Senior Python Engineer

Must have:6+ years of professional Python development experience after graduation from universityAt 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 chatbotsStrong Python engineering skills (3.9+), large-scale applications (not just small web apps): async/await, dataclasses, Pydantic, NumPy, Pandas, etcGood understanding of integration patterns, API development (REST / GraphQL), and third-party system interoperabilitySolid experience in building automated tests: unit, integration, and E2E testsReadiness to start a new project as a solo engineer and drive communication with the client. In addition, manage extension of a new team if neededExperience with at least one major web/API framework: FastAPI, Django REST Framework, or FlaskProficiency with relational databases (PostgreSQL) and ORMs (SQLAlchemy, Django ORM)Solid understanding of software architecture patterns: clean architecture, domain-driven design, CQRS, event-driven systemsFamiliarity 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 usageHands-on experience with AI coding assistants: Claude Code, Cursor, GitHub Copilot, or similarStrong prompt engineering skills: ability to produce reliable, structured output and critically evaluate AI-generated codeCritical mindset toward AI-generated output: knowing when to trust it, when to verify it, and when to rewrite itPassion for clean code, peer reviews, and high code quality standardsFamiliarity with scaling large systems — vertical scaling, single-tenant deploymentsSelf-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 processingContributions to open-source Python or AI projectsExperience with RAG (Retrieval-Augmented Generation) pipelines and vector databases (Qdrant, Chroma, pgvector)Knowledge of LangGraph, AutoGen, or other agent orchestration frameworksAbility to create custom sub-agents and orchestrate multiple AI agents in parallel for concurrent task executionExperience integrating LLMs into Python applications via the Anthropic SDK, OpenAI SDK, or LangChain/LlamaIndexExposure 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 haveWeb / API: FastAPI, Django REST Framework, Flask, etcDatabases: PostgreSQL, Redis, MongoDb, MySQLTask queues: Celery, RabbitMQ, KafkaAI/LLM: Anthropic Claude, OpenAI, LangChain, LlamaIndex, BMAD, SpecKit, OpenSpecTesting: pytestInfrastructure: Docker, GitLab CI/CD, AWS / GCPAI tooling: Claude Code, Cursor, GitHub CopilotVersion 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.