Sr Tech Lead-GenAI - VectorDBand PostgreSQL

Job Summary

This role is accountable for delivering advanced Generative AI solutions by leveraging large language models and prompt engineering techniques. The position drives technical excellence in project execution, ensures robust solution design, and optimizes AI-driven applications using modern Python frameworks and scalable database technologies. The individual acts as a technical authority, guiding teams in implementing best practices, and plays a key role in the successful delivery of complex AI projects aligned with organizational goals.

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 Tensor Flow Developer Certificate

• Microsoft Azure AI Engineer Associat