Sr GenAI Engineer - VectorDBand PostgreSQL (IN)

This role is accountable for delivering robust AI-driven solutions by leveraging large language models and prompt engineering techniques. The individual applies in-depth expertise in Python, RESTful APIs, and database technologies to design, implement, and optimize generative AI applications, ensuring alignment with organizational standards and project objectives.

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.

Advanced proficiency in GenAI, large language models (LLMs), and prompt engineering. - Solid expertise in Python programming, including frameworks such as Flask, Django, and FastAPI. - In-depth knowledge of RESTful API design and implementation for AI integrations. - Advanced skills in database management using PostgreSQL, MySQL, and VectorDB technologies (e.g., Pinecone, AzureAISearch). - Strong understanding of embedding techniques and their application in generative AI workflows. - Experience in optimizing code quality, performance, and scalability of AI-driven applications.