Senior Backend Engineer

• Own and ship product features end-to-end - from problem scoping through backend implementation to production
• Design and ship LLM agents that reason over large, messy, real-world organizational data, and make them reliable enough to trust
• Make key technical decisions across the product and backend - architecture, data modeling, APIs, tooling - and set the engineering quality bar
• Operate with full autonomy; in a team this small, your judgment directly shapes the product, the codebase, and the company
• Own high-risk, high-impact projects in a fire-and-forget work style with minimal hand-holding
• Shape the product direction alongside the founding team; translate customer needs into technical solutions
• Work closely with the founding team to support growing client engagements ranging from hundreds to thousands of employees

We’re looking for a generalist, high-agency engineer with 5+ years of backend experience building customer-facing products. You should have startup DNA - experience at top-tier startups (Series B or earlier) or as a founder - and a product mindset that ties technical decisions to business impact. We need someone who questions the “why,” drives projects end-to-end without oversight, and thrives in early-stage ambiguity with high ownership and fast iteration., * Must have Experience at top- tier startups (Series B or earlier) or as a founder; production- deployed software at a real company

• Must have Built and shipped customer- facing backend products at production scale

Hard skills

• Must have Deep Python expertise for production backend systems
• Must have Strong backend architecture and systems design skills

Baseline

Seniority

• Required 5+ years of experience with focus on customer- facing products

Work experience

• Required Set technical direction on ambiguous, high- impact projects end to end
• Required Generalist - not a pure infra/backend specialist; comfortable building across the product surface

Hard skills

• Required Proficient in API design and SQL data stores
• Required Hands- on experience building with LLMs or agentic AI systems

Soft skills

• Required Product mindset - ties technical work to business/customer impact, not just internal systems

Nice-to-have

Work experience

• Direct experience working with customers

Hard skills

• Fluent with AI coding tools; uses AI as a force multiplier without outsourcing thinking

Traits to avoid

• Infra, platform, DevOps, data or ML engineer as the current or most recent title, or a resume that is K8s, pipelines and models with no customer- facing product
• Long tenure at slow- moving orgs (govt, banks) or 6- 7+ years at big tech (Microsoft, LinkedIn, Apple, Cisco) with no evidence of independent initiative