Full Stack Software Engineer (Mid-Senior Level)

• Build and ship features end to end across React/TypeScript frontends and Java 21+ / Spring Boot and Go microservices that power automated mortgage and personal finance workflows.
• Develop high-throughput Go services using gRPC and Protocol Buffers for internal service-to-service communication, and expose external REST APIs documented with OpenAPI 3.
• Build event-driven pipelines with Amazon MSK (Kafka), SQS, SNS, and EventBridge to asynchronously process loan applications, bank transactions, and document uploads.
• Integrate AI capabilities using Amazon Bedrock and Amazon Textract to extract, classify, and validate data from financial documents such as W-2s, pay stubs, bank statements, and loan estimates.
• Orchestrate multi-step workflows such as loan pre-qualification, document verification, and payment scheduling using AWS Step Functions and AWS Lambda.
• Design data models and optimize queries for Amazon Aurora PostgreSQL and DynamoDB, and implement caching with Amazon ElastiCache for Redis.
• Implement multi-tenant authentication and authorization using Amazon Cognito, OAuth 2.0/OIDC, and Spring Security, enforcing strict tenant data isolation across services.
• Protect sensitive financial data (PII/NPI) using AWS KMS, AWS Secrets Manager, least-privilege IAM policies, and field-level encryption in support of SOC 2 Type II and GLBA compliance.
• Integrate third-party financial data providers such as Plaid and credit bureau APIs, and work with MISMO-standard mortgage data.
• Build data-rich dashboards for loan tracking, cash flow, and budgeting using TanStack Query, React Hook Form with Zod validation, Tailwind CSS, and Recharts.
• Containerize services with Docker and deploy to Amazon EKS using Helm and Argo CD, with build pipelines in GitHub Actions and images stored in Amazon ECR.
• Provision and manage AWS infrastructure as code with Terraform.
• Instrument services with OpenTelemetry and monitor production health using Amazon CloudWatch, AWS X-Ray, and Datadog.
• Write automated tests using JUnit 5, Mockito, Testcontainers, Go’s testing package with testify, Jest, React Testing Library, and Playwright., Backend: Java 21+, Spring Boot, Spring Security, Spring Data JPA/Hibernate, Go, gRPC, Protocol Buffers, OpenAPI 3 Frontend: TypeScript, React, Vite, TanStack Query, React Hook Form, Zod, Tailwind CSS, Recharts AWS Compute & Orchestration: Amazon EKS, Amazon ECR, AWS Lambda, Amazon API Gateway, AWS Step Functions AWS Data & Messaging: Amazon Aurora PostgreSQL, Amazon DynamoDB, Amazon ElastiCache for Redis, Amazon S3, Amazon MSK, Amazon SQS, Amazon SNS, Amazon EventBridge AWS AI: Amazon Bedrock, Amazon Textract AWS Security & Edge: Amazon Cognito, AWS KMS, AWS Secrets Manager, AWS IAM, AWS WAF, Amazon CloudFront DevOps & IaC: Docker, Kubernetes, Helm, Argo CD, Terraform, GitHub Actions Testing: JUnit 5, Mockito, Testcontainers, testify, Jest, React Testing Library, Playwright Observability: OpenTelemetry, Amazon CloudWatch, AWS X-Ray, Datadog

• Bachelor’s degree in Computer Science, Software Engineering, or a related field.
• 3-7 years of professional experience in full stack software development.
• Strong production experience with Java 17+ and Spring Boot, including Spring Data JPA/Hibernate and Spring Security.
• Production experience building Go services, including concurrency with goroutines and channels, gRPC, and net/http or frameworks such as Gin or Echo.
• Strong proficiency in TypeScript and React (hooks, component architecture, state management) with modern tooling such as Vite, ESLint, and Prettier.
• Hands-on experience with AWS services, including several of the following: EKS or ECS, Lambda, API Gateway, S3, Aurora/RDS, DynamoDB, SQS/SNS, and IAM.
• Experience designing event-driven microservices with Kafka or Amazon MSK, including idempotency, retries, dead-letter queues, and the transactional outbox pattern.
• Solid PostgreSQL skills, including schema design, indexing, query tuning, and migrations with Flyway or Liquibase.
• Experience running Docker containers on Kubernetes with Helm in a production environment.
• Experience with CI/CD in GitHub Actions (or similar) and infrastructure as code with Terraform.
• Working knowledge of secure coding practices (OWASP Top 10) and handling of sensitive data such as PII.
• Must be a U.S. citizen. We are unable to sponsor work visas now or in the future., Master’s degree in Computer Science, Software Engineering, or a related field. Experience building LLM-powered features with Amazon Bedrock, LangChain4j, or retrieval-augmented generation (RAG) using pgvector or Amazon OpenSearch Serverless. Experience with Amazon Textract or other document AI/OCR tools. Mortgage or fintech domain knowledge, such as MISMO data standards, loan origination systems like ICE Encompass, or Plaid integrations. Experience working in SOC 2 Type II, PCI DSS, or GLBA regulated environments. AWS certifications such as AWS Certified Developer - Associate or AWS Certified Solutions Architect - Associate.

Competitive salary range of $100,000 - $120,000 per year, commensurate with experience. 401(k) retirement plan with company match. Comprehensive medical, dental, and vision insurance. Paid time off and company holidays. Flexible work arrangements. Professional development and continuing education support. Opportunity to work on innovative AI-driven products in a high-growth environment.

Equal Opportunity Employer

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. All qualified applicants will receive consideration for employment.

Pay: $100,000.00 - $120,000.00 per year, * 401(k)

• Dental insurance
• Flextime
• Happy hour
• Paid sick time
• Work from home

Application Question(s):

• Tell us about a recent project you worked on that you think is relevant to this role. What did your day-to-day work look like, and what problems were you solving?
• Describe a time you had to troubleshoot a difficult production issue in a distributed or microservices-based system (for example, message loss, duplicate processing, latency spikes, or cascading failures). How did you identify the root cause, what did you change to fix it, and what did you do to prevent it from happening again?
• Which AWS services have you used hands-on in production, and how did you use them? Please walk us through one example of how you built, deployed, or secured a service on AWS, including any tradeoffs or decisions you had to make along the way.