Architect scalable multi-tenant backend systems for AI agent workflows
Build an enterprise AI agent skill ecosystem
Implement an internal skill marketplace with search/discovery, quality scoring, security vetting pipelines, and approval workflows
Implement production-grade AI agent harnesses
Design feedforward guides and feedback sensors
Build and optimize context engineering systems
Develop observability frameworks with LLM-specific telemetry
Design layered guardrail architectures

Requirements

Bachelor's in CS, Engineering, or related field; advanced degree highly desirable
6+ years designing, implementing, and maintaining multi-tenant AI/ML systems in production
6+ years with cloud platforms (Azure, AWS) and backend systems (Kubernetes, Temporal, OpenSearch, PostgreSQL, Redis, Neo4j)
Deep understanding of Docker, Prometheus, and OpenTelemetry
Deep proficiency in Python, Java, or Go
Extra credit for effectively leveraging AI coding tools (Cursor, Claude Code, GitHub Copilot)
Proficiency in AI/ML and agentic frameworks (TensorFlow, PyTorch, LangGraph, CrewAI, AutoGen)

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

multi-tenant systemsAI/ML systemscloud platformsKubernetesTemporalOpenSearchPostgreSQLRedisNeo4jPython

Certifications

Bachelor's in CSBachelor's in Engineeringadvanced degree