Senior Enterprise AI Platform Engineer

• 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

The Senior Enterprise AI Platform Engineer is a senior individual contributor and builder role focused on production internal systems - not model training, research, or customer-facing product features. This role designs and implements the platform components that agents and internal tools run on, and brings the depth of experience to make architectural decisions, set platform standards, and mentor peers along the way.

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. We are building internal platforms that let teams across the company automate their own work and processes. At the Senior level, you are not only building; you are helping shape how we build, establishing patterns others follow, and owning the reliability and scalability of what we ship.

• Designs, builds, and maintains production-grade backend services and APIs (REST) that power agent orchestration, tool execution, and LLM integration for internal automation workflows - with an emphasis on scalability, reliability, and operational readiness.
• Architects and operates MCP server and client infrastructure, including tool registration, enterprise system integration, versioning, and lifecycle management; establishes patterns and standards that the broader team adopts.
• Leads integration of LLM services - streaming, structured outputs, tool/function calling - with robust error handling, retry logic, and cost/latency controls across multi-agent workflows.
• Designs and implements multi-agent and multi-step workflows using orchestration frameworks, evaluating tradeoffs between deterministic, role-based, and autonomous agent patterns.
• Owns observability and reliability for non-deterministic AI systems - defining tracing, monitoring, evaluation frameworks, and cost/latency visibility across the platform.
• Provides technical leadership and mentorship to engineers across the team, conducting code reviews, shaping architectural decisions, and raising the collective engineering bar.
• Partners with architecture, Dev Ops, and security to define and uphold platform standards for secure, well-tested service delivery following CI/CD and governance best practices.
• Identifies and drives platform improvements proactively, surfacing technical debt, reliability gaps, and architectural risks before they become production issues.
• 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.

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 agent platform infrastructure and AI systems engineering. 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.

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, and product stakeholders.

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