About Shelf
There is no AI Strategy without a Data Strategy. Getting GenAI to work is mission-critical for most companies, but 90% of AI projects haven't deployed. Why? Poor data quality - it is the #1 obstacle companies have in getting GenAI projects into production.
We've helped some of the best brands like Glovo, Lufthansa, Herbalife, and Nespresso solve their data issues and deploy their AI strategy with Day 1 ROI.
Simply put, Shelf unlocks AI readiness. We provide the core infrastructure that enables GenAI to be deployed at scale. We help companies deliver more accurate GenAI answers by eliminating bad data in documents and files before they go into an LLM and create bad answers.
Shelf is partnered with Microsoft, Salesforce, Snowflake, Databricks, OpenAI and other big tech players who are bringing GenAI to the enterprise.
Our mission is to empower humanity with better answers everywhere.
Job Description:
As a Backend Engineer at Shelf, you'll architect and build the distributed systems that make enterprise AI actually work. While others are chasing AI hype, we're solving the unglamorous but critical problem that determines whether AI succeeds or fails: data quality at scale.
You won't just write code—you'll design architectures that handle petabytes of unstructured data, provision and optimize databases across multiple cloud regions, and build services that process millions of documents daily. Every architectural decision you make ripples through to the accuracy of AI systems at companies like Glovo, Lufthansa, and Nespresso.
This is systems engineering at its most demanding. You'll tackle challenges like building multi-tenant distributed systems with strict data isolation, implementing real-time data quality scoring at scale, and creating self-healing pipelines that maintain 99.9% uptime. Your services will integrate with everything from enterprise systems to cutting-edge LLMs, requiring both deep technical knowledge and pragmatic engineering judgment.
We obsess over backend quality because we're building the quality layer for AI itself. When your code elegantly handles edge cases, gracefully degrades under load, and self-monitors for anomalies, you're not just meeting engineering standards - you're directly preventing AI hallucinations and ensuring accurate answers for millions of end users.
We're a product company that ships fast without compromising on lasting quality. You'll work alongside proactive, ever-learning engineers in an environment where AI isn't just what we build—it's how we build.
The best engineers we know are drawn to problems that matter. If you're excited by the challenge of building the infrastructure that makes the AI revolution actually deliver on its promises, this role offers the rare combination of technical depth, meaningful impact, and the prestige of solving problems that the industry hasn't figured out yet.
Responsibilities
- Design efficient database schemas and distributed architectures that elegantly handle multi-tenant data isolation, horizontal scaling, and fault tolerance
- Create comprehensive technical specifications and architecture diagrams that clearly communicate system design decisions and trade-offs
- Define & maintain SLOs for your services and architect solutions that consistently meet them, even under peak load conditions
- Develop modular, composable components using Python, leveraging AI coding assistants to accelerate development while maintaining high code quality
- Transform ML models and LLMs into production-ready, reusable services with proper versioning, monitoring, and deployment pipelines
- Instrument services for performance metrics, track processing throughput, and build automated data quality and consistency checks
- Take full ownership of the systems you build, monitoring their health, optimizing performance, and ensuring they scale gracefully as data volumes grow
- Stay current with industry best practices in distributed systems, data engineering, and AI infrastructure—experiment with new approaches and share your findings with the team
- Contribute to our engineering standards and practices, mentor colleagues, and actively participate in our culture of continuous learning and improvement
- Build and maintain data pipelines across diverse storage solutions including S3, RDS/PostgreSQL, Elasticsearch, DynamoDB, and modern data warehouses
Requirements
- Over 4 years of professional software engineering experience, including more than 1 year specializing in Python
- Deep understanding of distributed systems, concurrency patterns, and event-driven architectures
- Hands-on experience with AWS or Azure cloud primitives - you've personally provisioned resources, configured services, and built scalable systems using the full stack (compute, storage, messaging, databases). Cloud certifications are a plus
- Comfortable working with diverse data stores (SQL and NoSQL), including schema design and performance tuning at scale
- Write well-structured, testable code with thoughtful abstractions and interfaces
- Strong problem-solving skills and genuine curiosity - you don't wait for instructions but proactively identify problems and propose solutions. You're never satisfied with "good enough" and constantly refine your tools and approaches
- Experience with AI coding assistants (GitHub Copilot, Claude, etc.) and eagerness to push the boundaries of AI-assisted development. Part of this role involves creating AI agents to automate portions of the engineering workflow
- Familiarity with service cataloging and documentation tools like OpsLevel or similar platforms
- Upper-Intermediate or better English skills for technical communication and documentation
- Present your work effectively both verbally and visually, creating clear architecture diagrams and well-structured documentation
- Bonus: hands-on experience with NLP, unstructured data processing, Node.js/TypeScript, or RAG pipelines
- Bonus: experience with CQRS, distributed processing techniques, or building ML infrastructure
What Shelf Offers:
- B2B contract.
