- 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.
Highest-signal resume keywords
- 10+ Years In Software Engineering
- 5+ Years In Engineering Leadership
- Experience With Multi-Agent Orchestration Frameworks
- Hands-On Expertise With LLM APIs
- Production Cloud-Native Infrastructure Experience
ATS Optimization Keywords
Hard Skills
- Python
- FastAPI
- Kubernetes
- Docker
- Terraform
- Multi-Agent Orchestration
- Systems Design
- Distributed Systems
- Microservices
- Event-Driven Architecture
Soft Skills
- Team Leadership
- Mentoring
- Collaboration
- Continuous Learning
- Technical Excellence
Industry Keywords
- Financial Services
- Regulated Industry
- Platform Reliability
- Compliance
- Audit Requirements
Tools & Technologies
- LangGraph
- CrewAI
- OpenAI
- Anthropic
- AWS Bedrock
- SSE
- WebSocket
- AG-UI
- GraphQL
- Dbt