Senior Backend Python Engineer
About Shelf
The enterprise is going agentic and we are creating a unique operating system for an automated future.
Most AI agents break the moment they hit real business complexity. That's why we built a platform that models a company's policies, workflows, and operational logic into an AI Data Model. Shelf enables AI Agents to reliably reason and deliver precise and reliable outcomes at scale.
We already have what most AI startups are still trying to earn: Enterprise customers such as Glovo, Nespresso, and HelloFresh, real production data, and tens of thousands of users. Customers trust us with operational knowledge: Our platform is highly reliable and secure with SOC2, HIPAA-ready security practices, and mature integrations in place.
Job Description:
This role is for a senior backend engineer who can design and own business-critical systems.
We want someone who is strong technically, communicates clearly, and has the judgment to make systems simpler, safer, and easier to evolve over time. Expect real ownership from system design through production.
The team is small enough for engineers to make real decisions. Career growth comes from ownership. Titles matter less than the scope you can carry. The people who grow fastest take responsibility for larger systems, drive customer outcomes, and strive to develop better engineering practices.
You solve ambiguous problems by shaping the right architectural approach, then ship, iterate, and keep it healthy in production.
We build AI-native. Engineers use Codex, Claude Code, and agents they build themselves. We invest in harness engineering through skills, CLIs, logs, traces, and orchestration.
This is a role for someone in a high-growth chapter of their career, who wants to do the best work of their life, learn fast, and win as part of a team going all-in on a hard mission.
Location - Warsaw, work from the office.
What You Will Own
Design and ship backend services, APIs, data flows, and background processing for production systems
Turn vague requirements into concrete technical plans, trade-offs, and execution
Own services after launch: reliability, observability, performance, and incident follow-through
Instrument what you ship and use production signal to iterate, not just to keep the lights on
Make sound decisions around system boundaries, data models, interfaces, and scaling paths
Work closely with product, frontend, and platform engineers to deliver end-to-end outcomes
Improve engineering leverage with AI tooling, automation, and internal workflows rather than using AI as a gimmick
Raise the quality bar through code review, design review, and pragmatic technical leadership
What Strong Performance Looks Like
You reliably move important backend work forward without waiting to be tightly managed.
Your systems are easier to operate and easier to change because of your design decisions.
You make smart trade-offs to unblock shipping - and you stand by those decisions.
You keep raising the bar on engineering excellence for yourself and everyone else.
What We Are Looking For
Strong senior-level backend engineering experience in production systems
Strong Python skills and the ability to design clean, maintainable backend code
Good distributed systems judgment: concurrency, failure handling, data consistency, async work, and service boundaries
Hands-on experience with cloud infrastructure such as AWS, GCP, or Azure
Comfort with database schema design and performance tuning for real-time and high throughput scenarios
A security-conscious approach to engineering: you build for enterprise-grade requirements, handle sensitive data carefully, and think about the security implications of the systems and AI workflows you ship
Ability to go from problem statement to design to production rollout with real ownership
Clear written and verbal communication. You can explain systems, trade-offs, and incidents without hiding behind jargon
AI-native working style. You already use AI tools in your daily engineering workflow, and you're excited to improve how the team builds, not just your own output: better tooling, workflows, and engineering leverage
Strong Plus
Experience building agentic systems: AI agents, tool-calling, orchestration, retrieval, or LLM-backed infrastructure in production
Working knowledge of TypeScript or the ability to contribute across the stack when needed
Experience shaping technical direction for other engineers, even without formal management responsibility
How We Evaluate Fit
We care more about ownership, systems judgment, and learning velocity than a perfect keyword match to our stack. If you are the kind of engineer who can take a messy problem and turn it into a strong production system, we want to talk.
What Shelf Offers:
B2B contract.
Company Stock Options.
Hardware: MacBook Pro.
Modern technical stack. Develop open-source software.
GitHub Copilot subscription.
A strong AI-native engineering environment with modern tools and room to experiment, including Claude Code, OpenAI Codex, and GitHub Copilot.
Why Shelf:
Becoming one of the defining companies of the AI age is a hard plan, and our leadership team has the rare mix of deep AI, knowledge-management, and enterprise SaaS experience to actually execute it
We have raised over $60 million in funding; our investors include Tiger Global, Insight Partners, Base10, and others
Recognized by Gartner as a Cool Vendor, with high-velocity growth powered by the most innovative product in our category
We love our customers and our customers love us. Ask a Shelf customer why, and they'll tell you it's our innovative capabilities and rock-solid reliability, that they enjoy working with our people, and most of all, the improvements they see in their business KPIs
We're building fast across three hubs: our New York HQ and our Product and Engineering centers in Warsaw and Lviv