Careers at UseAgentic
We build high-throughput multi-tenant AI platforms, agentic workflow architectures, and resilient enterprise systems. Join our engineering team.
How We Build Systems
Real Production Scale
We run deterministic agent workflows processing thousands of concurrent tool executions, avoiding superficial prototype architectures.
Strict Multi-Tenancy
Engineered from day one for zero cross-tenant leakage with row-level security, isolated vector namespaces, and distinct encryption keys.
Clean Developer Tooling
Lightweight client loaders, clean OpenAPI contracts, automated linting pipelines, and high test coverage on every merge.
How We Hire
A streamlined, peer-reviewed evaluation process focused on real-world system architecture and production trade-offs.
Application Review
Evaluated directly by our technical architects and engineering team.
Initial Alignment
Introductory conversation to explore role alignment, culture, and expectations.
System Architecture & Deep Dive
Architectural whiteboarding on real production bottlenecks and stateful agent systems.
Managerial & Leadership
Strategic alignment on code standards, engineering velocity, and mentorship.
Background Verification (BGV)
Standard compliance verification powered by certified enterprise providers.
Formal Offer & Onboarding
Transparent compensation breakdown, equity agreement, and hardware delivery.
Engineering & Architecture Roles
Lead AI Systems Architect
Lead the architectural design of multi-tenant autonomous AI agents, LangGraph stateful loops, and Model Context Protocol (MCP) tool integrations.
Senior Distributed Systems Engineer
Design high-throughput vector ingestion pipelines, tenant-scoped schemas, and resilient event streaming over WebSockets.
Lead Full-Stack AI Engineer
Own the development of our multi-tenant SaaS console, zero-dependency embeddable widgets, and Next.js client experiences.
Lead Cloud Infrastructure Engineer
Drive cloud reliability on AWS, automated CI/CD pipelines, container orchestration, and multi-region deployment security.
Lead AI Systems Architect
Overview
Lead the architectural design of multi-tenant autonomous AI agents, LangGraph stateful loops, and Model Context Protocol (MCP) tool integrations.
Key Technical Responsibilities
- Architect multi-tenant agent execution graphs with cyclic loops and checkpointing.
- Integrate Model Context Protocol (MCP) servers for deterministic tool execution.
- Lead technical design reviews and establish engineering standards across the AI stack.
- Optimize vector indexing latency to ensure sub-100ms retrieval times.
Requirements
- 5+ years of software engineering experience with strong Python and FastAPI proficiency.
- Production experience with LangChain, LangGraph, or custom agentic loops.
- Deep understanding of multi-tenancy, vector stores, and distributed caching with Redis.
Engineered for Builders
Top-Tier Compensation
Competitive base salaries benchmarked against the 90th percentile, complemented by substantial early equity grants.
Workstation Allowance
Complete setup budget for latest M-series MacBook Pros, ergonomic seating, and external 4K displays.
Premium Health Coverage
Comprehensive health, dental, and medical insurance covering you and your immediate dependents.
Flexible Time Off
Generous paid leave, national holidays, and annual engineering team offsites in premier locations.
Frequently Asked Questions
Architecting something exceptional?
If your expertise covers stateful agent graphs, LangGraph orchestration, or high-throughput multi-tenant backends, send your code and profile directly to our founders.