Job Description

Job Summary:

We are looking for

1

to 2 year experienced

AI & Data Retrieval Engineer

to develop natural language query (NLQ) and Text-to-SQL systems for PostgreSQL. The ideal candidate has expertise in LLMs, NLP, AI-powered SQL generation, and vector search using tools like LangChain, LlamaIndex, Haystack, and pgVector. You will design and optimize AI-driven search and data retrieval solutions, enabling accurate and efficient query execution.

Key Responsibilities:

Develop AI-powered query systems:

Implement LLM-based SQL generation and vector search techniques for efficient natural language querying on PostgreSQL.

Integrate NLP & Database Technologies:

Use LangChain SQL Agent, LlamaIndex, Haystack, pgVector, FAISS, or Pinecone for efficient retrieval.

Optimize Database Queries:

Ensure fast and accurate retrieval from PostgreSQL by optimizing SQL queries and indexing techniques.

Implement Vector Search:

Use pgVector or FAISS for semantic search on unstructured database fields.

Fine-Tune LLMs:

Improve accuracy by fine-tuning OpenAI, Hugging Face models, or custom LLMs on database schema.

API Development & Integration:

Build APIs that allow front-end applications and BI tools to interact with AI-driven queries.

Security & Compliance:

Implement access control and secure querying to prevent SQL injection and ensure data privacy.

Monitor Performance:

Continuously improve accuracy, response time, and efficiency of AI-generated SQL queries.

Required Skills & Experience:

1+ years of experience in AI-powered SQL query generation, NLP, and PostgreSQL. Hands-on experience with LangChain, LlamaIndex, Haystack, or similar AI-powered search frameworks. Strong understanding of SQL query optimization and PostgreSQL indexing strategies. Experience with vector search databases like pgVector, FAISS, Weaviate, Pinecone. Familiarity withLLMs (GPT-4, Llama 2, Claude, DeepSeek Coder, etc.) for SQL generation. Proficiency inPython (FastAPI, Flask, Django) and AI/ML libraries (Transformers, OpenAI API, Hugging Face). Experience in building AI-driven chatbot or search systems is a plus. Knowledge ofBI tools (Metabase, Superset, Power BI) and their integration with AI-powered query systems. Preferred Qualifications:Experience working onlarge-scale NLP & database integration projects. Previous work with RAG (Retrieval-Augmented Generation) architectures. Knowledge of embedding models (BERT, OpenAI Embeddings, Cohere, etc.). Experience in deploying LLM-based SQL query engines in production environments.
Job Type: Full-time

Pay: ?20,000.00 - ?30,000.00 per month

Experience:

relevant: 1 year (Preferred)
Work Location: In person