Senior Python Engineer

Must have:

• 6+ years of professional Python development experience after graduation from university
• At least 0.5 years of commercial experience in AI tools on real projects – building/implementing agents/sub-agents, MCP integrations, skills crafting, or Spec driven integration into clients projects, or building SDLC with help of agents, or RAG chatbots
• Strong Python engineering skills (3.9+), large-scale applications (not just small web apps): async/await, dataclasses, Pydantic, NumPy, Pandas, etc
• Good understanding of integration patterns, API development (REST / GraphQL), and third-party system interoperability
• Solid experience in building automated tests: unit, integration, and E2E tests
• Readiness to start a new project as a solo engineer and drive communication with the client. In addition, manage extension of a new team if needed
• Experience with at least one major web/API framework: FastAPI, Django REST Framework, or Flask
• Proficiency with relational databases (PostgreSQL) and ORMs (SQLAlchemy, Django ORM)
• Solid understanding of software architecture patterns: clean architecture, domain-driven design, CQRS, event-driven systems
• Familiarity with CI/CD pipelines (GitLab CI, GitHub Actions) and containerization (Docker, Docker Compose)
• A demonstrable, personalized AI development workflow with custom skills, prompt templates, and project-level instructions — not just default out-of-the-box usage
• Hands-on experience with AI coding assistants: Claude Code, Cursor, GitHub Copilot, or similar
• Strong prompt engineering skills: ability to produce reliable, structured output and critically evaluate AI-generated code
• Critical mindset toward AI-generated output: knowing when to trust it, when to verify it, and when to rewrite it
• Passion for clean code, peer reviews, and high code quality standards
• Familiarity with scaling large systems — vertical scaling, single-tenant deployments
• Self-driven, comfortable with autonomy and open team cultures (trust > process)
• Experience working with or around AWS services (e.g., RDS, S3, Kubernetes, SQS, RabbitMQ)
• Readiness to work with Windows (WSL)

Nice to have:

• Frontend experience (React)
• Familiarity with Celery, RabbitMQ, or Kafka for async task processing
• Contributions to open-source Python or AI projects
• Experience with RAG (Retrieval-Augmented Generation) pipelines and vector databases (Qdrant, Chroma, pgvector)
• Knowledge of LangGraph, AutoGen, or other agent orchestration frameworks
• Ability to create custom sub-agents and orchestrate multiple AI agents in parallel for concurrent task execution
• Experience integrating LLMs into Python applications via the Anthropic SDK, OpenAI SDK, or LangChain/LlamaIndex
• Exposure to ML/AI model lifecycle: fine-tuning, embedding generation, model evaluation

Godel is on the lookout for talented Senior Python Engineers to join one of our teams engaged in the development of business applications for major British companies. We always have new and exciting projects with opportunities to improve your skills in a wide spectrum of technologies. If you are an enthusiastic and ambitious Python Engineer, this job is for you!

Tech Stack

• Language: Python 3.9+, JS (Typescript, React) nice to have
• Web / API: FastAPI, Django REST Framework, Flask, etc
• Databases: PostgreSQL, Redis, MongoDb, MySQL
• Task queues: Celery, RabbitMQ, Kafka
• AI/LLM: Anthropic Claude, OpenAI, LangChain, LlamaIndex, BMAD, SpecKit, OpenSpec
• Testing: pytest
• Infrastructure: Docker, GitLab CI/CD, AWS / GCP
• AI tooling: Claude Code, Cursor, GitHub Copilot
• Version control: Git (GitLab)

,[Design, develop, and maintain scalable finance-focused backend solutions using Python and Django, Integrate external systems and third-party APIs, Work closely with Product Managers and Tech Leads to define, size, and solve real-world telecom customer problems, Write high-quality, well-tested code ensuring reliable daily deployments to production, Participate in peer reviews, refinements, and continuous feedback loops across a multi-disciplinary team, Maintain a developer-first quality culture: own unit, integration, and functional testing, Be part of a weekly engineering goal-setting process (lean Kanban-style working), Apply AI tools throughout the entire development lifecycle: code generation, refactoring, automated review, test creation, debugging, and technical research, Architect and design Python-based systems: API services, data pipelines, async workers, and AI-integrated backends — with AI assistance as a core part of the process, Conduct thorough code reviews, uphold engineering best practices, and ensure high-quality, maintainable Python codebases across the team, Contribute to technology selection, system design, and trade-off analysis across client projects, Identify risks, bottlenecks, and security concerns proactively; propose and implement solutions, Work directly with clients in English for requirements clarification, technical discussions, and progress updates, Mentor junior and mid-level Python engineers through day-to-day guidance, pair sessions, and knowledge sharing, Stay current with advancements in Python tooling, AI coding assistants, and LLM-integration patterns] Requirements: Python, AI, FastAPI, API, Django, Testing, Data pipelines, SDLC, REST API, GraphQL, SQLAlchemy, Clean Architecture, Domain Driven Design, CQRS, CI/CD Pipelines, Docker, Docker Compose, GitHub, Clean Code, AWS, Kubernetes, RabbitMQ, Windows, React, Celery, Kafka, SDK, JavaScript, TypeScript, PostgreSQL, Redis, MongoDB, MySQL, pytest, GitLab CI, CD, GCP, Git Tools: . Additionally: Flat structure, Small teams, Integration events, Internal trainings/meetups, Private healthcare, Sport subscription, Training budget, Free coffee, Bike parking, Playroom, Free snacks, Free beverages, In-house trainings, In-house hack days, Modern office.