About the Role
You will be the technical anchor for the CAE team, driving architecture and delivery of the Control Center platform, enabling safe and fast product integration. You will design MCP constructs, agentic guardrails, HITL workflows, and evaluation frameworks for secure autonomous operations. You will lead technical direction with the Engineering Manager and Product, authoring TDDs, running design reviews, decomposing complex initiatives into milestones, and raising the engineering quality bar through code review and mentorship. You will build highly reliable, secure distributed backend services, owning SLO definitions, observability instrumentation, incident response, and operational readiness for Tier-1 systems serving thousands of internal users and AI agents. You will partner across EAA engineering, Product Engineering, and Security Engineering teams to deliver cross-functional outcomes and drive shared platform primitives that eliminate duplicated infrastructure.
Requirements
- 8+ years of software engineering experience with a demonstrated track record architecting and delivering large-scale, high-traffic distributed systems, including deep proficiency in backend service design, API development (gRPC, MCP, GraphQL), and scalable microservices architectures.
- Proven ability to independently lead ambiguous, high-impact technical initiatives from whiteboard to production as a technical owner across complex, multi-team problem spaces, writing high-quality, well-tested code that sets the standard for others.
- Hands-on experience with cloud-native infrastructure including AWS, Kubernetes, Terraform, CI/CD pipelines, event-driven architectures (Kafka, MQ), distributed caching (Redis/Memcached), and SQL or NoSQL databases.
- Track record building secure, compliant internal tools or platforms with deep appreciation for security controls, access management, audit logging, and data governance in a regulated financial services environment.
- Experience building or integrating with agentic AI systems including MCP servers, LLM orchestration layers, RAG pipelines, HITL workflows, or evaluation and guardrail frameworks for production agentic workloads, with proficiency in Go and willingness to work across Python.
- Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.
Responsibilities
- Own the architecture and delivery of foundational platform capabilities including MCP tool registries, AI orchestration layers, risk-based access automation, and the away-team contribution model that enables product groups to build on Control Center safely and at speed.
- Drive the evolution of Control Center into an AI-agent-ready, headless operations platform by designing and implementing MCP procedure constructs, agentic guardrails, HITL orchestration, and evaluation frameworks for secure autonomous operations.
- Lead technical direction across the team in partnership with the Engineering Manager and Product, authoring TDDs, running design reviews, decomposing complex initiatives into deliverable milestones, and raising the engineering quality bar through code review and mentorship.
- Build highly reliable, secure distributed backend services, owning SLO definitions, observability instrumentation, incident response, and operational readiness for Tier-1 systems serving thousands of internal users and AI agents.
- Partner across EAA engineering, Product Engineering, and Security Engineering teams to deliver cross-functional outcomes and drive shared platform primitives that eliminate duplicated infrastructure.
Benefits
- Medical dental and vision insurance
- 401(k) retirement plan
- Equity
- Bonus eligibility