Senior Java Developer

You will own backend services that process large, complex mortgage documents at scale, designing the pipelines, integrating LLMs, and keeping the whole thing fast, accurate, and cost-effective in production. This is a hands-on senior role with real ownership: you will make architecture calls, drive them to a decision, and set the quality bar for engineers working alongside you.

Responsibilities:

• Build high-throughput document pipelines. Asynchronous, parallel processing with batching, retries, backpressure, and idempotent reprocessing for large documents and large data volumes.
• Work with the latest LLMs. Build against current LLM API timeouts, token and cost controls, response validation, and automatic failover between providers.
• Engineer for resilience. Circuit breakers, fallback chains, and graceful degradation so a single upstream failure never takes the pipeline down.
• Debug production. Investigate extraction failures, latency spikes, and cost regressions using dashboards and metrics, and fix the root cause.
• Raise the bar on the team. Review PRs, break features into clear tasks, unblock junior engineers, and write design docs that hold up to scrutiny across time zones.

Requirements:

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• 4+ years of hands-on Java development, including at least 2 years owning a production service.
• Excellent command of Core Java, with real depth in multithreading and concurrent architecture design.
• Strong with Spring Boot and Spring Data; comfortable in microservices and REST architecture.
• Strong working knowledge of NoSQL DB (preferred: MongoDB ); familiar with relational databases (MySQL or PostgreSQL).
• Comfortable with Docker and Kubernetes, and at least one cloud platform (AWS, GCP, or Azure).
• Strong debugging and problem-solving skills with a solid command of data structures.
• Reasons about trade-offs in cost, latency, and accuracy, not just correctness.
• Has informally mentored or guided junior engineers; the person others come to when they're stuck.
• Operates independently with minimal supervision, and proactively flags risks instead of waiting to be asked.
• Excellent written communication; much of the collaboration is asynchronous and across time zones.

Good to Have:

• Exposure to LLM or GenAI application development, prompt iteration, evaluation, or accuracy measurement.
• Working knowledge of Python.
• Experience with streaming queues like Kafka or RabbitMQ.
• Background in Document AI, OCR, or the mortgage/fintech domain.
• Familiarity with observability tooling (Grafana, Metabase, ELK).