TalentHawk
Senior Python Engineer - AWS and AI
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Senior Python Engineer - AWS and AI - 2 days a week in London
About The Role
Our client is a market-leading fintech platform looking for a Senior Python Engineer to drive the evolution of their core B2B SaaS products. In this role, you will design scalable microservices handling massive financial datasets, collaborate closely with product teams, and mentor junior peers.
They heavily embrace cutting-edge engineering; you will actively utilize modern AI agent tools and LLM assistants to accelerate delivery and maintain a high bar for code quality.
Key Responsibilities
- SaaS Design & Build: Design, implement, and scale reliable Python microservices across single- and multi-tenant Enterprise SaaS architectures.
- AI Productivity: Champion the adoption of AI engineering tools (e.g., Copilot, Claude, Cursor) and automated workflows to optimize delivery speed and code quality.
- Cloud Operations: Manage and optimize AWS infrastructure with a focus on observability, least-privilege security, and operational excellence.
- Product Collaboration: Partner with Product Owners to translate complex data requirements into clear, well-scoped engineering tasks.
- Mentorship: Actively support the technical growth of junior and mid-level engineers through thoughtful code reviews and guidance (no formal line management required).
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Technical Requirements
- Python & SaaS Architecture: Strong experience building B2B SaaS applications, REST APIs, and distributed microservices using Python.
- AWS Cloud & IaC: Practical experience with core AWS services (Cognito, Lambda, Fargate, API Gateway, S3, IAM) and infrastructure management via Terraform.
- Data Layer: Solid working knowledge of PostgreSQL (relational modeling, query optimization).
- AI Tooling Literacy: Hands-on experience integrating AI assistants or LLM workflows into your daily development cycle to boost productivity.
- Engineering Leadership: Proven ability to navigate ambiguity, take end-to-end ownership of tasks, and influence technical decisions constructively.
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Desirable Skills
- FinTech & Big Data: Familiarity with capital markets, financial data visualization, or high-scale tools (DuckDB, pandas, Spark, Snowflake).
- Advanced AWS & AI: Experience with event-driven architectures (SQS, SNS, EventBridge) or LLM frameworks (LangChain, LlamaIndex).
- Frontend: Competency in TypeScript for building data science/data visualization interfaces.
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