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Digital & GenAI Analyst - Consulting at HEXAWARE
, , India -
Full Time

Start Date

Immediate

Expiry Date

03 Sep, 26

Salary

0.0

Posted On

05 Jun, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Python, Generative AI, LangChain, Vector Databases, FastAPI, Flask, RAG Pipelines, Prompt Engineering, SQL, NoSQL, TensorFlow, PyTorch, Docker, Cloud Environments, React, Pandas

Industry

IT Services and IT Consulting

Description
Role : AI Senior Developer Key Roles & Responsibilities: • Develop and implement GenAI applications, chatbots, and enterprise AI assistants. • Build and optimize RAG pipelines including: • Data ingestion (PDFs, docs, structured data) • Chunking, embeddings, indexing, and retrieval • Implement prompt engineering strategies and prompt workflows. • Develop APIs and microservices using FastAPI or Flask. • Integrate LLMs with: • SQL/NoSQL databases • Enterprise knowledge bases • Vector databases • Implement Text-to-SQL, conversational search, and semantic querying solutions. • Fine-tune and prompt-tune LLMs where required. • Write clean, scalable, and secure Python code. • Perform unit testing, debugging, and performance tuning. • Participate in code reviews and CI/CD pipelines. • Support production deployments and post-deployment monitoring. Required Skills & Experience: • 15+ years in software development with strong Python expertise. • Hands-on experience with: • LangChain or similar frameworks • Vector databases and embeddings • REST APIs and microservices • Working knowledge of HTML/CSS/React for basic UI integration. • Strong SQL skills and data processing with Pandas/NumPy. • Familiarity with Docker and cloud environments (AWS/Azure/GCP) is a plus. Additional Qualifications: • Bachelor’s or Master’s degree in Computer Science / AI / related. • 8+ years in software development with at least 3+ years building AI/ML applications. • Expert Python skills, including frameworks such as TensorFlow, PyTorch, transformers libraries. • Strong experience with REST APIs and microservices (Flask/FastAPI). • Proficiency with vector databases and embedding-based search systems.
Responsibilities
Develop and implement GenAI applications, chatbots, and enterprise AI assistants using RAG pipelines and prompt engineering. Build scalable APIs and microservices while integrating LLMs with various databases and knowledge bases.