Responsibilities
- Build financial operations and reporting infrastructure — Design and implement backend services for Accounting, FP&A, Tax, Procurement while keeping the company compliant.
- Lead a platform migration — Architect the migration of business-critical workflows from legacy vendor platforms to Block's internal systems, ensuring zero disruption to agents and customers during cutover
- Design workflow and automation systems — Build configurable workflow engines, rules-based routing, and event-driven automations that reduce manual effort and scale across multiple business lines
- Own integrations end-to-end — Design, build, and maintain integrations between internal platforms and external systems (middleware, workforce management, Oracle fusion, Salesforce etc) using APIs, event streams, and messaging patterns
- Partner across the business — Work directly with operations, compliance, and product stakeholders to translate complex financial and regulatory requirements into well-architected technical solutions
- Ensure compliance and data integrity — Build systems with audit trails, access controls, and data governance baked in — not bolted on — to meet regulatory requirements across multiple jurisdictions
- Lead technical discussions — Drive architecture decisions, contribute to design reviews, and mentor engineers; raise the bar on code quality, testing, and operational reliability
- Direct AI agents across the full development lifecycle — from prototyping and implementation to debugging and code review — operating as the architect and decision-maker while AI handles the building
- Expand what's possible with AI tooling — identify opportunities to automate repetitive engineering work, improve code quality through AI-driven review, and share effective patterns with your team
Requirements
- Embrace an AI-first mentality. Leverage AI to augment your knowledge and capability in navigating development in complex systems with confidence.
- Familiar with agentic engineering.
- 6+ years working on complex systems and delivering quality software, with clear expertise developed in one or more technical areas.
- Strong fundamentals in distributed systems design — you've built services that handle high throughput, manage state across systems, and degrade gracefully
- Experience with workflow or state machine systems — you've designed systems where entities move through complex lifecycles with branching logic, SLAs, and human-in-the-loop steps
- Proficiency in building and maintaining APIs and integrations — REST, gRPC, event-driven architectures, and data synchronization across multiple platforms
- Experience working on financially sensitive or regulated systems — you understand why idempotency, audit trails, data retention, and access controls matter and you build for them by default
- Strong collaboration skills and the ability to work effectively with non-technical stakeholders — translating ambiguous business requirements from operations, compliance, and risk teams into well-scoped engineering work
- A growth mindset and comfort navigating open-ended problems where the "right" answer depends on business context that's still evolving.
- Contributed to the growth of fellow engineers through technical leadership, mentoring, and setting engineering standards
- Demonstrated fluency with AI-assisted development tools (e.g., Claude Code, Cursor, GitHub Copilot, or similar agentic coding tools) in real production work — not just familiarity, but regular, effective use
- You stay current on the rapidly evolving landscape of AI tooling and actively experiment with new capabilities as they emerge
Nice to Have
- Experience with platform migrations — moving business-critical systems between platforms with zero customer impact and phased rollout strategies
- Background in financial services domains — accounting, revenue forecasting, treasury operations, tax operations.
- Experience building multi-tenant or multi-BU platforms — systems that serve different business lines with shared infrastructure but configurable behavior
- Experience with operational analytics — building data pipelines or reporting systems that give operations leaders real-time visibility into performance
Technologies
AI-Driven Development: Claude Code, Goose (Block's open-source AI agent), Cursor, GitHub Copilot, Anthropic's Model Context Protocol (MCP)
Languages: Kotlin, Java, Python, JavaScript
Protocols: HTTP, JSON, gRPC, Protocol Buffers
Data: DynamoDB, MySQL, Kafka, Snowflake
Infrastructure: AWS, Kubernetes
Observability: DataDog, Prometheus
Feature Management: LaunchDarkly
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