Lead Python developer (GenAI/Microservices focused)

Toyota North America•Plano, TX

1d•Hybrid

About The Position

Overview Who we are Collaborative. Respectful. A place to dream and do. These are just a few words that describe what life is like at Toyota. As one of the world’s most admired brands, Toyota is growing and leading the future of mobility through innovative, high-quality solutions designed to enhance lives and delight those we serve. We’re looking for talented team members who want to Dream. Do. Grow. with us. An important part of the Toyota family is Toyota Financial Services (TFS), the finance and insurance brand for Toyota and Lexus in North America. While TFS is a separate business entity, it is an essential part of this world-changing company- delivering on Toyota's vision to move people beyond what's possible. At TFS, you will help create best-in-class customer experience in an innovative, collaborative environment. To save time applying, Toyota does not offer sponsorship of job applicants for employment-based visas or any other work authorization for this position at this time. Who We’re Looking For Toyota Financial Services seeks a motivated Senior Software Engineer with expertise in Python, AWS, and microservices to act as a hands-on tech lead. You will design, build, and support scalable microservices and APIs, leveraging FastAPI and OpenAPI standards, while leading a squad of engineers. You will collaborate closely with architects, business stakeholders, data governance teams, and data scientists to deliver AI-powered solutions, dashboards, and interactive user interfaces.

Requirements

Education: Bachelor’s or higher in Computer Science, Information Systems, Data Engineering, or related field (or equivalent experience).
Experience: 5+ years in professional software engineering, including designing microservices and deploying containerized applications.
Python Expertise: Strong experience building backend services and RESTful APIs with Python (FastAPI) and documenting with OpenAPI/Swagger.
Cloud: Proficiency with AWS (e.g., ECS Fargate, API Gateway, Lambda, S3, CloudWatch); familiarity with GenAI platforms (AWS Bedrock or equivalents).
Infrastructure as Code: Practical experience with Terraform (and/or AWS CloudFormation).
Programming & Data: Hands-on skills in Python, SQL; exposure to Java is a plus.
Build & CI/CD: Proficiency with Git/GitHub, CI/CD tools (GitHub Actions, Jenkins); familiarity with build tools (Gradle/Maven) where Java is used.
Communication: Clear, concise communicator who can influence decisions with data, presentations, and visualizations.
Ways of Working: Effective collaborator in a hybrid environment; able to work independently with strong ownership and follow-through.

Nice To Haves

Master’s degree in Information Systems, Data Engineering, or Data Analytics.
Any AI practioner certification.
Frontend/Tools: Experience creating internal tools or dashboards with Streamlit (nice to have).
Hands-on experience with AWS ECS Fargate, API Gateway, Lambda, EC2, S3, AWS Bedrock, and GenAI platforms.

Responsibilities

Backend/API Development Build and maintain RESTful APIs with Python (FastAPI; OpenAI/Bedrock SDKs as clients), containerized and deployed on AWS ECS Fargate. Design clean contracts and versioned APIs; document with OpenAPI/Swagger.
GenAI & RAG Integration Integrate with AWS Bedrock and other GenAI services to enable RAG and knowledge-base queries. Work with vector databases (e.g., Pinecone, Weaviate, OpenSearch/Elasticsearch vector) for semantic search and retrieval. Implement robust API clients for AI endpoints, including auth, throttling, retries, and error handling.
AWS & Infrastructure Configure API Gateway for secure routing, throttling, authentication/authorization. Use IaC (Terraform or AWS CloudFormation) for ECS/Fargate, API Gateway, IAM, networking. Utilize AWS services: S3, Lambda, OpenSearch/Elasticsearch, CloudWatch, Bedrock.
CI/CD, Quality, and Testing Build CI/CD pipelines (GitHub Actions, Jenkins, or CodePipeline) for automated build/test/deploy; use GitHub/GitLab and artifact repos (e.g., Artifactory). Write unit, integration, and end-to-end tests with pytest; automate regression tests with QA. Perform load/stress testing; analyze performance and reliability metrics.
Observability & Operations Implement centralized logging and metrics (CloudWatch, Dynatrace; Elasticsearch/OpenSearch if needed); set up SLIs/SLO-based alerts. Troubleshoot incidents using logs, traces, and metrics; proactively address bottlenecks.
Security & Governance Implement SSO/OAuth2/JWT; follow AWS and MuleSoft integration security best practices where applicable. Apply AI/application guardrails for safe, compliant usage; manage secrets and dependency scanning.
Collaboration & Delivery Work closely with data scientists, AI engineers, and architects to productize AI outputs as APIs. Participate in sprint planning, code reviews, design discussions; maintain clear documentation.

Benefits

A work environment built on teamwork, flexibility, and respect
Professional growth and development programs to help advance your career, as well as 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, as well as an annual retirement contribution from Toyota regardless of whether you contribute
Paid holidays and paid time off

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