About Workato

Workato delivers enterprise infrastructure for the agentic era redefining iPaaS and helping enterprises unify data applications processes and AI into a single governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500 Workatos cloud-native architecture connects every application data source and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. To learn more visit

Why join us

Ultimately Workato believes in fostering a flexible trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company.

But we also believe in balancing productivity with self-care. Thats why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.

If this sounds right up your alley please submit an application. We look forward to getting to know you!

Also feel free to check out why:

• Business Insider named us an enterprise startup to bet your career on

• Forbes Cloud 100 recognized us as one of the top 100 private cloud companies in the world

• Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area and 96th in North America

• Quartz ranked us the #1 best company for remote workers

Responsibilities

Were looking for an exceptional Staff Software Engineer to help define and build the distributed backend that powers our AI agent platform and the developer-facing products around it. Youll architect the event-driven services real-time integrations APIs gateways and platform capabilities that enable AI agents to reliably perform work at enterprise scale.

As a Staff Engineer youll operate beyond individual featuresyoull influence technical direction across teams establish architectural patterns and build the foundational systems that will support millions of users as Workatos AI platform continues to grow.

You will:

• Architect and build highly scalable event-driven backend systems that remain correct resilient and available under partial failure and production load.
• Design the core platform capabilitiesincluding APIs streaming services gateways CLIs and developer infrastructurethat power AI agents and developer-facing products.
• Lead the technical design and evolution of distributed systems making thoughtful architectural tradeoffs around scalability reliability developer experience and operational excellence.
• Integrate LLMs agent frameworks MCP RAG and other AI-native capabilities into production systems that serve enterprise customers.
• Drive initiatives end-to-endfrom product ideation and technical strategy through architecture implementation deployment observability and continuous improvement.
• Partner closely with Product Infrastructure AI Research and Developer Relations to shape the roadmap and developer experience for our AI platform.
• Establish engineering best practices through architecture reviews design leadership code reviews technical mentorship and raising the engineering bar across the organization.
• Build systems that are observable measurable and resilient with strong validation monitoring tracing and operational tooling.
• Influence platform strategy by identifying opportunities to simplify systems reduce operational complexity and improve developer productivity.

Requirements

Qualifications / Experience / Technical Skills

• 10 years of experience designing building and operating production backend systems at scale.
• Expert-level proficiency in Python with a demonstrated ability to write clean maintainable well-tested code and lead through hands-on technical execution.
• Deep expertise in distributed systems including designing for partial failure backpressure concurrency consistency fault tolerance and horizontal scalability.
• Extensive experience building event-driven streaming or real-time systems using messaging platforms pub/sub architectures queues or long-lived connections.
• Strong experience designing developer-facing products such as APIs SDKs CLIs gateways platform services or infrastructure that other engineers build upon.
• Production experience integrating LLMs agent frameworks MCP RAG or similar AI technologies into enterprise systems. Experience with LLMOps or ML infrastructure is highly desirable.
• Strong understanding of observability monitoring distributed tracing metrics logging debugging and operating services in Kubernetes and cloud environments.
• Excellent architectural judgment with the ability to evaluate tradeoffs across reliability scalability cost security and developer usability.
• Demonstrated experience driving technical direction across multiple teams and influencing engineering decisions beyond your immediate organization.
• Proven history of mentoring engineers leading architecture discussions and raising engineering quality across an organization.

Our stack: Python FastAPI Postgres Kubernetes AWS. You dont need experience with every technology but you should have a proven ability to learn new technologies quickly and apply them effectively.

What Were Looking For

• You think like a platform engineer and build systems that other engineers love to use.
• You have strong product intuition and understand that great developer experience is as important as technical correctness.
• You naturally take ownership of ambiguous problems and drive them through architecture implementation and long-term operation.
• You design for failure operational reality and scalenot just the happy path.
• Youre AI-native and actively leverage modern AI development tools while staying current with advances in agentic systems and LLM technologies.
• Youre an influential technical leader who elevates the engineers around you through mentorship thoughtful design reviews and clear technical communication.
• You enjoy working across organizational boundaries aligning stakeholders and helping define the long-term technical direction of the platform.