B2B SaaS (GDPR, CCPA, SOC 2)
• Building AI-powered automations, agent workflows or LLM-based product features
• Data and analytics tooling (Redshift, Athena) or event-driven architectures
• CI/CD, preview/ephemeral environments, end-to-end testing (Cypress)