Data Engineer

3B Staffing LLC

The challenge is not just applying LLMs-it's making them reliable in production for financial workflows.

What You'll Work On

Designing pipelines that process high-volume financial documents (batch + near real-time)
Building LLM-powered extraction workflows (classification, parsing, summarization)
Implementing validation layers (rule-based + model-based) to reduce hallucinations
Developing retrieval systems using embeddings and vector search
Architecting end-to-end systems: ingestion → processing → storage → serving
Ensuring data quality, observability, and fault tolerance
Collaborating with product to turn messy data into usable financial intelligence

Core Requirements

Strong Python and backend/data engineering experience
Experience building production data pipelines (ETL, streaming, or async systems)
Solid understanding of distributed systems and failure modes
Experience working with LLM-based systems in production:
- Prompt design
- Output validation
- Retry/fallback strategies
- Evaluation and monitoring
Experience with data storage systems (SQL + NoSQL)
Familiarity with cloud infrastructure (AWS or similar)

Preferred Experience

What Makes This Role Interesting

Work on high-accuracy AI systems where correctness matters
Solve real problems around:
- LLM reliability and hallucination mitigation
- Data consistency across conflicting sources
- Real-time vs correctness tradeoffs
Build systems used in financial decision-making workflows
High ownership over core architecture in an early-stage environment

Nice to Know (but not required)

Tech Stack (Representative, not exhaustive)

Vacancy posted more than 2 months ago

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