Staff Software Engineer - AI Platform / Distributed Systems Engineer

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, Workato’s 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 www.workato.com

We're 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. You'll 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, you'll operate beyond individual features—you'll influence technical direction across teams, establish architectural patterns, and build the foundational systems that will support millions of users as Workato's 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 capabilities—including APIs, streaming services, gateways, CLIs, and developer infrastructure—that 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-end—from 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.

• 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 don't need experience with every technology, but you should have a proven ability to learn new technologies quickly and apply them effectively.

• 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 scale—not just the happy path.
• You're AI-native and actively leverage modern AI development tools, while staying current with advances in agentic systems and LLM technologies.
• You're 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.