Sr. Integration Engineer

We are looking for an experienced Integration Engineer to join our FDE team. You will own the design, implementation, and production support of enterprise integrations that connect Automate with customers’ source systems — including Salesforce, NetSuite, Google Drive, SharePoint, SFTP, and custom REST/SOAP APIs — using iPaaS platforms including Boomi and Workato. This is a delivery-focused, customer-facing role. You will work directly with enterprise customers to gather integration requirements, translate them into scoped technical specs, build the integration, and own it through to production. You will also triage and resolve production failures with speed and clarity. Because this is an AI-first team, you’ll be expected to use AI-assisted development tools (e.g., GitHub Copilot, Claude Code, Cursor, or similar) as a default part of how you design, build, and debug integrations — not as an occasional convenience — while retaining full ownership of correctness and production quality.

● Own end-to-end integration builds on Boomi and Workato — from requirements through go-live — covering Salesforce→Automate deal ingestion, NetSuite billing sync, SFTP/cloud file-based ingestion, and Automate→SFDC sync-back.

● Design integration architecture that accounts for trigger strategy, error handling, deduplication, and partial failure scenarios from day one — not as an afterthought.

● Translate ambiguous customer requirements into clearly scoped integration specs with defined field mappings, edge cases, and acceptance criteria before writing any configuration.

● Coordinate UAT with customers, manage the go-live process, and own post-launch monitoring and stabilization.

● Build robust error handling into every integration: batch partial failure routing, retry with backoff, alerting, and dead letter queues.

● Use AI-assisted development tools to scaffold connector logic, draft field mappings, and speed up integration builds — while validating every AI-generated output against real source-system data before it ships.

● Spot places in the integration pipeline where AI/LLM-based processing (e.g., unstructured document classification, intelligent field extraction, anomaly detection) could replace brittle rule-based logic, and prototype those improvements with the platform team.

● Lead integration scoping calls with enterprise customers — asking structured discovery questions, surfacing unstated assumptions, and pushing back constructively when requirements are vague or out of scope.

● Communicate trade-offs, timeline impacts, and technical constraints to both technical and non-technical stakeholders in clear, direct language.

● Manage scope in writing: document all requirement changes, flag risks early, and keep customers aligned throughout the implementation lifecycle.

● Respond to production failures with calm, specific customer communication — stating what you know, what you don’t, and what your next step is.

● Speak credibly with customers about where AI is used in their integration (e.g., AI-assisted mapping, intelligent exception handling), and set accurate expectations about what AI automates versus what still requires human review.

● Triage integration failures by analyzing platform job logs, API responses, and field mappings — systematically distinguishing trigger failures from execution failures from downstream rejections.

● Reproduce issues against specific records (e.g., Salesforce Opportunity IDs, NetSuite transaction IDs) to isolate root cause before escalating.

● Identify recurring patterns across customer incidents and contribute to platform-level fixes or internal knowledge base documentation.

● Use AI-assisted log analysis and root-cause classification to accelerate triage, while knowing when an AI-suggested cause needs manual confirmation against the actual record before you act on it.

● Contribute improvements to Automate’s internal AI-powered on-call and triage tooling based on patterns you observe across customer incidents.

● 4+ years of hands-on iPaaS integration experience using Boomi and Workato, including production deployments at enterprise scale.

● Proven Salesforce integration depth: Opportunity-level data, ContentDocument/attachment retrieval, bidirectional sync-back, Salesforce API limits, and trigger behavior.

● Solid NetSuite integration experience: standard objects (Customers, Sales Orders, Invoices, Vendors), upsert vs. insert logic, and handling nulls from upstream systems.

● Strong understanding of integration error handling patterns: batch partial failure, document-level error routing, retry mechanisms, and deduplication strategies.

● Experience with file-based integrations: SFTP with PGP encryption/decryption, and cloud file stores (Google Drive, SharePoint) including auth differences and re-processing prevention.

● Ability to lead integration scoping independently with enterprise customers — asking discovery questions, documenting requirements, and managing scope boundaries.

● Proficiency with REST and SOAP web services, JSON and XML data mapping, and scripting (Groovy, JavaScript, or equivalent) for data transformation.

● Strong written communication skills — you document clearly, follow up in writing, and write customer-facing messages that are calm and specific under pressure.

● Comfortable using AI-assisted coding tools (GitHub Copilot, Claude Code, Cursor, or similar) as a core part of your daily development workflow.

● Able to critically evaluate AI-generated code, mappings, or triage suggestions — you use AI to move faster, never to skip validation. Strongly preferred

● Experience with both Boomi and Workato — Automate customers use both platforms.

● Boomi certifications (Professional Integration Developer, API Design, API Management) or Workato certifications (Solution Consultant, Implementation Specialist).

● Experience with Boomi Master Data Hub (MDH) or similar master data management patterns.

● Familiarity with NetSuite Advanced Billing (ZAB) or revenue recognition object models.

● Exposure to AWS services (S3, Lambda, webhooks) in an integration pipeline context.

● Prior experience in a SaaS Professional Services, Solutions Engineering, or Forward Deployed Engineering team with direct customer delivery accountability.

● Experience applying LLM/AI techniques to integration or data problems — e.g., AI-assisted extraction, classification, or anomaly detection in a production pipeline.

● Familiarity with prompt engineering or building lightweight AI agents/automations to support operational or support workflows.