Software Engineer - AI Augumented Development

Hamsa

About The Position

Hamsa is building the operating system for global finance. Through our AI-enabled Unified Ledger, we connect the world's largest financial institutions while solving critical challenges in interoperability, privacy, and speed. With $400B on platform in 2025 and $1T projected for 2026, we're scaling rapidly and reshaping how the world's financial system operates. Backed by top-tier investors, our global team operates across the US, APAC, EU, and LATAM. We are seeking a highly experienced Software Engineer with approximately 5+ years of hands-on software development experience building production-grade systems. The ideal candidate has spent the last ~2 years deeply engaged in AI-augmented development (“vibe coding”), using LLM-based coding tools, agent-driven workflows, and MCP-style multi-agent systems to accelerate software delivery and engineering productivity. This is a deeply hands-on individual contributor role focused on shipping high-quality software at scale using both traditional engineering expertise and modern AI-native development practices.

Requirements

5+ years of hands-on software engineering experience
Deep experience building and maintaining production systems at scale
Recent (2+ years) hands-on use of AI coding assistants (LLM-based IDE tools, copilots, agent frameworks)
Recent (2+ years) hands-on use of Multi-step agent workflows (MCP-style or equivalent systems)
Recent (2+ years) hands-on use of Prompt-driven development, debugging, and refactoring workflows
Strong track record of shipping complex systems in fast-moving environments
Expert-level coding ability in Java as well as Python, Go or TypeScript
Strong experience with backend systems, APIs, and distributed systems
Experience with AWS cloud services (production-grade environments)
Strong experience with PostgreSQL (data modeling, performance tuning, querying)
Strong understanding of cybersecurity standards and best practices (e.g., secure coding, OWASP principles, authentication/authorization, data protection in distributed systems)
CI/CD pipelines, automated testing, and production debugging
Comfortable operating in AI-augmented development environments daily

Nice To Haves

Experience with financial systems, fintech platforms, trading systems, payments, or other regulated financial environments
Experience with developer productivity tools or internal engineering platforms
Exposure to high-scale SaaS or distributed enterprise systems
Experience training and experimenting with autonomous coding agents or AI workflows
Contributions to automation, tooling, or engineering efficiency improvements

Responsibilities

Design, implement, and maintain high-quality production code across backend and distributed systems
Own complex feature development end-to-end, from implementation through production deployment
Debug, troubleshoot, and resolve issues in large-scale production environments
Use AI to deliver robust, maintainable, and fully tested software
Use LLM-based tools and agent workflows daily to accelerate coding, refactoring, and debugging
Work with MCP-style agent systems to generate and iterate on production code, automate test creation and validation, support debugging and root-cause analysis, improve code review cycles and refactoring speed, and continuously evolve personal development workflows using AI-native tooling
Deliver robust, maintainable, and fully tested software
Improve testing practices, CI/CD workflows, and developer efficiency
Identify and fix performance, reliability, and scalability issues in existing systems
Collaborate closely with engineers and product teams to deliver features iteratively
Participate in code reviews and provide strong technical feedback
Act as a high-seniority IC contributor embedded within engineering teams