Generative AI Engineer_4+yrs

Zorba AI; Bengaluru; On-site; INR 1,000,000 - 2,000,000; Full time

Job summary

A leading AI technology firm in Bengaluru is seeking a skilled professional to design and develop innovative application solutions utilizing generative models. The ideal candidate should have 4-10 years of experience and be proficient in Python, AWS, and data pipeline optimization. Responsibilities include collaborating with cross-functional teams and adapting the latest generative AI technologies for business needs. Excellent documentation and communication skills are essential to succeed in this role.

Qualifications

• 4-10 years of experience in relevant fields.
• Experience fine-tuning generative models.
• Ability to explain technical concepts to non-technical stakeholders.

Responsibilities

• Design and develop application solutions using generative models.
• Collaborate with teams to integrate generative AI solutions.
• Research advancements in generative AI technologies.
• Create comprehensive documentation for generative AI models.

Skills

Strong proficiency in Python

Effective prompt engineering techniques

Hands-on experience with generative text models

Proficiency in AWS Bedrock

Solid experience with AWS serverless architecture

Experience building and optimizing data pipelines

Excellent documentation skills

Strong communication skills

Tools

AWS

Azure

GCP

GitHub Copilot

Git

Job description

Overview

Design and develop application solutions using generative models, RAG and vector database and vector search. Collaborate with cross-functional teams to integrate generative AI solutions into existing workflow systems. Research and stay current on the latest advancements in generative AI technologies, methodologies, and best practices. Optimize and fine-tune generative models for performance, scalability, and efficiency. Troubleshoot and resolve issues related to generative AI models, implementations, and workflows. Create and maintain comprehensive documentation for generative AI models and their applications. Build efficient data pipelines and manage large datasets for model training and evaluation. Measure model outputs using appropriate metrics, with awareness of bias and fairness issues. Implement and use AI coding assistants (e.g., GitHub Copilot) and version control (Git). Conduct rigorous testing and build scalable, maintainable systems. Read, analyze, and implement recent AI research papers; conduct experiments as needed. Communicate complex technical concepts and findings to non-technical stakeholders.

Experience

4-10 Years.

Key Responsibilities

• Design and develop application solutions using generative models, RAG and vector database and vector search.
• Collaborate with cross-functional teams to integrate generative AI solutions into existing workflow systems.
• Research and stay current on the latest advancements in generative AI technologies, methodologies, and best practices.
• Optimize and fine-tune generative models for performance, scalability, and efficiency.
• Troubleshoot and resolve issues related to generative AI models, implementations, and workflows.
• Create and maintain comprehensive documentation for generative AI models and their applications.
• Build efficient data pipelines and manage large datasets for model training and evaluation.
• Measure model outputs using appropriate metrics, with awareness of bias and fairness issues.
• Implement and use AI coding assistants (e.g., GitHub Copilot) and version control (Git).
• Conduct rigorous testing and build scalable, maintainable systems.
• Read, analyze, and implement recent AI research papers; conduct experiments as needed.
• Communicate complex technical concepts and findings to non-technical stakeholders.

Required Qualifications

• Strong proficiency in Python and effective prompt engineering techniques; familiarity with other programming languages is a plus.
• Hands-on experience with leading generative text models (e.g., Claude, OpenAI GPT, Gemini), including model fine-tuning and customization.
• Proficiency in AWS Bedrock, including model access and knowledge base implementations; experience with Azure OpenAI.
• Solid experience with AWS serverless architecture; familiarity with Azure or GCP is desirable.
• Experience building and optimizing data pipelines for handling large-scale datasets.
• Knowledge of metrics for evaluating model performance, including bias and fairness considerations.
• Experience with AI coding assistants (e.g., GitHub Copilot), version control systems (Git), and scalable system design.
• Excellent documentation skills and experience collaborating with multi-disciplinary teams.
• Strong communication skills, with the ability to present technical concepts to non-technical audiences.