Overview

Who we're looking for

At TFS, we're building a greenfield, cloud-native engineering platform that will redefine how Toyota Financial Services delivers digital products to millions of customers. We're looking for a Principal Architect - a senior individual contributor at the top of our IC track - who owns the technical coherence of the entire platform. This is not a management role and it's not an advisory role. It's for the engineer who can see across every layer of the system - application, data, AI/ML, and infrastructure - make binding architectural decisions and then get in the code to validate them. You'll be the connective tissue between engineering teams, setting direction across the stack, shaping standards that last, and serving as the person engineering leadership trusts to say, "this is how we build it."

What you'll be doing

Platform Architecture & Technical Leadership

• Own the end-to-end reference architecture for our engineering platform team - application, data, AI/ML, and infrastructure layers - ensuring coherence across all product domains
• Make binding, well-documented architectural decisions across teams; author RFCs, ADRs, and design documents that become the foundation for how we build
• Lead platform-wide technical design reviews and architecture forums, driving alignment across engineering leads, engineering managers, and product
• Define, evolve, and enforce engineering standards: API design contracts, IaC patterns, security posture, observability baselines, and deployment safety
• Identify and resolve systemic risks before they become incidents - performance ceilings, reliability gaps, coupling issues, and architectural drift
• Evaluate and recommend new technologies, frameworks, and AWS services; balance innovation with operational maturity and team capability

Hands-On Implementation & Code Quality

• Contribute with spikes/production-quality code in TypeScript and/or Python - you validate architectural decisions by writing and reviewing the code, not just describing it
• Own the design and lead implementation of the most complex, cross-cutting platform components: shared infrastructure modules, API frameworks, data pipeline foundations, and AI/ML integration layers
• Lead technical troubleshooting for the hardest distributed system failures - from API latency and data pipeline failures to infrastructure misconfigurations and LLM reliability issues
• Review and approve architectural changes across codebases, holding a consistently high bar for quality, testability, observability, and security

Data Platform & AI/ML Architecture

• Architect the data backbone of the platform: S3-based lakehouse design, event-driven streaming pipelines, data orchestration, and analytical query patterns
• Define integration patterns for AI/ML capabilities - how Bedrock agents, SageMaker endpoints, RAG pipelines, and agentic workflows connect to the application and data layers as first-class architectural concerns, not bolt-ons
• Establish guardrails for LLM-based systems: structured outputs, prompt engineering standards, observability for model behavior, and patterns for deterministic, production-grade AI features
• Partner with the ML/AI engineering team to ensure AI components are observable, testable, and maintainable at production scale

Cross-Functional Influence & Engineering Culture

• Serve as a technical thought partner to Engineering Managers and the VP of Engineering - translating complex technical tradeoffs into clear, actionable recommendations for both engineering and non-technical stakeholders
• Partner with Product and Program Management to assess technical feasibility, shape roadmaps, and surface risks early
• Drive the RFC and design review process across the engineering organization, ensuring major decisions have appropriate rigor and broad visibility
• Mentor senior and lead engineers - through design reviews, pairing, and written feedback - raising the technical ceiling of the entire org
• Contribute to hiring by conducting technical interviews for senior IC and architect-level roles, and helping define what architectural excellence looks like at TFS
• Champion a culture of documentation: ADRs, runbooks, design documents, and onboarding guides that transfer knowledge and reduce key-person risk

What you bring

• Bachelor's degree in computer science or related field, or equivalent practical experience
• 10+ years of software engineering experience, with at least 5 years of operating as a hands-on architect or principal-level IC on AWS-based platforms
• Proven track record of owning full-platform architecture decisions in production - not just advising, but being accountable for the outcomes

AWS & Cloud Architecture

• Deep, hands-on expertise with serverless-first AWS architecture, including:
• Lambda, API Gateway (REST and HTTP), Step Functions, EventBridge, SQS/SNS for compute and async orchestration
• DynamoDB and/or Aurora Serverless for data persistence patterns
• S3, CloudFront, and edge patterns for object storage, CDN strategy, and API acceleration
• Experience designing multi-account AWS architectures with proper governance: AWS Organizations, Control Tower, Service Control Policies, and cross-account IAM patterns
• Strong command of IaC design and governance using AWS CDK, CloudFormation, or Terraform - owning infrastructure design end-to-end, not just reviewing it

Data Platform

• Experience architecting S3-based lakehouse patterns: table formats (Apache Iceberg or Delta Lake), partitioning strategies, and lifecycle management
• Hands-on design of event-driven streaming pipelines using Kinesis, MSK/Kafka, or similar, through to analytics with Athena, Redshift, or equivalent
• Familiarity with data governance patterns: Lake Formation, data cataloging, access control for sensitive financial data

AI/ML Integration

• Practical experience integrating Amazon Bedrock, SageMaker endpoints, or equivalent LLM/ML services into production application architectures
• Understanding of agentic flow design - tool calling, memory patterns, human-in-the-loop checkpoints, and failure recovery in multi-step agent workflows
• Experience with RAG pipeline architecture - embedding generation, vector store design (OpenSearch, pgvector, or similar), and query-time retrieval patterns
• Ability to define architectural standards for LLM reliability: structured outputs, guardrails, observability for model behavior, and prompt engineering governance

Application & API Architecture

• Proven ability to design and govern RESTful and GraphQL API contracts at scale - versioning strategies, federation patterns, type-safe tooling (OpenAPI, tRPC, GraphQL Code Generator)
• Experience with frontend architecture at platform scale: Next.js on AWS (CloudFront, Lambda[redacted]), monorepo tooling (Turborepo/Nx), and how front-end and back-end contracts evolve together

Security & Observability

• Deep understanding of security architecture: IAM least-privilege design, secrets management (Secrets Manager, SSM Parameter Store), encryption patterns, and network segmentation
• Strong experience with distributed observability: CloudWatch, X-Ray, Datadog - defining SLAs, building dashboards, instrumenting services for traceability, and leading incident response

Communication & Leadership

• Strong written and verbal communication - you can author a clear RFC, lead a contentious design review, and explain a complex architectural tradeoff to a non-technical executive
• Track record of influencing without authority: aligning multiple engineering teams on a shared direction through credibility, evidence, and clear thinking
• Experience defining and maintaining engineering standards across an organization - code quality, testing strategies, deployment safety, and architectural review processes.

Added bonus if you have

• Master's degree in Computer Science or related field
• Experience in financial services, banking, or insurance - understanding of compliance, data residency, and auditability requirements
• AWS certifications: Solutions Architect Professional, Data Analytics Specialty, or Machine Learning Specialty
• Experience with data mesh or data product patterns - decentralized ownership with centralized governance and discoverability
• Hands-on experience with responsible AI practices: fairness metrics, bias detection, explainability (SHAP/LIME), and model monitoring
• Experience with CI/CD at platform scale - pipeline design, deployment strategies (blue/green, canary), and progressive delivery frameworks
• Experience contributing to or defining open standards, internal frameworks, or open-source projects
• Familiarity with GraphQL federation for composing distributed services across teams

What we'll bring

During your interview process, our team can fill you in on all the details of our industry-leading benefits and career
development opportunities. A few highlights include:
• 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 (if applicable)
• 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)
• Relocation assistance (if applicable)