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Circle

Global payments platform using digital currencies

Manager, Software Engineering - Data Platform

Engineering LeadershipPosted on Nov 11
Full-timeRemote in USA$195k - $236.7k

About the Job

Requirements

  • At least 4 years of experience managing software engineers, including hiring, performance management, coaching, and senior individual-contributor development, and at least 6 years in data, machine learning, and/or platform engineering.
  • Hands-on experience building and operating large-scale warehouse, orchestration, streaming, or ingestion platforms, using technologies such as BigQuery, Airflow, Pub/Sub, Kafka, Iceberg, or equivalents.
  • Experience defining and meeting data service-level objectives, building validation that detects real problems, and changing architecture when data is wrong, late, or untrusted.
  • Experience building or leading large language model-based or agentic data systems, such as natural-language analytics, semantic layers, pipeline agents, or evaluation frameworks, while maintaining existing data access controls.
  • Experience designing a platform used by other teams, driving adoption, measuring reductions in bespoke requests, and reflecting on areas for improvement.
  • Experience owning high-impact platform projects end to end and delivering successful releases.
  • Recent hands-on experience critically reviewing code and designs, debugging difficult pipeline or warehouse issues, and designing, prototyping, reviewing, or shipping production code.
  • Ability to write useful design documents, explain complex systems to analysts, scientists, engineers, and finance partners, and provide leaders with direct recommendations.
  • Understanding of model training and evaluation, including cleaning training and fine-tuning corpora, creating labeled evaluation sets, versioning data, measuring effects on model quality, and preventing label noise, leakage, and distribution drift.

Responsibilities

  • Own the vision, architecture, and roadmap for ingestion, orchestration, warehouse, business intelligence, and real-time data services, and clearly prioritize trade-offs.
  • Manage, coach, and grow senior engineers; develop senior individual contributors into technical leaders and hire effectively.
  • Lead AI-agent management, guardrails, and review standards, holding agent output to a human engineer’s quality bar.
  • Curate, version, and govern training, fine-tuning, and evaluation datasets with provenance, labeling workflows, access controls, and deterministic reproducibility.
  • Equip engineers with agentic tools for design, coding, testing, on-call work, and documentation, and measure the resulting gains.
  • Make correctness and data quality platform features through service-level objectives, data contracts, lineage, automated checks, and clear dataset ownership.
  • Build the platform’s AI and agentic layer, including metadata, semantic context, natural-language access to canonical data, pipeline and on-call agents, and deterministic, auditable evaluations within existing access controls.
  • Enable Data Engineering and product teams to onboard sources, pipelines, dashboards, and monitoring rules without filing tickets.
  • Operate a reliable production platform with clear service-level agreements, cost attribution, budget planning, vendor upgrades with rollback plans, and accurate status reporting.
  • Partner with Data Engineering, Data Science, Analytics, Product Engineering, Security, TechOps, and Finance to build reusable platform capabilities rather than one-off pipelines.
  • Stay close to the code by leading designs, reviewing critical paths, debugging production issues, and prototyping when it accelerates progress.

Desired Qualifications

  • Experience with blockchain data at scale, including indexing multiple networks, handling chain reorganizations, reconciling balances, and providing near-real-time on-chain event monitoring.
  • Experience in fintech, crypto, payments, or another regulated environment where auditability, restricted data handling, and operational controls are part of the platform.
  • Experience with streaming and stateful processing for transaction-centric, low-latency monitoring.
  • Familiarity with data catalog and lineage tools, access governance on a cloud warehouse, and cost attribution for shared compute.
  • Experience with Python, Go, or Java services, and with agent frameworks and protocols such as LangGraph or MCP.
  • Experience leading a geographically distributed team.

About the Company

Circle

Global payments platform using digital currencies

Circle is a global fintech company that helps businesses use digital currencies and public blockchains for payments, commerce, and financial applications. It provides a platform for digital payments and related financial services built on blockchain technology, charging transaction fees and service charges for its activities. How it works: Circle offers digital currency and blockchain-based payment capabilities that enable fast, secure transfers and cross-border transactions for businesses of all sizes; revenue comes from fees on these services. How it differs from competitors: Circle targets a broad range of business customers and focuses on integrating digital currencies and public blockchains into everyday commercial and financial processes, emphasizing security and efficiency. Circle's goal is to become a leading provider of enterprise-grade digital finance tools, helping many organizations adopt and use digital currencies and blockchain-based payments globally.

Company size
1,001-5,000
Company stage
IPO
Headquarters
New York City, New York
Founded
2013

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