Junior Gen AI Engineer

Location: Santa Clara, CA (Onsite from Day 1)

Job Type: Contract

Experience Level: 3–7 Years (Software Development)

Key Responsibilities

• Demonstrate advanced programming expertise, particularly in Python, with deep proficiency in AI-centric libraries such as TensorFlow, PyTorch, and Hugging Face Transformers.
• Architect and implement Retrieval-Augmented Generation (RAG) pipelines to enhance model performance using external knowledge sources, including document chunking, embedding generation, and retrieval systems.
• Design, develop, and deploy Custom AI agents capable of autonomous decision-making and task execution using LLMs and multi-modal models.
• Implement and manipulate complex algorithms essential for developing and optimizing generative AI models.
• Manage data pipelines involving data pre-processing, augmentation, and synthetic data generation to enhance model training and performance.
• Ensure robust data handling practices including cleaning, labeling, and structuring datasets for generative AI workflows.
• Design MS Copilot Studio Agent Builder advanced skills, including custom plugin development, adaptive orchestration of multiple AI skills and APIs, contextual memory management, dynamic prompt engineering, and secure data handling.
• Agent Orchestration: Build multi-turn agents that adapt and chain AI skills and APIs.
• Trigger Management: Configure message, data, scheduled, and webhook triggers.
• Automation Workflow: Design workflows with Power Automate for task automation.
• Flow Design: Create logical, scalable flows for complex business processes.
• Tool Integration: Use Copilot’s built-in connectors to integrate enterprise apps and services seamlessly.

• Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.
• 3+ years of experience in AI/ML engineering, with at least 1 year focused on Generative AI.
• Hands-on experience with RAG architectures, including document chunking, embedding generation, and retrieval systems.
• Proficiency in Python and familiarity with libraries such as Hugging Face, Transformers, OpenAI API, and PyTorch/TensorFlow.
• Experience with Agentic AI frameworks (LangGraph, OpenAI SDK, AutoGen, CrewAI) and building agent accelerators using platforms like Copilot Studio or AWS Bedrock AgentsCore
• Strong understanding of LLM capabilities, limitations, and prompt engineering techniques.
• Experience with cloud platforms and containerization (Docker, Kubernetes).