Job Title: AI/ML Engineer (GenAI & System Modernization)

Experience: 4 to 8 years

Work Mode: HybridLocation: Bangalore

Job Overview:

We are seeking AI engineers passionate about Generative AI and AI-assisted modernization to build cutting-edge solutions. The candidate will work on in-house GenAI applications, support AI adoption across the organization, collaborate with vendors for POCs, and contribute to legacy system modernization using AI-driven automation.

Key Responsibilities:

Design & develop in-house GenAI applications for internal use cases.

Collaborate with vendors to evaluate and implement POCs for complex AI solutions.

Work on AI-powered tools for SDLC modernization and code migration (legacy to modern tech).

Provide technical support, training, and AI adoption strategies for internal users & teams.

Assist in integrating AI solutions into software development processes.

Must Have:

Bachelor’s / Master’s degree in Computer Science / Computer Engineering / Computer Applications / Information Technology OR AI/ML-related field.

Relevant certification in AI/ML is an added advantage.

Minimum of 2 successful AI/ML POCs or production deployments.

Prior experience in AI-powered automation, AI-based DevOps, or AI-assisted coding.

Proven track record of teamwork and successful project delivery.

Strong analytical and problem-solving skills with a continuous learning mindset.

A positive, can-do attitude with attention to detail.

AI/ML Expertise:

Strong hands-on Python programming experience.

Experience with Generative AI models and LLMs/SLMs (worked on real projects or POCs).

Hands-on experience in Machine Learning & Deep Learning.

Experience with AI/ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face).

Understanding of MLOps pipelines and AI model deployment.

System Modernization & Enterprise Tech Familiarity:

Basic understanding of Java, Spring, React, Kotlin, and Groovy.

Experience and willingness to work on AI-driven migration projects (e.g., PL/SQL to Emery, JS to Groovy DSL).

Experience with code quality, AI-assisted code refactoring, and testing frameworks.

Enterprise Integration & AI Adoption:

Ability to integrate AI solutions into enterprise workflows.

Experience with API development & AI model integration in applications.

Familiarity with version control & collaboration tools (Git, CI/CD pipelines).