Director, AI Platform Engineering

Jobtailor

California (MO)

On-site

USD 250,000 - 360,000

Full time

14 days+

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Job summary

Jobtailor is seeking a senior leader to define and drive the AI agent platform roadmap, overseeing multi-agent orchestration, LLM routing, tool integration, and observability.

You will architect enterprise-grade multi-tenancy, security, and scalability, and lead a team of 8–15 platform engineers. Collaboration with product, data science, and business stakeholders will be essential to ensure platform reliability and performance across domains.

Qualifications

10+ years in software engineering.
5+ years in engineering leadership and management roles.

Responsibilities

Define and execute the technical roadmap for the AI agent platform (multi-agent orchestration, LLM routing, tool integration, observability).
Architect enterprise-grade multi-tenancy, security, and scalability.
Own platform reliability, availability, performance SLAs, observability, alerting, incident response, and capacity planning.
Lead architectural decisions using structured frameworks (DACI, ADR).
Build, lead, and mentor a team of 8–15 platform engineers.

Skills

Python

FastAPI

Kubernetes

Docker

Terraform

Multi-Agent Orchestration

Systems Design

Distributed Systems

Microservices

Event-Driven Architecture

Team Leadership

Mentoring

Collaboration

Continuous Learning

Technical Excellence

Tools

LangGraph

CrewAI

OpenAI

Anthropic

AWS Bedrock

SSE

WebSocket

AG-UI

GraphQL

Dbt

Job description

Define and execute the technical roadmap for the AI agent platform, including multi-agent orchestration, LLM routing, tool integration, and observability
Architect enterprise-grade multi-tenancy, security, and scalability
Drive platform standardization across LangGraph, MCP, and AG-UI protocols
Evaluate and integrate emerging AI technologies, LLM providers, inference optimizations, and agentic frameworks
Build, lead, and mentor a team of 8–15 platform engineers
Establish engineering best practices including code review, testing, CI/CD, and documentation
Foster technical excellence, ownership, continuous learning, prototyping, and delivery
Collaborate with product, data science, and business stakeholders
Own platform reliability, availability, performance SLAs, observability, alerting, incident response, and capacity planning
Deliver iterative platform capabilities through discovery-driven development
Manage dependencies across consuming teams and agent developers
Lead architectural decisions using structured frameworks such as DACI and ADR
Evaluate build-versus-buy-versus-integrate trade-offs
Champion developer experience through APIs, SDKs, documentation, and self-service tooling
Ensure AI agent platform security, compliance, and audit requirements

Requirements

10+ years in software engineering
5+ years in engineering leadership and management roles, managing managers or large teams
Deep experience building and operating production platforms, such as API, data, or ML platforms
Experience with multi-agent orchestration frameworks including LangGraph, CrewAI, and AutoGen
Strong knowledge of Model Context Protocol (MCP) or similar tool-integration standards
Hands-on expertise with LLM APIs including OpenAI, Anthropic, and AWS Bedrock
Experience with agent frameworks and prompt engineering
Strong systems design knowledge, including distributed systems, microservices, and event-driven architecture
Production cloud-native infrastructure experience at scale with Kubernetes, Docker, and Terraform
Python as primary backend language, including FastAPI and asynchronous patterns
Proven track record shipping platform products used by multiple internal or external teams
Experience leading technical strategy at the organizational level
Financial services or regulated-industry background preferred
Experience with SSE, WebSocket, or AG-UI preferred
Knowledge of data mesh/data platform architectures, GraphQL, dbt, or data catalogs preferred
Exposure to Module Federation or micro-frontend architectures preferred
Open-source contributions or AI/ML community leadership preferred
Experience scaling a platform from 0 to 1 through growth stages preferred

Core Competencies

Demonstrates expertise in architecting and executing AI agent platforms with a focus on multi-agent orchestration, security, and scalability. Proven ability to lead engineering teams, establish best practices, and drive platform reliability and performance.

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