About the Role
YOU will build and operate the LLM and agent infrastructure that powers production systems. You will contribute to scaling AI capabilities by designing and delivering core platforms such as the LLM gateway AI Hub and agent runtime with sandboxes You will work with security legal and product stakeholders to ensure governance and cost efficiency You will help shape the applied AI strategy and enable production agents
Requirements
- 8+ years of software engineering experience with at least 3 years building ML/AI infrastructure LLM systems or distributed platform services at scale
- Proven ability to lead multi quarter Staff level initiatives end to end with measurable platform wide impact
- Deep expertise in LLM orchestration patterns agent frameworks vector databases and model serving infrastructure across multiple providers
- Proven track record of cross functional partnership with security legal and product teams to ship governed production grade AI systems
- Fluency in Python and at least one systems language Go Rust or C++ with production experience building APIs microservices and runtime environments
- Uses 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 core platform systems including the LLM Gateway AI Hub and agent runtime with microVM sandboxes and a governed MCP gateway
- Drive the design and implementation of Knowledge Base infrastructure connecting data sources to auto provisioned vector and markdown stores queryable by any agent
- Lead AI FinOps capabilities including spend attribution governance and cost optimization across all AI workloads
- Partner with engineering security legal finance product and external partners to ship high impact platform capabilities
- Build evaluation and observability tooling including LLM as judge harnesses full tracing and feedback loops that let subject matter experts refine production agents
- Shape applied AI strategy by embedding with teams to build production agents applying fine tuning and traditional ML where it outperforms prompting
Benefits
- Health insurance
- Dental insurance
- Vision insurance
- 401(k) retirement plan
- Equity
- Bonus eligibility
- Remote work options