Gen AI Engineer

Metasys Technologies

5 years

0 Lacs

hyderabad telangana india

Posted:1 day ago| Platform:

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Skills Required

ai retrieval engineering evaluation metrics design data aggregation preprocessing vectorization automation fastapi flask ml microservices aws azure model tuning configuration development devops containerization code python scalability integration docker

Work Mode

On-site

Job Type

Full Time

Job Description

Role: Gen AI Engineer / AI Solution Developer

Location: Hyderabad / Bangalore / Noida

Experience: 5+ Years

Responsibilities:

Develop, deploy, and optimize Generative AI solutions for production environments.
Build and maintain RAG (Retrieval-Augmented Generation) pipelines, including prompt engineering, evaluation metrics, and performance tuning.
Design and implement complete embedding pipelines involving data aggregation, preprocessing, chunking, and vectorization using state-of-the-art embedding models.
Work with GPT-4o/4/5 family models or similar foundational large language models to build intelligent applications and automation solutions.
Develop scalable backend services and APIs using FastAPI or Flask frameworks.
Deploy AI/ML and microservices-based applications on AWS or Azure, ensuring high availability and robustness.
Perform model fine-tuning, including parameter configuration, hyperparameter tuning, and evaluation for domain-specific tasks.
Contribute to the design and development of microservice architectures, ensuring modularity and maintainability.
Collaborate with DevOps teams and follow best practices in CI/CD, containerization, and cloud deployment.
Write clean, production-ready code using Python, ensuring best practices in performance, scalability, and security.

Required Skills:

Strong experience in building end-to-end GenAI applications.
Solid understanding of RAG architectures, embedding models, and vector databases.
Hands-on experience with LLM model integration and optimization.
Expertise in Python, FastAPI/Flask, and cloud computing (AWS/Azure).
Familiarity with DevOps practices, microservices, Docker, and CI/CD pipelines.

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