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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in AI and LLM systems, with a focus on model fine-tuning, deployment, and architecture. Proven ability to lead complex projects while ensuring quality, cost management, and effective communication across teams.
Highest-signal resume keywords
AI And LLM ExperienceModel Fine-TuningProduction Experience With LLM SystemsPython And Rust ProficiencyEnterprise-Level Design And Architecture
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Design and build an AI-powered insurance marketplace that AI agents use to shop on a person’s behalf
- Own the end-to-end technical architecture, including models, model serving, MCP server, tools, and integrations with other AI platforms
- Decide where model reasoning runs, which models to use, how they are packaged, and how AI platforms connect
- Fine-tune open-weight models and determine when tuning, retrieval, or prompting is appropriate
- Deploy and operate the agent and MCP server with reliability, speed, affordability, versioning, and rollback capabilities
- Build programmatic evaluation sets, guardrails, and monitoring for quality, drift, cost, and speed
- Design data models, request and response payloads, exposed reasoning, and trust signals with the AI product lead
- Establish engineering patterns and standards and document code and architecture
- Monitor inference costs and make scalability trade-offs
- Help publish code, architecture, and findings
- Mentor engineers and provide leadership with regular visibility into technical progress and risks
Requirements
What you’ll need- Deep, current, hands-on experience in the AI and LLM space
- Experience fine-tuning and running open-weight models, including LoRA, QLoRA, SFT, DPO, or similar
- Production experience serving LLM systems reliably, pinning versions, rolling back changes, and managing inference costs
- Enterprise-level design and architecture experience
- Experience leading and delivering large, ambitious projects
- Strong grasp of evaluation, guardrails, failure modes, and monitoring quality, drift, cost, and speed
- Fluency with model serving, containers, orchestration, and monitoring on at least one major cloud
- 8+ years in engineering, including senior or lead ownership of complex technical systems and hands-on machine learning or LLM work
- Hands-on fine-tuning and deployment of open-weight or open-source models in production
- Strong Python and Rust skills, plus fluency with the modern LLM stack
- Strong strategic thinking and methodical execution
- Excellent communication across technical and non-technical levels
- Current, unrestricted work authorization in the United States
- This role is not eligible for immigration sponsorship
Benefits
Comp & perks- Variable cash bonus programs, based on eligibility
- Equity, based on eligibility
- Comprehensive health, welfare, and wellbeing benefits, based on eligibility
- Additional compensation components, including OTE structure and bonus targets, as applicable
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Model ServingOpen-Weight ModelsContainersOrchestrationMonitoringMachine LearningTechnical ArchitectureEvaluation And GuardrailsInference Cost ManagementVersion Control
Soft Skills
Strategic ThinkingMethodical ExecutionExcellent Communication
Tools & Technologies
Cloud PlatformsMCP ServerAI Platforms
Industry Keywords
AI MarketplaceTechnical LeadershipEngineering PatternsQuality MonitoringScalability Trade-Offs