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Salary: USD 140,000 - 180,000 / annual
TrueML is a mission-driven fintech company building machine learning-powered software to improve customer experiences for distressed borrowers. The company uses digital-first, AI-driven strategies to engage customers in real time and ensure financial inclusion.
As a Senior Engineer on the Data Services team, you will own 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 modern and legacy systems during an active migration.
You will take full ownership of complex technical work, set a high engineering bar, and mentor junior engineers. The team builds with AI as a core capability—running LLM-backed services in production pipelines and shipping agent-readable context and tooling.
Key Responsibilities:
- Own complex engineering tickets end-to-end: design, implementation, testing, and production deployment
- Author and review Technical Design Documents (TDDs) and Architecture Decision Records (ADRs)
- Build and maintain the Common Event Bus, including event validation/enrichment, EventBridge routing, DLQ handling, replay mechanisms, and Iceberg lakehouse connectors
- Steward event and API contracts in a centralized schema registry (OTDS), managing versioning and compatibility
- Write and deploy infrastructure as code using Terraform across sandbox/dev/staging/production environments
- Use AI coding agents as a primary workflow tool; improve team adoption of agentic engineering
- Own LLM-backed services: prompt design, context engineering, structured output, tool calling, validation, and model selection with cost discipline
- Instrument pipelines with meaningful observability (delivery rates, validation failures, DLQ depth, latency)
- Support junior engineers through code review, pairing, and direct feedback
- Partner with Data Engineering, Data Science, and Product to define data contracts and coordinate schema changes
- Contribute to code quality, testing, and operational readiness standards
Requirements:
- 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
- Deep experience with event-driven architecture: event buses, schema evolution, idempotency, dead-letter handling, replay
- Hands-on experience with managed event platforms (EventBridge, SNS/SQS, Kinesis) and/or Kafka with schema registry
- Strong multi-account AWS fundamentals: Lambda, IAM, S3, Glue Catalog, Athena, Firehose, Iceberg
- Production-grade proficiency in Go or TypeScript; willingness to work in JVM for legacy systems
- Production-scale Terraform experience
- Daily use of agentic coding tools (Claude Code or equivalent) with grounded opinions on their limitations
- Practical understanding of Model Context Protocol (MCP): consuming servers and ideally building one
- Hands-on experience building on LLM APIs (Bedrock, Anthropic, or similar): prompt 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 permissions as real security risks
- Ownership mindset: initiative, follow-through without close direction, production reliability as personal standard
- Comfort inheriting and improving under-documented systems
- Clear written communication for technical design proposals and ability to explain trade-offs to non-engineers
