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TrueML is a mission-driven financial software company using machine learning to create better customer experiences for distressed borrowers. The company combines data scientists, financial services experts, and customer experience specialists to build technology that serves people's unique financial needs.
As a Senior Engineer on the Data Services team, you will be a key technical contributor responsible for the reliability, scalability, and evolution of TrueML's event and data infrastructure. This includes the centralized event bus for asynchronous communication between domains, streaming and change-data-capture pipelines that move operational data into analytics platforms, and integration services bridging the modern platform with legacy systems during an active migration.
You will take full ownership of complex technical work, set a high engineering bar, and actively help elevate engineers around you. The team builds with AI rather than just alongside it—running LLM-backed services in pipelines and shipping agent-readable context and tooling in repositories. In partnership with your Engineering Manager, Product, and sibling teams, you will translate requirements into well-architected solutions with a strong bias toward reliability, observability, and measurability.
Key responsibilities include: owning complex engineering tickets end-to-end from design through production; authoring Technical Design Documents and Architecture Decision Records; building and maintaining the Common Event Bus including event validation, enrichment, EventBridge routing, DLQ handling, and Iceberg lakehouse connectors; stewarding event and API contracts with schema definitions and versioning; treating infrastructure as code with Terraform across environments; using AI coding agents as a primary workflow tool and improving team adoption; instrumenting pipelines with meaningful observability; actively supporting junior engineer growth through code review and pairing; partnering cross-functionally with Data Engineering, Data Science, and Product teams; and contributing to engineering standards and FinOps conversations.
Qualifications:
- Bachelor's degree in a related technical field or equivalent practical experience
- 5+ years of software or data engineering experience with demonstrated ownership of production systems (no people management required)
- Deep experience with event-driven architecture: event buses, schema evolution, idempotency, dead-letter handling, replay
- Hands-on with managed event platforms (EventBridge, SNS/SQS, Kinesis) and/or Kafka with schema registry
- Strong multi-account AWS fundamentals: Lambda, IAM, data ecosystem (S3, Glue Catalog, Athena, Firehose, Iceberg)
- Production-grade Go or Typescript; willingness to work in JVM for legacy platform
- Terraform at production scale
- Agentic coding tools (Claude Code or equivalent) as daily driver with grounded opinions on limits
- Practical understanding of MCP—consuming servers, ideally building one
- Hands-on experience building on LLM APIs (Bedrock, Anthropic, or similar): prompt and context engineering, structured output, tool calling, evaluation and guardrails
- Ability to reason about model tiers, token budgets, and cost profiles
- Experience with PII, tokenization, and least-privilege access in regulated environments; understanding of prompt injection and over-broad agent permission risks
- Ownership mindset: initiative, follow-through without close direction, production reliability as personal standard
- Clear written communication for technical design proposals and ability to explain trade-offs to non-engineers
