Python Full Stack Engineer

AI / Backend Engineering

• Develop and maintain Python-based backend services and APIs using frameworks like FastAPI, Flask, or Django.
• Build and integrate AI/ML models, including LLMs, RAG systems, embeddings, and vector databases.
• Implement agentic AI workflows that can call tools, orchestrate tasks, and automate actions.
• Build scalable data pipelines for model training and inference.
• Optimize models for performance, latency, and cost.

Frontend Engineering

• Develop responsive UI using React, Next.js, or similar frameworks.
• Integrate frontend with backend AI services and APIs.
• Build dashboards, chat interfaces, and workflow screens interacting with AI outputs.

Full-Stack Ownership

• Translate business requirements into technical design and working software.
• Own the end-to-end delivery of features from design to production.
• Build reusable components and maintain coding best practices.
• Collaborate closely with product, design, and data/ML teams.

DevOps / Cloud

• Deploy full-stack applications on AWS/Azure/GCP.
• Implement CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI).
• Work with containerization technologies like Docker and Kubernetes.
• Manage vector databases (Pinecone, FAISS, Chroma) and document stores (MongoDB, PostgreSQL, DynamoDB).

Required Skills

• Strong proficiency in Python for backend and AI development.
• Experience with FastAPI / Flask / Django.
• Experience with c#.
• Hands-on experience with LLMs, RAG, embedding models, and AI agent frameworks.
• Excellent understanding of REST APIs, microservices, and distributed systems.
• Frontend experience with React, Next.js, Typescript, HTML/CSS.
• Familiarity with cloud services such as AWS Lambda, S3, EC2, API Gateway, Bedrock, SageMaker, or Azure OpenAI.
• Experience with SQL and NoSQL databases.
• Strong debugging, optimization, and production support skills.

Preferred Skills

• Experience with vector databases (Pinecone, FAISS, Weaviate).
• Knowledge of LangChain, LlamaIndex, or OpenAI function-calling agents.
• Experience building chatbots or agentic AI solutions.
• Knowledge of MLOps, monitoring tools, and observability.
• Familiarity with event-driven architectures (Kafka, Kinesis).
• Basic understanding of UI/UX principles.

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (preferred).
• 3–8+ years of experience in software engineering, including at least 1–2 years in AI/ML or LLM-based application development.