Forward Deployment Engineer

AI EngineerRequired Skills & Experience: Typically 2–4 years of professional experience in software engineering, solutions engineering, integration engineering, automation engineering, or a related technical discipline, or equivalent practical experience. Experience taking software or automation from concept through implementation, testing, deployment, and production support. Working knowledge of AI agent architecture, AI agents, MCP (Model Context Protocol), tool-calling patterns, LLM applications, prompt workflows, evaluation approaches, and responsible enterprise AI practices. Strong proficiency in at least one modern programming language such as Python, JavaScript/TypeScript, Java, Apex, or C#. Experience designing and consuming REST APIs and working with JSON, authentication, webhooks, and asynchronous or event-driven patterns. Familiarity with source control, CI/CD, automated testing, observability, SQL, data mapping, and cross-system troubleshooting.Nice to Have Skills & Experience: Experience with Salesforce, MuleSoft, NetSuite, Quickbase, Workday, Splunk, Datadog, or comparable enterprise platforms. Experience building or operating AI agents, LLM applications, RAG systems, prompt workflows, evaluation pipelines, or agent tool integrations. Claude certification or demonstrated experience using Claude for enterprise engineering and automation use cases. Familiarity with MCP, tool-calling patterns, OAuth, secrets management, data-loss prevention, or AI security controls. Experience with event streaming, message queues, data lakes, distributed integrations, financial systems, CRM, or customer-support workflows.Job Description: Execute scoped initiatives across the AI and platform roadmap, from discovery and proof of concept through testing, production rollout, and hypercare. Build and integrate AI-enabled workflows, agents, and tools across Salesforce, MuleSoft, data platforms, finance applications, and CXO processes. Implement governed access patterns, including permissioning, data classification, human-in-the-loop controls, auditability, and approval-gated writes. Design and implement integrations using REST APIs, webhooks, queues, middleware, and reusable API client patterns. Deliver prototypes and technical spikes quickly, then harden successful solutions for security, scalability, maintainability, and supportability. Improve operational readiness through structured logging, tracing, monitoring, alerting, error handling, retries, dashboards, and runbooks. Participate in technical discovery, estimation, code reviews, testing, release planning, incident support, and retrospective improvement. Document solution designs, data flows, integration decisions, operational procedures, and known limitations so others can adopt and support the work.