- Company Stock Options.
- Hardware: MacBook Pro.
- Modern technical stack. Develop open-source software.
- GitHub Copilot subscription.
- Access to Claude Code, OpenAI Codex, TypingMind, and MCP Servers.
Why Shelf:
- GenAI will be at least a $4 Trillion market by 2032 and Shelf is a core infrastructure that enables GenAI to be deployed at scale
- Our Leadership Team has deep knowledge management and AI domain expertise and enterprise SaaS background to execute this plan
- We've been helping our customers prevent knowledge mismanagement since our founding in 2017
- We have raised over $60 million in funding and our investors include Tiger Global, Insight Partners, Connecticut Innovations, and others
- We have high velocity growth powered by the most innovative product in our category, 3X growth for 3 years in a row
- We now have over 100 employees in multiple U.S. states and European countries, and we have ambitious hiring goals over the next few months
Our Values:
Quality - We’re united by our focus on world‑class Quality. Quality in all things – starting with everything that leaves your desk. Everything you touch – every email, report, campaign, and piece of code – should be outstanding. Your work product should blow people away. Having people look at what you’ve done and say, “Wow.” That’s the standard here. Remember that how you do anything is how you do everything. Focus on craftsmanship—your ability to make things better.
Momentum - for us means that you should know that the things you’re responsible for are moving forward. When you look around and see something that’s stalled, get it moving again. We pride ourselves on “ball movement.” When your boss or team leaves you with something, they should return to see measurable progress. Small, continuous movement is our recipe for success. Constantly look for how to make the work around you move forward. We want you to initiate solutions, ideas, and progress. Don’t wait for it to come to you—reach out and create movement. All the time.
Accountability - We expect every team member to feel that they are accountable for more than anyone might normally expect. Each of us should feel real responsibility for things even at the edge of our control. We consistently share and align on expectations, give each other open and respectful feedback, and use those two drivers to ensure that every agreement we make with one another is clear and complete.
Hard Work - We’re here to do something difficult together. We care intensely about the mission and we expect that from our teammates. That care means that we work hard here. Hard work comes with long hours, extra effort…and real opportunity at Shelf. Your passion for creating and sustaining output is a part of our DNA. Support each other, cheer each other on, drive the mission forward. Great teams sustain intense effort together to win.
Learning Agility - We’re innovating in one of the fastest‑moving spaces in history at a time of accelerating global change. That’s incredibly exciting and requires each of us to commit fully to learning each and every day so that we can be the best at what we do. None of us know everything. All of us can learn anything. Staying open and constantly curious is a key success driver at Shelf. It also requires humility. We prize people who are consistently humble and open to making mistakes and growing from them. Recognize also that learning itself is a skill…we need you to be really good at it. Keep dialing in your own understanding about how you learn best and push yourself to keep growing.
Adapt and Thrive - Overcoming challenges lives deep in our DNA. We have a proud history of understanding and living the reality that obstacles are our opportunities…they’re the key to our success. Change is a constant in our business and fighting change is counterproductive. We need you to be good at being uncomfortable and understand that discomfort is the key to growth. Cultivate your own ability to adapt and know that struggling well is something you’ll share with every team you’re on at Shelf. Our company stories are about thriving through real difficulty…together.
Win Together - We win or lose as a team. Always. Everything you do here is connected to the rest of the organization. Part of our shared team environment demands full honesty…real candor and directness with one another. We expect you to constantly be thinking about how to support your teammates and the company, always acting in service to our shared mission and what’s best for the organization as a whole.