AI Development Engineer - Onshore

Pragma Edge Inc; Hyderabad; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

Pragma Edge Inc in Hyderabad, India seeks an experienced AI Engineer to design and deploy agentic generative AI solutions, leveraging LLMs, RAG pipelines, and context engineering. The role involves building multi-agent automation, API development with FastAPI/Flask, and advancing MLOps practices.

You will collaborate with AI architects, product managers, and compliance teams to ensure governance, safety policies, and robust deployment.

Qualifications

• Proficiency in Python, SQL, and Java for building AI solutions.
• Deep expertise in prompt engineering, LLMs, governance and model safety.
• Experience with Streamlit and basic UI/UX concepts.

Responsibilities

• Design and deploy agentic generative AI solutions using LLMs, RAG pipelines, prompt engineering, and REST APIs.
• Architect and build multi-agent automation systems using LangGraph or similar orchestration platforms.
• Implement LLM governance architecture including prompt drift detection, auditability, and safety policies to ensure regulatory compliance.
• Develop and integrate vector database solutions for semantic search and retrieval-augmented generation.
• Collaborate cross-functionally with AI architects, product managers, and compliance teams to accelerate AI adoption across business units.
• Develop APIs using FastAPI/Flask and build interactive demos for stakeholder showcases.
• Contribute to MLOps practices including CI/CD pipelines, model monitoring, and deployment automation.
• Conduct research experiments to enhance model performance, reliability, and fairness.
• Build and maintain ML models for domain-specific tasks such as NLP, computer vision, and predictive analytics.

Skills

Python

SQL

Java

LLMs

RAG

Prompt engineering

Fine-tuning

Model governance

LangGraph

FastAPI

Flask

Streamlit

UI principles

Tools

LangGraph

FastAPI

Flask

REST APIs

Job description

• Design and deploy agentic generative AI solutions leveraging LLMs, RAG pipelines, context engineering, and REST APIs.
• Architect and build multi-agent automation systems using frameworks such as LangGraph or similar orchestration platforms
• Implement LLM governance architecture including prompt drift detection, auditability, and safety policies to ensure regulatory compliance.
• Develop and integrate vector database solutions for semantic search and retrieval-augmented generation.
• Collaborate cross-functionally with AI architects, product managers, and compliance teams to accelerate AI adoption across business units.
• Develop APIs using FastAPI/Flask and build interactive demos for stakeholder showcases.
• Contribute to MLOps practices including CI/CD pipelines, model monitoring, and deployment automation.
• Conduct research experiments to enhance model performance, reliability, and fairness.
• Build and maintain ML models for domain-specific tasks such as NLP, computer vision, and predictive analytics.

Required Qualifications

Technical Skills

• Programming: Proficiency in Python; working knowledge of SQL and Java.
• GenAI & LLMs: Deep expertise in LLMs, RAG, prompt engineering, fine-tuning, and model governance.
• Visualization & UI: Streamlit, basic UI/UX design principles.