Note: The job is a remote job and is open to candidates in USA. isolved is an employee experience leader providing people-first human capital management technology. The Enterprise AI Platform Engineer will build and maintain production internal platforms, backend services, APIs, MCP infrastructure, LLM integrations, and multi-agent workflows that automate employee processes, while contributing to observability, reliability, security, and CI/CD practices.
Responsibilities
- Build and maintain backend services and APIs (REST) that power agent orchestration, tool execution, and LLM integration for internal automation workflows
- Develop and operate MCP servers and clients including tool registration, integration of databases and enterprise systems into agent workflows, versioning, and lifecycle management
- Integrate LLM services (streaming, structured outputs, tool/function calling) with robust error handling across agent workflows
- Implement multi-agent and multi-step workflows using an orchestration framework
- Contribute to observability, evaluation, and reliability for non-deterministic systems including tracing, monitoring, and cost/latency visibility
- Collaborate with architecture, DevOps, and security to ship secure, well-tested services following CI/CD best practices
Skills
- Strong software engineering fundamentals and a track record of shipping and maintaining production backend systems
- Proficiency in **Python**
- Solid backend/API experience building REST APIs at scale and comfort with relational databases
- Experience integrating LLM APIs into real applications
- Hands-on comfort with **MCP** (building and/or consuming servers and clients)
- Experience with at least one agent orchestration framework (e.g., LangGraph, CrewAI, AutoGen, Semantic Kernel)
- Understanding of common agent design patterns, and how the right choice for a given task ie deterministic workflows vs. role-based vs. autonomous agents
- Experience with agentic software development - building with AI coding tools and agent-based workflows as part of how you work
- Working familiarity with agent-to-agent (A2A) concepts and interoperability patterns
- Comfortable working in a cloud environment and on the command line; fluent with Docker, Git, and CI/CD
- Sound instincts around secrets management and authentication/authorization
- Experience with **Node/TypeScript** or **C#.**
- **Rust** from the infrastructure/systems-engineering side - CLI tools, proxies, and other performance-sensitive behind-the-scenes components
- Depth in multi-agent architectures - supervisor/worker patterns, hierarchical graphs, ReAct-style loops
- RAG and vector database experience (chunking, hybrid search, re-ranking)
- Redis-backed queues or other high-throughput backend patterns
- Experience shipping software in a regulated or governed environment (security, privacy, compliance)
- Familiarity with Azure and Microsoft Entra ID
- Observability/eval tooling for LLM systems (LangFuse, Prometheus, or similar)
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