# Software Engineer, Finance Applications

**Company:** [Square](https://hotfix.jobs/companies/square)
**Location:** San Francisco, CA
**Role:** Backend Engineering
**Salary:** $143k – $258k/yr
**Experience:** 6+ years
**Skills:** Kotlin, Java, Python, JavaScript, Kubernetes, AWS, Kafka, DynamoDB, MySQL, Snowflake, gRPC, Datadog, Prometheus, Launchdarkly, AI Agents
**Posted:** 2026-04-28

> Designs and builds backend services, workflow engines, and integrations for financial infrastructure, emphasizing AI-driven development and compliance. Requires 6+ years in distributed systems, APIs, and agentic AI tools for complex financial operations.

## Job Description

## 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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**Canonical:** https://hotfix.jobs/jobs/65eba8e4-7461-40e4-8534-7b78b29bcd49