Senior Enterprise AI Platform Engineer

Why Work Here

• Headquarters is in Charlotte, NC
• Recently expanded to nearshore
• isolved ranked for SMB Payroll in 2023 Sapient Report
• Voted top places to work in USA 2025

Job Description

The Senior Enterprise AI Platform Engineer is a senior, high-ownership builder role focused on production internal systems - not model training, research, or customer-facing product features, and not building the agents themselves. We are building a centralized gateway that internal agents and tools connect to, rather than a collection of one-off agents. You will build the control plane that handles authentication and authorization, model routing, tool-calling, and audit logging for every agent and internal tool that plugs into it. This role sits at the intersection of platform engineering and AI infrastructure. You will help define the platform's architecture and technical direction, mentor other engineers, and own the reliability and security of what we ship. If you are a strong backend and systems engineer who wants to go deep on the agent-infrastructure layer and help define what it becomes, this is that job.

Core Job Duties

• Architects and builds the core platform services that agents and internal tools connect to, building the infrastructure and backend agents need rather than the agents that consume them.
• Designs the centralized model - how the platform brokers access across multiple model providers, internal systems, and teams - with clear, vendor-neutral contracts between components.
• Owns the platform's authentication and authorization architecture, including token-exchange and on-behalf-of style patterns and integration with enterprise identity.
• Leads technical design of MCP server and client infrastructure, including toolboxes for agents with scoped MCP connections that execute requests in sandboxed runtimes.
• Drives observability, evaluation, and reliability practices for non-deterministic systems, including tracing, monitoring, cost/latency visibility, and audit-first logging.
• Sets technical direction and reviews designs for the platform team; mentors junior and mid-level engineers through code review, pairing, and architecture discussions.
• Partners with architecture, DevOps, and security leadership to ship secure, well-tested services following CI/CD best practices, representing the platform in cross-team design decisions.
• Uses AI-assisted development - agentic coding, spec-driven development, AI code review - as a core part of how you work, and helps establish adoption norms across the team.

Job Complexity

Having wide-ranging experience, uses professional concepts and company objectives to resolve complex issues in creative and effective ways. Acts as a go-to expert in AI platform infrastructure, centralized gateway architecture, and enterprise identity integration. Some barriers to entry exist at this level (e.g., department and peer review). The level at which a career may plateau for those not pursuing a staff or principal track.

Interaction

Works on complex issues where analysis of situations or data requires an in-depth evaluation of variable factors. Exercises judgment in selecting methods, techniques, and evaluation criteria for obtaining results. Networks with key contacts outside own area of expertise, including architecture, security, DevOps, and product stakeholders.

Supervision

Determines methods and procedures on new assignments and may coordinate activities of other personnel. Acts as an informal technical lead, setting technical direction and providing design review for the platform team without direct managerial authority.

Experience

Typically requires a minimum of 8 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or equivalent experience.

Minimum Qualifications

• Significant software engineering experience with a track record of designing, shipping, and operating production backend platforms - not just consuming services built by others.
• Direct experience building a platform or gateway that other teams' systems build on top of, ideally including a centralized architecture that managed access across multiple providers, systems, or tenants.
• Strong proficiency in Python.
• Deep backend and API experience, including REST APIs at scale, relational databases, and the tradeoffs involved in distributed systems design.
• Hands-on expertise with MCPs - building and operating servers, clients, and/or gateways, including tool registration, versioning, and lifecycle management.
• Solid understanding of auth/authz architecture: OAuth/OIDC, token exchange or on-behalf-of flows, and enterprise identity integration.
• A track record of mentoring or leading other engineers through code review, technical guidance, and helping junior and mid-level engineers grow.
• Comfortable owning technical direction and driving design decisions with minimal oversight.
• Fluent with Docker, Git, and CI/CD; comfortable on the command line and in cloud environments.
• Sound instincts around secrets management and authentication/authorization at enterprise scale.
• Experience with agentic software development - building with AI coding tools and agent-based workflows as a core part of how you work.

Nice to Have:

• Experience with Node/TypeScript or C#.
• Rust experience on the infrastructure or systems side - proxies, gateways, CLI tools, and other performance-sensitive components.
• Experience with at least one agent orchestration framework (e.g., LangGraph, CrewAI, AutoGen, Semantic Kernel) and understanding of common agent design patterns, even though this role builds the platform underneath rather than the agents themselves.
• Depth in multi-agent architectures - supervisor/worker patterns, hierarchical graphs, ReAct-style loops.
• Working familiarity with agent-to-agent (A2A) concepts and interoperability patterns.
• 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 and eval tooling for LLM systems (LangFuse, Prometheus, or similar).

About isolved

isolved is a leading provider of human capital management (HCM) solutions that combines modern technology with expert services and support. Purpose-built for People Heroes™, isolved gives HR, payroll and benefits leaders the tools and insights to streamline operations and deliver employee experiences that matter. isolved People Cloud™ is a connected HCM platform with built-in artificial intelligence (AI) and analytics that brings together HR, payroll, benefits, workforce management and talent management in one experience. Built on a legacy of 40 years in the market, isolved is trusted by more than 200,000 employers and used by 9 million U.S. employees, representing about one in 20 American workers. Visit www.isolvedhcm.com.