Senior AI Engineer

ROLE The Senior AI Engineer builds and deploys production-grade AI agents that power ACQ Vantage. This role exists to turn AI capability into real, usable systems that drive business outcomes, not experiments or prototypes. You will work inside a lean Technology team to design, build, and ship agentic workflows that interact with internal tools, data systems, and user-facing products. You are responsible for taking ideas from concept to production, with a focus on reliability, speed, and practical value. This is a hands-on engineering role. You are writing code daily, iterating quickly, and working directly with modern AI tooling. You are expected to understand how LLMs behave in production, not just how they work in theory. RESPONSIBILITIES - Design, build, and deploy production-grade AI agents and end-to-end agentic workflows that solve real business problems across ACQ Vantage - Integrate LLMs with internal systems, APIs, and data sources, ensuring reliability, performance, and clean abstractions - Collaborate with product and engineering teams to prioritize, ship, and iterate on AI features quickly - Own and improve RAG pipelines across multiple Pinecone namespaces, including chunking strategy, embedding model selection, hybrid retrieval, and reranking - Build and maintain an evaluation framework, including golden datasets, automated quality scoring, retrieval metrics, latency benchmarks, and regression detection - Optimize model routing and tiering to improve unit economics while maintaining output quality - Instrument the AI layer for observability, including cost-per-request, token usage, quality signals, and anomaly detection REQUIREMENTS - 7+ years shipping production software systems (distributed backends, APIs, deployment pipelines, monitoring) - 2+ years building production RAG systems using vector databases (Pinecone, Qdrant, FAISS, or Weaviate), including embedding strategies, index management, and retrieval tuning - Built and deployed AI agents or multi-step LLM workflows in production, including tool use, orchestration, and system integrations - Built or contributed to an evaluation framework for an LLM-based product (retrieval quality measurement, regression detection, model-switching decisions based on data) - Reduced LLM API costs in production through model routing, caching, token management, or architectural improvements - Worked across multiple LLM providers (OpenAI, Anthropic, or equivalent) and understands tradeoffs in prompt behavior, token economics, and failure modes - Comfortable in both TypeScript and Python (our stack uses both) RESULTS - Production AI agents are deployed and actively used within ACQ Vantage - New AI-driven features move from concept to production in weeks, not months - Agent performance improves over time through structured testing and iteration - AI systems operate reliably with minimal failure or manual intervention - Engineering output translates directly into measurable business impact SCHEDULE - Work hours aligned with local timezone or Pacific timezone (8a-5p M-F) - Availability to support critical launches or events when needed LOCATION - Full-time, remote (US-based) - Quarterly on-sites in Las Vegas COMPENSATION: - $170,000 - $200,000 base salary - The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits (more details below). BENEFITS: We offer a comprehensive, evolving benefits package designed to support your health, family, and wellbeing. Some key offerings: - Flexible Unlimited Paid Time Off and Company-wide Holidays - Employer sponsored Medical, Dental, & Vision plans - $1,950 annual Employer HSA contribution - FSA options including dependent care - Employee assistance program and mental health resources - Employer match program for 401(k), eligible for both