Software Engineer - AI Augumented Development

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.

Key Responsibilities

Hands-on Software Development

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

AI-Augmented Development (Vibe Coding / MCP Systems)

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

Continuously evolve personal development workflows using AI-native tooling

Code Quality & Engineering Excellence

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

Technical Collaboration

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

Required Experience

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)

Multi-step agent workflows (MCP-style or equivalent systems)

Prompt-driven development, debugging, and refactoring workflows

Strong track record of shipping complex systems in fast-moving environments

Technical Skills

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 Have

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

Mindset & Traits

Strong individual contributor who excels at execution and delivery

Deep technical curiosity and strong coding craftsmanship

Comfortable working in rapidly evolving AI-driven development environments

Strong bias toward shipping working software quickly and iteratively

Uses AI tools as a core part of daily engineering practice, not as an add-on