Senior MuleSoft Engineer

Green Irony•Raleigh, NC

11h•Remote

About The Position

At Green Irony, we exist to turn AI into Actual Intelligence—accelerating outcomes and proving that complexity is optional. We hire people who automate first, ask permission never, and treat ownership as a default setting. If you’d rather govern yourself than be governed by layers of project managers, welcome home. As a Senior MuleSoft Engineer, you will design and deliver API-led integration solutions on Anypoint Platform — directly with clients, from discovery through go-live. You'll drive architecture decisions, protect margin through scope discipline, and build the kind of trusted client relationships that turn one engagement into many.

Requirements

Consulting Services Experience: 3–5+ years delivering integration programs for external clients — leading discovery/estimation, shaping SOWs, managing stakeholders from exec to dev, and owning delivery KPIs. This is non-negotiable. Internal IT delivery experience does not substitute.
Client-Facing Ownership: Proven track record of managing client relationships through the full engagement lifecycle — including difficult scope and change-order conversations that preserve both trust and margin.
API & Microservices Architecture: Expert in designing, implementing, and maintaining distributed, scalable API-led solutions using MuleSoft and industry-standard patterns.
MuleSoft Platform Mastery: Advanced hands-on with Anypoint Platform, including DataWeave 2.x, CloudHub 2.0, Runtime Fabric, Flex Gateway, and Anypoint MQ.
Autonomous Execution: Demonstrated ability to self-govern in flat, PM-free consulting environments — independently scoping, prioritizing, and delivering without hand-holding. If you've only worked in highly structured orgs, be honest with yourself about this one.
AI/LLM Tools & Automation: You don't just tolerate AI tools — you seek them out. Cursor, LLM-based assistants, AI-powered static analysis — these are in your daily rotation, not your LinkedIn bio.
DevOps, CI/CD & Automation: Strong experience with CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins), containerization (Docker/Kubernetes), and cloud-native deployment strategies.
Security & Integration Standards: Advanced knowledge of RAML/OAS, OAuth2, JWT, TLS, and encryption best practices.
Programming Proficiency: Skilled in Java and Node.js, with the ability to refactor legacy codebases into clean, maintainable solutions.
MuleSoft Certifications: MuleSoft Certified Developer – Level 1 required; Architect or Integration Professional certifications strongly preferred.

Nice To Haves

Experience integrating Salesforce, AWS, or other SaaS/ERP platforms.
Familiarity with event-driven architectures (Kafka, Pub/Sub).
Hands-on experience or strong interest in AI/ML pipeline design or integration.

Responsibilities

Lead technical design, implementation, and deployment of large-scale MuleSoft integration and API solutions (CloudHub 2.0, Runtime Fabric, Anypoint MQ, Flex Gateway, or on-prem).
Develop and maintain DataWeave scripts, Mule flows, and CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins).
Enforce architectural and security standards (RAML/OAS, OAuth2, JWT, TLS, encryption).
Monitor and optimize integrations for performance, scalability, and maintainability.
Lead discovery sessions, shape estimates, and contribute to SOW development — you are the technical voice in the room with the client.
Own delivery KPIs: on-time rate ≥90%, estimate variance ≤±15%, client satisfaction scores that earn repeat business.
Proactively communicate status, risks, and decisions — updates go out without being asked.
Build trusted relationships that make scope conversations easier, not harder.
When scope creeps (and it will), you call it — with a path forward, not just a flag.
Provide coaching and technical guidance to engineers; lead code reviews and process improvements.
Operate as a peer, not a manager — lift standards through quality of work and direct feedback.
AI as Your Default Toolchain: You reach for your AI-enabled IDE, LLM-based assistants, and AI-powered static analysis before anything else — not as a shortcut, but because better tools produce better outcomes. You don't write code you can automate reviewing.
Integration Workflows, Augmented: You actively prototype and deploy AI/LLM services inside integration solutions — summarization, document parsing, intelligent transformation, synthetic test data generation.
Advance automation with AI-assisted code review and LLM-based development platforms to accelerate delivery and lift code quality across the team.