Bengaluru, Karnataka
Job Summary
Role: Python Lead EngineerMandatory skills: Python backend development, Rest APIs (FastAPI, Django, or Flask), SQL (PostgreSQL) and NoSQL (Redis, MongoDB), Any frameworks for agentic workflows (LangChain, LlamaIndex)Role Overview: We are looking for a Python Backend Engineer to build the backbone of our platform. You will be responsible for creating high-performance APIs, integrating advanced AI agent logic, and ensuring our infrastructure remains rock-solid as we scale. If you enjoy solving complex architectural puzzles and want to work at the intersection of traditional backend engineering and AICore ResponsibilitiesScalable API Development: Design, build, and maintain robust, high-throughput APIs (FastAPI, Django, or Flask) capable of handling millions of requests.Agent Logic Integration: Architect the backend systems that power our AI agents, managing long-running tasks, state persistence, and seamless communication between LLMs and our core services.Authentication & Security: Implement and manage secure identity protocols (OAuth2, JWT, OpenID Connect) to protect user data and internal endpoints.Routing & Orchestration: Design efficient request routing and service communication patterns using tools like API Gateways, or Service Meshes.Required Technical SkillsLanguage: Expert-level proficiency in Python (3.10+ preferred).Frameworks: Deep experience with FastAPI, DjangoAI Tooling: Familiarity with LangChain, LlamaIndex, or similar frameworks for agentic workflows.Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate).Infrastructure: Proficiency with Docker, AWS/GCP, and asynchronous task queues
Key Responsibilities
1. Provide advanced proficiency in GenAI and prompt engineering by designing, refining, and deploying LLM-driven solutions using Python frameworks such as Flask, Django, and FastAPI.
2. Architect and implement RESTful APIs to integrate LLM models and vector databases (e.g., Pinecone, PostgreSQL, AzureAISearch) for scalable and efficient data retrieval in AI applications.
3. Optimize database schemas and embeddings using PostgreSQL and VectorDB to enhance performance and accuracy of generative AI systems.
4. Oversee code quality and performance by conducting comprehensive code reviews and enforcing best practices in Python, RESTful API development, and prompt engineering.
5. Lead technical feasibility studies and solution breakdowns, evaluating architecture alternatives and technical risks for GenAI project modules.
6. Collaborate with internal stakeholders to define technical objectives, deliverables, and ensure process compliance in the development and deployment of AI-powered solutions.
Skill Requirements
1. Advanced Proficiency In Genai, Large Language Models (Llms), And Prompt Engineering.
2. Solid Expertise In Python Programming, Including Frameworks Such As Flask, Django, And Fastapi.
3. Indepth Knowledge Of Restful Api Design And Implementation For Ai Integrations.
4. Advanced Skills In Database Management Using Postgresql, Mysql, And Vectordb Technologies (E.G., Pinecone, Azureaisearch).
5. Strong Understanding Of Embedding Techniques And Their Application In Generative Ai Workflows.
6. Experience In Optimizing Code Quality, Performance, And Scalability Of Aidriven Applications.
Other Requirements
1. Optional but valuable:
2. Certifications such as TensorFlow Developer Certificate
3. - Microsoft Azure AI Engineer Associat
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