Data Systems Engineer

Bluprynt is the Compliance OS for digital assets—the enterprise-grade infrastructure layer linking off‑chain compliance with on‑chain identity, policy, and supervisory visibility. Trusted by leaders across Trad Fi and DeFi and built in close alignment with central banks and regulators worldwide, Bluprynt helps issuers, banks, and market participants meet regulatory expectations without sacrificing the speed and modularity of on‑chain systems.

The company completed the EU's first MiCA pilot, launched Know Your Issuer (KYI) with Paxos and Circle, partnered with Chainlink on automated on‑chain compliance enforcement, and closed an oversubscribed $4.25M Seed round in 2026 with investors including Coinbase and Robinhood.

We are hiring a Data Systems Engineer to own the technical architecture and delivery of our data platform. This is a hands‑on role. You will write code daily, design systems, and ship product—while translating complex regulatory and product requirements into clean, scalable engineering solutions. Strong English communication skills and the ability to work core EST hours are required.

• Python (primary) and Type Script / Node.js
  Exceptional Python engineering for data‑intensive systems;
  Node.js/Type Script for backend services, async patterns, and API design at scale.
• PostgreSQL schema design
  Relational modeling for multi‑tenant compliance data, indexing strategy, migration workflows.
• API integration architecture
  Designing polling, webhook, and event‑driven pipelines across multiple external providers (think: RWA.xyz, TRM Labs, Cipher Owl, Chainlink, GLEIF).
• Multi‑source data ingestion & pipeline architecture
  Designing and building ETL/ELT architectures that ingest from multiple heterogeneous sources (APIs, databases, documents, on‑chain feeds), process both structured and unstructured data, and execute customizable computation logic with scheduling, retries, and observability.
• Schema design for structured vocabularies
  Versioned taxonomies, controlled vocabularies, or ontology‑like systems with cross‑reference resolution.

• Smart contract interaction
  Reading and writing to on‑chain registries, understanding gas mechanics, transaction lifecycle, and multi‑chain deployment patterns.
• On‑chain registry design
  Credential issuance/revocation, attestation hash anchoring, IPFS metadata storage.

• Managing external or embedded engineering teams
  Influence without direct authority, expectation setting, code review culture, knowledge transfer.
• Product-to-engineering translation & technical roadmap ownership
  Exceptional ability to decompose ambiguous product requirements into precise, phased engineering specifications; scope negotiation, dependency mapping, and shipping increments with clarity.
• Startup velocity
  Comfort with ambiguity, bias toward shipping V1 with known limitations, iterating in production.

• AI agent orchestration & workflow automation
  Actively using LLMs, AI agents, and orchestration frameworks (e.g. Lang Chain, Lang Graph, CrewAI, or similar) to build faster with equal or better quality; must be able to design and deploy multi‑agent workflows as a core part of the development process.
• AI-assisted testing & quality automation
  Leveraging AI tools to automate test generation, validation pipelines, and data quality checks; comfort using AI to accelerate development cycles without sacrificing reliability.

• Regulatory or compliance technology experience (KYC/AML, regulatory reporting, credential/certification systems).
• LLM integration for structured data extraction, taxonomy suggestion, confidence‑scored classification, and RAG or retrieval‑augmented systems for domain‑specific knowledge bases.
• Multi‑chain experience beyond EVM (Solana, Aptos, Stellar, Avalanche).
• RAG or retrieval‑augmented systems for domain‑specific knowledge bases.
• Experience with institutional custody platforms (Fireblocks, Bit Go) or MPC/multi‑sig architectures.
• AWS infrastructure (ECS/EKS, RDS, Lambda, SQS) and infrastructure‑as‑code.