Ai Rag Jobs in Riverside, CA (NOW HIRING)

Job Summary:
Lendistry is the nation’s largest minority-led lender for small businesses and commercial real estate, dedicated to creating economic opportunities for small business owners. They are seeking a Senior AI Engineer to lead the delivery of AI features, focusing on document intelligence, underwriting copilots, and borrower-facing AI experiences while mentoring junior engineers and shaping the shared AI platform.
Responsibilities:
• Deliver the Lendistry AI strategy.
• Lead the day-to-day delivery of agentic workflows, document intelligence, retrieval systems, and borrower- and operator-facing AI experiences.
• Contribute to and shape the shared AI platform — the prompt registry, tool-calling framework, evaluation harness, and inference routing layer.
• Own end-to-end LLM features — from requirements through design, implementation, evaluation, deployment, and production operation.
• Lead the design of new agentic workflows — LLMs that plan, call tools, evaluate results, and iterate across multi-step lending tasks with appropriate human-in-the-loop controls.
• Maintain, debug, and improve existing LLM-powered features already running in production.
• Fine-tune and adapt foundation models to Lendistry-specific tasks using various techniques.
• Design and build RAG systems end to end.
• Lead the development of document processing pipelines that extract structured data from financial documents.
• Design validation, confidence scoring, and fallback mechanisms for AI outputs.
• Diagnose and resolve agentic failure modes and build prevention patterns.
• Contribute to and shape the shared AI platform owned by the AI team.
• Design evaluation frameworks that measure model quality and output reliability.
• Instrument AI systems with observability.
• Manage cost and latency at the feature level.
• Partner with the AI team lead and Senior Staff Engineer to translate AI strategy into shipped features.
• Collaborate with product, credit, underwriting, and platform engineering to translate business requirements into reliable LLM system designs.
• Mentor junior AI engineers through design reviews and code reviews.
• Lead proof-of-concept work to validate new AI use cases.
Qualifications:
Required:
• 5+ years of software engineering experience, with 3+ years building and shipping LLM-powered applications in production.
• Expert-level Python for production systems — clean architecture, type-safe data modeling (Pydantic or equivalent), clean async patterns, and testable design.
• Deep hands-on production experience with at least one major LLM provider — AWS Bedrock, Anthropic Claude, OpenAI GPT, Google Gemini, or equivalent — including tool/function calling, structured output, and streaming.
• Proven track record designing and operating RAG systems end to end — chunking, embeddings, vector databases (Qdrant, Pinecone, Weaviate, OpenSearch, or pgvector), retrieval, and re-ranking — including measuring and improving retrieval quality.
• Demonstrated experience leading agentic workflows in production — LLM agents that call tools, reason across multiple steps, and autonomously complete multi-stage tasks with appropriate safeguards and audit trails.
• Hands-on experience with fine-tuning and adaptation — LoRA, QLoRA, instruction tuning, or preference tuning — and with rigorous evaluation of model outputs rather than demo-driven validation.
• Strong LLM tooling fluency — LangChain or LangGraph, LlamaIndex, DSPy, Hugging Face — with the judgment to pick the right tool and the willingness to build custom when the tool is wrong.
• Production experience with unstructured data — extracting, classifying, and generating structured outputs from text-heavy inputs, including documents, forms, and scanned images.
• Cloud and deployment depth — AWS preferred (including Bedrock), containerization (Docker), and hands-on experience with self-hosted LLM serving (vLLM, TGI, Ollama, or similar).
• Evaluation discipline — ability to design evaluation frameworks for non-deterministic systems, build golden sets, and reason about output quality at scale.
• Strong debugging instincts for LLM-specific failure modes — hallucinations, retrieval gaps, prompt drift, latency spikes, and cost regressions.
• API and service design experience — exposing AI capabilities as reliable internal APIs with clear contracts, error handling, and cost controls.
• Working knowledge of LLM security concerns — prompt injection, data exfiltration, output filtering, and secure inference for sensitive workloads.
• Discipline around PII and sensitive financial data — PII detection and redaction, data minimization, and deployment patterns that keep sensitive data inside Lendistry's trust boundary.
Preferred:
• Experience in fintech, lending, banking, healthcare, or another regulated or data-sensitive industry.
• Experience fine-tuning LLaMA or similar open-weight models on domain-specific corpora.
• Familiarity with document understanding models (LayoutLM, Donut, Nougat) and modern OCR tooling (Textract, Tesseract, or equivalents).
• Background in NLP tasks such as named entity recognition, classification, or semantic similarity.
• Experience building and operating shared AI platforms (prompt registry, evaluation harness, routing layer) consumed by multiple product teams.
• Experience mentoring engineers and leading design reviews.
• B.S. or M.S. in Computer Science, Machine Learning, or equivalent experience.
Company:
Lendistry is a lender and fintech company that provides business loans and grant access to small businesses. Founded in 2015, the company is headquartered in Los Angeles, USA, with a team of 201-500 employees. The company is currently Growth Stage.