Senior Product Integration Engineer

Position Overview

Job Responsibilities

What You Will Own
Turn partner use cases into bounded, productized integration designs with clear data flows, authentication and authorization models, failure handling, versioning, ownership, and support plans.
Build, test, deploy, and maintain Workato recipes, custom connectors, API-based components, data mappings, and reusable integration templates.
Partner with engineering quality assurance to take demonstrable integrations to productized ones, including automated tests, data validation, secure credential handling, observability, alerting, deployment practices, and runbooks.
Work directly with partner engineering teams to resolve questions about APIs, schemas, authentication, rate limits, version changes, and operational responsibilities.
Collaborate with Product and Engineering to identify gaps in Agiloft APIs and platform capabilities, then translate recurring partner needs into clear product requirements.
Support selected sales opportunities by scoping requirements, validating feasibility, and building targeted demos or proofs of concept, with a focus on reusable partner capabilities rather than one-off implementations, and hand-off to Solution Engineering partners to scale demo ability.
Use AI coding and agent tools to accelerate API discovery, solution design, data mapping, custom logic, test creation, troubleshooting, and documentation. Review and validate all AI-assisted output before it is used in production.
Evaluate MCP and other agent-to-system integration patterns when they fit the use case, with appropriate identity, access control, auditability, and operational safeguards.
Provide escalation support for the integrations you own and create the documentation and runbooks that enable support teams to handle routine operations.
What Success Looks Like
Priority partner integrations move from discovery to supported production releases with clear scope, ownership, and technical documentation.
Reusable connectors and patterns reduce duplicate work and shorten delivery time for future integrations.
Production integrations are secure, observable, and maintainable, with predictable failure handling and effective operational handoffs.
Alliances, Product, and Solution Consulting receive timely, technically sound guidance on partner opportunities and constraints.
AI-assisted methods shorten discovery, build, test, and troubleshooting cycles without lowering quality or increasing support burden.
Other duties as assigned
 
 

Required Qualifications

No candidate will have used every product or protocol named in this description. We care most about depth in integration engineering, partner-facing judgment, and the ability to learn unfamiliar systems quickly.

Five or more years of experience designing, building, and operating production integrations across enterprise systems.

Strong hands-on experience with Workato or a comparable enterprise iPaaS, including building, deploying, monitoring, and supporting production workflows. Candidates with MuleSoft, Boomi, Tray.ai, Celigo, or similar experience will be considered if they can become productive in Workato quickly.

Deep practical experience with REST APIs, webhooks, JSON, pagination, rate limits, API versioning, error handling, and identity and access patterns such as OAuth 2.0, OIDC, signed JWTs, and API keys.

Production experience integrating at least one enterprise platform such as Salesforce, SAP, Coupa, NetSuite, Workday, DocuSign, or a comparable CRM, ERP, procurement, or e-signature system.

Ability to write and review custom integration logic in at least one language such as Python, JavaScript, TypeScript, Ruby, or Java.

Experience across the integration lifecycle, from requirements and technical design through automated testing, deployment, monitoring, incident response, and change management.

Strong partner or customer-facing communication skills, including the ability to explain tradeoffs, set technical boundaries, and turn business needs into implementable designs.

Demonstrated expert-level use of AI coding and agent tools in day-to-day engineering. You can explain specific workflows that improve speed and quality, how you verify AI-generated output, and how you protect confidential data and credentials
 

Preferred Experience

Deep Workato experience with custom connectors, environment management, deployment practices, monitoring, and platform governance, including Workato certifications.
Experience building productized partner or embedded integrations that are reused across multiple customers.
Experience in CLM, legal technology, source-to-pay, procurement, or adjacent enterprise application ecosystems.
Experience with event-driven or pub-sub integration patterns and cloud-native or serverless services.
Experience building or governing MCP servers, MCP clients, or other agent tool integrations with identity-aware access and audit controls.