Python Developer

Skill: Python Developer (Backend & AI)

Experience: 4 - 5 years

Location: Gurgaon

Work Mode: Work From Office

Job Description:

About the Role

We are hiring a Python developer with 4-5 years of experience to join our engineering team. In this role, you will design and build backend services and AI-driven features using Python and FastAPI, contribute to our microservices platform, and work on integrations with modern Large Language Models (LLMs). You will work closely with product, design and other engineers to turn requirements into reliable, well-tested systems.

Key Responsibilities

• Design, develop and deploy backend services and APIs using Python and FastAPI.

• Contribute to the design of our microservices: service boundaries, API contracts and inter-service communication.

• Build and integrate AI/LLM-powered features, including prompt design, model orchestration and integrations with LLM providers.

• Containerise services using Docker and work with the DevOps team on stable deployment pipelines.

• Write clean, well-tested and well-documented code, and take part in code reviews.

• Investigate and resolve issues across development, staging and production environments.

• Track relevant developments in the Python and AI ecosystem and bring useful ideas back to the team.

Must-Have Skills & Experience

• Python: 4-5 years of professional experience writing production Python.

• FastAPI: Strong, hands-on experience building RESTful APIs and backend services with FastAPI.

• Microservices: A working understanding of microservice architecture, including service boundaries, communication patterns and common trade-offs.

• Docker: Comfortable writing Docker commands, working with containers and running services locally.

• LLMs: A solid conceptual understanding of how Large Language Models work — prompts, tokens, context windows and embeddings — and practical experience integrating with LLM APIs (such as OpenAI, Anthropic or similar).

• Databases & APIs: Practical experience with SQL and/or NoSQL databases and with designing or consuming REST APIs.

• Version control: Proficient with Git and modern collaborative workflows.

• Mindset: Curious, self-driven and a go-getter who takes ownership of problems and sees them through to closure.

Good to Have

• Experience with asynchronous Python (asyncio, async/await) and a clear sense of when to use it.

• Hands-on experience with message queues such as Kafka, RabbitMQ or Redis Streams, or with event-driven architectures.

• Familiarity with cloud platforms such as AWS, GCP or Azure.

• Practical experience with vector databases, RAG (Retrieval-Augmented Generation) pipelines, or frameworks like LangChain or LlamaIndex.

• Working knowledge of CI/CD pipelines and basic Kubernetes concepts.

• AI-assisted coding tools: Practical experience using AI-enabled coding tools such as Cursor, Kiro or similar in day-to-day development, with a clear view of where they add value and where they do not.

• Spec-driven development: Familiarity with spec-driven development — writing clear specifications upfront and using them to guide design, implementation and testing.

• Contributions to open-source projects or a strong portfolio of personal work.

What We Value

• Curiosity — a genuine interest in understanding how things work and a willingness to dig in when you do not know something.

• Ownership — taking responsibility for your work end-to-end, without waiting to be prompted.

• Clarity — communicating well in writing and in conversation, and respecting other people's time.

• Quality — caring about clean, maintainable code that is easy for the next engineer to read.

• Collaboration — working well with peers, supporting more junior team members and learning from others.

Education

A Bachelor's degree in Computer Science, Engineering or a related field, or equivalent practical experience.

What We Offer

• Meaningful work at the intersection of backend engineering and modern AI.

• A high-trust, low-bureaucracy environment with real ownership of what you build.

• Direct exposure to LLM-powered product development, with room to experiment and shape how we use it.

• Competitive compensation, a learning budget and capable colleagues to learn from.