Lead AI/ML Engineer

Overview Toyota Financial Services (TFS) is part of Toyota, a world‑renowned brand that leads the future of mobility. We are seeking a Lead GenAI Developer to build cloud‑native, AWS‑based GenAI and LLM systems that deliver best‑in‑class customer experiences. The role is based in Plano, TX. Responsibilities Design scalable, secure AWS architectures (VPCs, IAM, networking, S3, EKS/ECS/Fargate, Lambda) and manage infrastructure using IaC (Terraform/CloudFormation), CI/CD, and observability tooling. Lead integration of API‑based and self‑hosted LLMs, implement RAG solutions, optimize inference cost/performance, and operate MCP servers and model‑serving infrastructure. Develop prompt engineering strategies, reusable templates, and evaluation frameworks; collaborate with product teams to iterate and improve prompt quality. Implement and maintain vector stores (OpenSearch, Pinecone, Milvus, Qdrant) and design efficient similarity search, retrieval workflows, and indexing strategies. Build robust ETL/ELT and document ingestion systems—batch and streaming—including data transformation, cleaning, metadata extraction, and embedding generation. Develop microservices and serverless components to support low‑latency inference, asynchronous processing, and event‑driven architectures. Build core backend components in Python, leveraging LangChain, LlamaIndex, Hugging Face, and related tooling. Enforce data privacy, secrets management, RBAC, and cost governance best practices while collaborating across teams, mentoring engineers, and maintaining operational runbooks. Qualifications Bachelor’s Degree and/or equivalent experience. 6+ years of cloud architecture experience, including 3+ years building production GenAI/LLM systems on AWS. Strong Python and AWS expertise, including Lambda, ECS/EKS, S3, SageMaker (or similar), plus Docker and Kubernetes. Production experience with vector databases and designing ingestion + embedding pipelines for both batch and streaming workloads. Hands‑on with prompt design, evaluation, LLM orchestration, and RAG implementation patterns. Experience deploying and operating model‑serving or MCP infrastructure (self‑hosted or managed). Proficient with IaC and delivery tooling, including Terraform/CloudFormation, GitOps, and CI pipelines. Proven skills in monitoring, logging, and automated testing for ML infrastructure and services. Strong communicator with clear documentation skills. Desired Experience Experience with model‑serving infrastructure such as Amazon SageMaker, NVIDIA Triton, Ray Serve, or similar platforms. Hands‑on experience with GenAI libraries and frameworks, including LangChain, LlamaIndex, Hugging Face, and OpenAI APIs. Deep operational expertise with vector databases such as Pinecone, Milvus, Weaviate, or Qdrant. Knowledge of data governance and regulatory compliance, including HIPAA and GDPR considerations. AWS Solutions Architect, AWS DevOps Engineer, or equivalent industry certifications. Benefits Work environment built on teamwork, flexibility, and respect. Professional growth and development programs, including tuition reimbursement. Team Member Vehicle Purchase Discount. Toyota Team Member Lease Vehicle Program (if applicable). Comprehensive health care and wellness plans for your entire family. Toyota 401(k) Savings Plan featuring a company match, plus an annual retirement contribution from Toyota. Paid holidays and paid time off. Referral services related to prenatal services, adoption, childcare, schools, and more. Tax‑advantaged accounts: Health Savings Account, Health Care FSA, Dependent Care FSA. Equal Employment Opportunity Applicants are considered without regard to race, ethnicity, national origin, sex, sexual orientation, gender identity or expression, age, disability, religion, military or veteran status, or any other characteristics protected by law. #J-18808-Ljbffr