Senior AI Backend Engineer

Klarity•San Francisco, CA

19h•Onsite

About The Position

We're hiring Senior Backend + Applied AI Engineers to build the core systems that power Klarity's multimodal agents in real enterprise environments. This is a hands-on engineering role at the intersection of distributed systems and applied AI: you'll design and ship backend services that ingest messy real-world data, orchestrate model/agent workflows, enforce enterprise-grade security and deliver reliable outcomes at scale. You'll work closely with product, design, and other engineers to turn ambitious AI capabilities into production-grade features that Fortune 500 enterprises can depend on. We care deeply about engineering fundamentals (correctness, observability, security, performance) and equally about iteration speed - because in this space, only the teams who ship quality products & features at incredible velocity win. You'll set technical direction for critical subsystems and mentor engineers earlier in their careers - raising the bar for the entire team. Note: We do not require a CS or Engineering degree. We care about your ability to ship, your systems thinking, and evidence of strong execution - whether through production work, open-source contributions, research, or high-quality side projects.

Requirements

Backend engineer with sharp product judgment - You design and build services, APIs, data models, and infrastructure that are reliable, observable, secure, and fast. You can explain architectural tradeoffs as fluently as you can debate the right abstraction boundary. You optimize for outcomes - developer velocity, latency, correctness, uptime - and not just for elegance in the abstract. You've been the person teams turn to when a design review needs a tiebreaker.
Systems thinker with uncommon foresight - You see around corners. While solving today's stated requirements, you anticipate how services will need to evolve - functionally and non-functionally. You design for the future but build for the present, and you never let architectural dogma slow the team down. You've designed at least one system from scratch that other engineers now build on top of and is used in production at scale. You establish patterns and conventions that become team defaults.
Applied AI builder who ships to production - You're energized by LLMs, multimodal agents, orchestration protocols, and the messy work of making the entire AI stack reliable. You think instinctively in terms of evals, model regression tests, traceability, and exception handling. You've shipped multiple AI-powered features to production and have hard-won opinions about orchestration patterns, eval frameworks, and failure modes at scale.
AI-native developer across the entire SDLC - You wield tools like Cursor, Claude Code, and Copilot as extensions of your craft. You are extremely confident to run concurrent agents doing your chores reliably. You use AI to generate technical designs, scaffold APIs, draft schemas, write tests, and build migration plans. You've built custom workflows and internal tooling around AI-assisted development that others on your team have adopted.
Ship with velocity and craft - You find the shortest path to get features into users' hands while obsessing over the details that create trust. You balance the tradeoff between taking shortcuts, and just enough tech debt to pay off in the next sprint or two. You believe speed and quality aren't opposites - they happen together when you're thoughtful about how you build. You've developed a reliable intuition for when to cut scope versus when to invest, and you help the team make those calls with confidence.
Bring energy that elevates the entire team - You see gnarly distributed systems challenges as puzzles waiting to be solved. Your optimism, intensity, and passion for craft are contagious. You make everyone around you faster and more ambitious. You also frequently cross-pollinate learnings by seeking and sharing them with the team. You create leverage by unblocking others - through code reviews, architecture guidance, and clear technical writing that becomes team documentation.
4+ years designing and shipping production-grade products

Responsibilities

Build the backbone of Klarity's AI platform - Design, experiment, build, test, and deploy the backend services that power everything our users use. You'll own critical infrastructure end-to-end: from data ingestion and storage to API design, background processing, and deployment architecture. You'll make foundational decisions on technology choices, data models, and service boundaries that shape the platform's trajectory.
Turn AI pipelines into bulletproof workflows - Implement AI orchestration pipelines that hold up under real-world variability. You'll work with structured outputs, tool calling, state management, grounding, and other guardrails to ensure agents behave reliably at scale. Build comprehensive evals and regression tests so the team ships model changes with confidence. You'll define the orchestration patterns and evaluation frameworks the team standardizes on.
Design for the future, ship for today - Balance long-term architectural vision with relentless shipping cadence. You'll make pragmatic decisions that keep the codebase healthy and the product moving forward - knowing exactly when to take on deliberate tech debt and when to invest in foundations. You'll own the technical roadmap for your area and make the calls on when the team pays down debt versus pushes forward.
Build for enterprise security and scale - Design least-privilege access, strong tenant isolation, auditability, and secure data handling. You treat trust and safety as core engineering requirements, not afterthoughts. You'll define security and isolation patterns for new product surfaces and be accountable for the trust posture of your systems. You also design and build systems that scale gracefully as a feature grows from 0 → 1 → 10 → 100.
Multiply your impact across disciplines - You speak backend, AI, product, and infrastructure fluently. Partner with frontend and design to shape how AI capabilities surface to users, and turn ambiguous product ideas into concrete technical plans that drive better decisions across the team. You'll be a key voice in cross-functional planning, shaping what we build as much as how we build it.