Title: AI Developer
Location: Remote - Remote but must be able to Travel to Arizona around 2 times
Client Job DescriptionBuild the connected-agent foundation that automates Client Operations processes from intake through completion.
We are seeking an experienced AI Engineer to design, build, and scale multi-agent solutions for Client Operations. This role will connect specialized agents, enterprise systems, and workflow services to execute complete business processes while maintaining reliability, security, traceability, and appropriate human oversight.
WHAT YOU WILL DO
· Design multi-agent architectures that coordinate tasks, share context, and manage sequential and parallel workflows.
· Build end-to-end automation for quoting, vendor pricing, product research and validation, order processing, PO validation, customer communications, and ServiceNow case routing.
· Integrate agents with SAP, ServiceNow, Salesforce, Databricks, internal AI platforms, and customer or vendor APIs.
· Implement event triggers, dynamic task routing, agent handoffs, retries, exception management, human escalation, and workflow monitoring.
· Create reusable APIs, tool calls, connectors, and orchestration patterns that can support multiple Client Operations use cases.
· Partner with Product Managers, Client Operations SMEs, Data Engineers, Enterprise Architects, and platform teams.
· Embed security, privacy, Responsible AI, observability, auditability, and human-in-the-loop controls.
REQUIRED QUALIFICATIONS
· 5+ years of software engineering experience, including 3+ years delivering AI, machine learning, or generative AI solutions.
· Production experience designing agentic or multi-agent systems that automate enterprise workflows.
· Strong Python skills and experience with APIs, event-driven architecture, distributed systems, testing, and modern DevOps practices.
· Experience with agent orchestration frameworks such as Semantic Kernel, LangGraph, AutoGen, CrewAI, Copilot Studio, or Azure AI Foundry Agent Service.
· Hands-on experience with Azure AI services, Azure Functions, Logic Apps, Databricks, vector databases, and RAG architectures.
· Ability to design context sharing, task routing, dependency management, exception handling, fallback strategies, and human approval points.
PREFERRED QUALIFICATIONS
· Experience in Client Operations, order management, customer service, supply chain, or quoting workflows.
· Knowledge of SAP and ServiceNow integrations.
· Familiarity with MCP servers, tool-calling architectures, agent interoperability, and enterprise AI governance.
SUCCESS PROFILE| The successful candidate is an AI systems engineer, not solely a chatbot or prompt developer. They think in terms of Process → Agents → Orchestration → Automation → Business Outcomes, and can deliver governed, resilient agent ecosystems that complete measurable business workflows. |