Senior AI Engineer – LLM Systems & RAG Optimization

Senior AI Engineer – LLM Systems & RAG Optimization Location: Remote (Global) Type: Full-Time or Contract Company: Texas Sports Academy About Us Texas Sports Academy is building the future of education for athletes. We combine elite athletic training with serious academics — and we’re scaling rapidly. We already have a parent-facing AI SMS chatbot live in production. It works. Now we need someone exceptional to make it world-class. This is not a “call the OpenAI API” role. This is a systems, evaluation, and scaling role. What You’ll Own You will improve and scale our parent SMS AI chatbot used by thousands of families. This includes: • Optimizing and redesigning our RAG architecture • Reducing hallucinations and irrelevant retrieval • Improving latency and token efficiency • Building robust evaluation pipelines • Implementing LLM observability and monitoring • Designing cost-efficient scaling infrastructure • Improving conversation memory and routing logic • Hardening guardrails for real-world usage You will operate as the AI systems architect for this product. Required Experience You must have real production experience building and scaling LLM systems. We’re looking for: • 3+ years in applied ML or NLP • Strong Python skills • Deep experience with RAG systems • Experience with vector databases (Pinecone, Weaviate, FAISS, etc.) • Experience optimizing chunking & embedding strategies • Experience evaluating LLM systems beyond subjective review • Familiarity with LLM observability tools (LangSmith, Helicone, PromptLayer, etc.) • Experience deploying scalable AI systems in production You should be able to: • Architect a full RAG pipeline from scratch • Diagnose retrieval failures • Build evaluation datasets • Optimize for cost at scale • Explain tradeoffs clearly Bonus Points • Experience with SMS-based AI systems • Experience with multi-model routing • Experience with context compression • Startup experience • Strong system design background What Success Looks Like Within 90 days: • Hallucination rate meaningfully reduced • Retrieval accuracy measurably improved • Cost per conversation reduced • Clear evaluation metrics implemented • Observability dashboard live • Scalable architecture roadmap in place Take-Home Evaluation You’ll be asked to: Audit our existing SMS chatbot and deliver a structured improvement plan including: • Architecture critique • Retrieval optimization suggestions • Hallucination reduction strategies • Scaling plan • Metrics & evaluation framework • 30 / 60 / 90-day roadmap Time expectation: 4–6 hours. Compensation Competitive. Open to global talent. Contract or full-time available. If you’ve built real AI systems — not demos — we want to talk. Job Type: Full-time Pay: $250,000.00 - $300,000.00 per year Work Location: Remote