Backend Systems Engineer (Senior, US-Based, Python/FastAPI)

About Kernel

Kernel Intelligence is building the intelligence layer for commercial real estate (CRE) by turning unstructured documents—like leases, invoices, contracts, and diligence reports—into high-quality, decision-ready data. CRE is a $20T+ asset class, yet much of its critical information still lives in PDFs and siloed systems. We're fixing that with a modern, AI-powered platform designed for high-stakes, data-heavy workflows.

Our team combines deep industry experience (we previously built the leading real-estate compliance platform) with strong distributed-systems and AI infrastructure expertise. We're building the data foundation that will power the next generation of CRE intelligence.

About the Team

We're a small, senior team of builders who value clarity, curiosity, and decisive execution—shipping fast and intentionally without sacrificing correctness or reliability.

We are an AI-enabled data platform for mid-market companies who value enterprise-grade (multi-tenant) systems that are scalable, secure, reliable, predictable, and accurate.

You'll work directly with experienced engineers on well-defined, high-impact backend systems that form the foundation for next-generation AI and data products. Unlike many startups, “build fast and break things” is our anti-motto! And unlike many large companies, every line of code that every developer contributes has a meaningful impact on our business.

Tech Snapshot

• Python 3.12+, AsyncIO
• FastAPI / Starlette
• SQLAlchemy 2.x (async)
• Pulsar or Kafka (typed events, producers/consumers)
• OIDC/JWT, multi-tenant auth
• Kubernetes, fully cloud-native architecture
• GitOps/Terraform, Infrastrucuture and CI/CD
• OpenTelemetry, LGTM, structured logs, traces, and observability
• Distributed systems fundamentals: idempotency, retries, distributed locks, backpressure, consistency, etc.

About the Role

As a Backend Systems Engineer, you'll design, develop, and deliver the distributed systems and infrastructure that power our AI-driven platform. You'll work directly with our CTO to architect observable backend services, evolve core data and AI pipelines, harden and isolate multi-tenant workloads, and build integrations across internal and customer systems.

This is an engineering-led, application-development-focused systems role ideal for someone who enjoys software development just as much as software delivery. The ideal candidate is someone who can take ownership across the full software lifecycle—from shaping system architecture and writing production-grade services, to defining CI/CD workflows, provisioning infrastructure through GitOps/Terraform, and ensuring their services remain healthy, scalable, and observable in production. You should be as comfortable designing and reviewing technical approaches as you are implementing, deploying, and operating them.

Responsibilities

• Design and build distributed backend services and apis in Python (3.12+) using FastAPI + SqlAlchemy and modern async patterns
• Implement event-driven pipelines (typed events, queues, idempotent handlers) that are observable and resilient
• Model, evolve, and scale data schemas and pipelines in heterogenous persistence architectures (RDBMS, NoSQL, VectorDBs)
• Apply dependency injection patterns (e.g., dependency_injector or equivalent) for modular, testable systems
• Instrument everything — traces, metrics, structured logs — and use real runtime data to drive improvements
• Deploy and operate services on Kubernetes with platform engineers (GitOps/Terraform collaboration)
• Drive reliability through rigorous testing (unit, async integration, and functional tests)

Example Projects

• Add new FastAPI endpoints secured by OIDC scopes with full request-context propagation
• Build observable and distribute pipelines via Apache Pulsar (producers/consumers/readers) to support data and AI workflows
• Extend DI-based resource providers with auto-instrumentation hooks and namespace replication
• Tune async SQLAlchemy transaction performance and manage connection lifecycles at scale
• Define SLO-adjacent telemetry and use traces/metrics to uncover and resolve performance bottlenecks

What You Bring

• 5+ years of experience building backend or distributed systems
• Strong fluency in Python 3.10+ with async/await (we run 3.12)
• Deep experience with FastAPI or Starlette (middleware, request context, router composition)
• Hands-on skill with SQLAlchemy 2.x async engines, sessions, and repository patterns
• Solid understanding of distributed-systems fundamentals: locks, retries, backpressure, idempotency, consistency
• Practical experience integrating OIDC/JWT in multi-tenant applications
• Comfort with dependency injection frameworks/patterns
• An observability-first mindset — you instrument before you guess
• Experience building secure, scalable, and stable cloud-native services on Kubernetes with Istio Mesh (or alternative)

Bonus Points For

• Production experience with Pulsar or Kafka (typed schemas, batching, QoS tuning)
• Experience with Zitadel or other modern IdPs
• Familiarity with multi-tenant runtime schemas or dynamic data isolation; vCluster experience a huge plus
• Experience with AI-integration patterns and tools (i.e. LiteLLM, NotDiamond, etc.)
• GitOps (Argo CD preferred) and CI/CD (GitLab preferred) design and management
• Security-first practices: secrets hygiene (Vault preferred), auditable logging, least-privilege design
• Comfortable using AI-assisted development tools
• Experience with enterprise SaaS systems

Mindset

• You take ownership and deliver — you ship, measure, iterate, and operate
• You communicate clearly and collaborate well across engineering and product
• You favor clarity, instrumentation, and reliability over ceremony
• You enjoy solving foundational problems in complex systems

Why Join Us

• Work closely with a highly technical founding team that values design clarity and data-driven engineering
• Build core systems that power AI-enabled data products in a massive, under-modernized industry
• Have direct, visible impact in an early-stage environment
• Flexible remote role with competitive compensation