{"id":4129964,"url":"https://alion.io/job/avante-senior-software-engineer-2","title":"Senior Software Engineer","company":{"id":9865,"name":"Avante","domain":"avante.ai","url":"https://alion.io/company/avante","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Seattle, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"C#","optional":false},{"name":"Claude Code","optional":false},{"name":"Cursor","optional":false},{"name":"Java","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"TypeScript","optional":false},{"name":"Zscaler","optional":false}],"status":"live","first_seen_at":"2026-10-06T20:46:36Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-11-12T02:15:33Z","board_verified":true,"closed_at":null,"days_open":36,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":36},"description":"Avante is the enterprise AI platform for benefits teams. Benefits is one of the most complex, high-stakes functions in any company, and Avante’s purpose-built agents take on end-to-end benefits work, from checking vendor contracts against claims to preparing leadership reports to helping employees use and understand their benefits. Samsung Semiconductor, Real Chemistry, Zscaler and News Corp use Avante today to keep costs in check, support employees across the globe, and get more from their benefits investment.\nThe Role\nAs a Senior Software Engineer at Avante, you will own outcomes end-to-end: writing production code yourself where it matters most, and directing AI agents to handle implementation elsewhere, with full accountability for what ships either way. This is a hands-on, high-ownership role. We are looking for an engineer who solves problems pragmatically, whether that means building directly or steering an agent to do it well, and who brings the judgment and maturity to guide both human teammates and the AI systems increasingly doing implementation work alongside them.\nWhat You'll Do\nAI-Native Engineering\nDirect AI agents to handle implementation where appropriate, remaining accountable for what ships either way\nPush toward a \"touchless PR\" workflow where your judgment, not your keystrokes, is the bottleneck\nUse AI coding tools (Claude Code, Cursor, or similar) as a core part of how you build, with sharp instincts for where they help and where they don't\nHelp the team decide how and when AI agents get used, and mentor teammates on working effectively alongside them\nProduct & Customer Impact\nCollaborate closely with product, design, and engineering peers to deliver solutions that drive real business value\nMentor teammates by sharing context, giving feedback, and helping them grow their craft\nOwnership & Execution\nOwn outcomes across our stack, writing production code directly where it counts\nDesign and build scalable services, APIs, and user-facing features within our TypeScript monorepo\nIntegrate with external systems such as HRIS and ticketing platforms\nModel data, design schemas, and optimize queries to keep our systems fast and reliable\nBuild for production with a focus on observability, monitoring, and testability from day one\nParticipate in design discussions and code reviews\nWhat We're Looking For\nDeep expertise in backend engineering, with solid working knowledge of the other side\nProven track record of delivering complex features end-to-end in production systems\nDeep experience with TypeScript or other modern application development languages such as Java, C#, or Python\nFamiliarity with system architecture, API design, and scalable engineering patterns\nProficiency with databases (schema design, query optimization, performance tuning)\nActive, hands-on engagement with AI engineering, including real experience with LLM APIs, RAG, agent workflows, evals, or tool-calling, and a clear point of view on how AI has changed what you own and how you work. This goes beyond openness to using AI tools\nStartup or high-ownership experience: comfortable operating without a large team or established process behind you\nStrong product and customer judgment: a track record of trade-off calls that account for what's actually right for the end user, not just what's technically correct\nAbility to operate effectively in ambiguity, prioritize well, and balance speed with maintainability\nStrong communication skills and empathy for both teammates and end users\nWhat to Expect from Us\nInterview Process:\nInitial screen with our recruiters\nVideo Interview with our Engineering Manager\nTechnical interview focused on real-world problem solving (no whiteboard algorithms)\nOn-site interview loop:Team behavioral interview (60 min)\nSession with our Engineering Manager (60 min)\nFinal conversation with our CTO (30 min)\n\nThe base salary for this role is $170,000-$210,000. Where you land in that range depends on your experience, your skills, and how well your background fits what the role needs.\nWe also offer:\nEquity: Stock options, so you share in what we’re building\nHealth coverage: Medical, dental, and vision, with employee premiums covered by Avante\nUnlimited PTO: Take the time you need to rest and recharge, plus paid company holidays\n Retirement: 401(k)\nCommuter benefit: $150/month toward however you prefer to get to work\nAvante is an Equal Opportunity Employer. We’re building a diverse, inclusive team and welcome candidates of all backgrounds.\nHow We Work\nOur four values aren't aspirational. They translate into concrete operating tenets that shape how we make decisions every day.\nBeat Yesterday. We re-evaluate our own toolkit every quarter, because the workflows that made you effective three months ago may already be outdated. We act on 70% of the information rather than waiting for certainty. We timebox, execute, and iterate, getting work in front of real people quickly instead of polishing in isolation. And we own our output regardless of how we produced it. AI can get you 80% of the way there. Everything that goes out with your name on it is your responsibility to review, refine, and stand behind.\nEmbrace Type 2 Fun. We take on hard problems and find meaning in the work, even when it's uncomfortable. We assume good intent and follow up directly rather than venting in side channels. We celebrate wins loudly and specifically, naming the actual behavior so the whole team learns what great looks like. We are on by default, because we owe it to each other and to our customers to be available beyond what a regular corporate job would demand. And we do unscalable things today that build scalable advantages tomorrow: every hand-built account play and late-night proposal turnaround earns us the right to scale later.\nStay Hungry, Stay Curious. We expect everyone to be the expert on AI in their function before anyone asks them to be. The landscape changes weekly. When you learn something, teach it. Learn enough about adjacent functions to ask good questions. Ask the question you think is too basic, because in complex domains like benefits, the cost of a wrong assumption can be a lost account. And remember: curiosity without urgency is a hobby. Learning has to translate into action on a timeline that matches the opportunity.\nAct Like an Owner. We say the uncomfortable thing early, raising missed commitments or quality gaps directly with the person within 48 hours. We surface problems when they're small, not the week they become a crisis. Customer-facing work gets priority, always. 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