Lead Software Engineer

We are partnered with an established global financial services firm to look for for an articulate, highly autonomous Solutions Engineer to take direct ownership across financial applications.

We are looking for individuals who pair deep backend systems programming and data architecture with the stakeholder presence to sit directly with business heads and turn complex financial workflows into production-grade software.

Key Responsibilities

• Take primary software and architectural ownership of core financial applications, driving backend service design, relational data models, API contracts, and scalable feature delivery.
• Partner directly with business heads, investment controllers, and portfolio teams to unpack messy, complex requirements, running architectural walkthroughs and translating domain friction into clean technical solutions.
• Architect scalable backend microservices and event-driven data pipelines utilizing cloud-native patterns on AWS and enterprise data platforms (Snowflake / PostgreSQL).
• Actively explore and integrate modern AI workflows (Cursor, Claude Code, Copilot, Model Context Protocol/MCP servers, and agentic workflows) to elevate development velocity and modernize platform capabilities across the engineering chapter.
• Provide technical conviction in code reviews, establish standards for test automation and CI/CD, and guide junior engineers through clear, opinionated software design.

Core Requirements

• Strong hands-on coding foundation in Python or Java, with extensive experience designing RESTful/GraphQL APIs, microservices, and distributed backend systems.
• Advanced SQL proficiency alongside hands-on experience in data platform architecture (PostgreSQL, Aurora, Snowflake, or Iceberg) and pipeline orchestration.
• Practical experience architecting and deploying cloud-native workloads
• Proven ability to communicate clearly with non-technical business users, defend architectural trade-offs, and operate with high autonomy without needing rigid work-package definitions.
• Hands-on curiosity and practical experience applying LLM-assisted tools (Cursor, Claude Code, Copilot) or building agentic frameworks/MCP tools in day-to-day engineering.
• Prior exposure to buy-side investment systems, trading lifecycles, portfolio management (e.g., Charles River / Aladdin / SimCorp), private equity, fund accounting, or risk platforms.
• Willingness to undergo a hands-on technical case study session (covering SQL data interpretation, backend OOP design, and an architecture presentation).