Software Engineer (Python)

About the Company

We are working with a US start-up that is building AI-driven workflow automation, the team is building an AI-first platform for the financial sector, they are focused on rethinking how investment professionals analyse data, make decisions, and execute workflows. At its core is a multi-agent system designed to turn complex, fragmented financial data into structured, actionable insight.

Backend engineers play a critical role in this vision, developing the infrastructure, services, and data systems that power intelligent, agent-driven workflows at scale.

Full-time roles are available with remote, hybrid, or on-site flexibility depending on preference and seniority. The office is in the Bay Area.

Candidates must be based in the US, there will be very occasional travel to the Bay Area.

What You’ll Be Doing

• Design and build scalable backend services using Python and cloud-native technologies
• Develop APIs, orchestration layers, and data pipelines that enable real-time analytics and agent-based workflows
• Convert complex financial requirements into clean, efficient, and maintainable code
• Work closely with product, data, and ML teams to integrate LLMs and intelligent systems into user-facing workflows
• Take ownership of system performance, reliability, and long-term maintainability
• Contribute to architecture decisions and implement best practices across testing, DevOps, infrastructure-as-code, and observability

What They’re Looking For

• 3–7 years of experience in backend engineering
• Proven track record of building and scaling production systems, particularly in data-heavy or real-time environments
• Strong Python skills and experience working with distributed systems
• A mindset geared toward building intelligent, autonomous systems rather than simple CRUD applications
• Experience designing and working with well-structured APIs (REST, GraphQL, or RPC)
• Familiarity with containerisation (Docker), orchestration (Kubernetes), and event-driven architectures (e.g. Kafka)
• Solid understanding of relational databases (e.g. PostgreSQL) and caching layers (e.g. Redis)
• Experience with performance optimisation, testing, CI/CD, and building secure, observable production systems
• Interest in complex problem-solving within domains such as fintech, trading, or enterprise SaaS

Nice to Have

• Experience with LLMs, AI frameworks, or agent-based systems (e.g. LangGraph, CrewAI, AutoGen, Haystack)
• Exposure to financial datasets, investment workflows, or alternative data pipelines

Perks

• Competitive compensation ($140 - $170K)
• Bonus
• Equity
• Unlimited PTO
• Access to AI assistants for work (coding and general-purpose tools)