AI/ML Engineer

Role Overview

As an AI/ML Engineer, you will be responsible for architecting, developing, and deploying production-grade Generative AI and Agentic AI solutions, including LLM-powered systems, autonomous workflows, and intelligent automation platforms that drive scalable business innovation. You will collaborate with cross-functional teams, oversee data infrastructure, and engage in the full lifecycle of AI projects from ideation to deployment.

Responsibilities

• Develop, validate, and implement Generative AI solutions and agentic AI workflows.
• Collaborate with data scientists and stakeholders to define project goals.
• Maintain data infrastructure to ensure scalability and efficiency.
• Stay updated with advancements in Large Language Models and emerging AI technologies.
• Communicate complex data findings to non-technical stakeholders.
• Adhere to data privacy and security guidelines.
• Participate in the entire AI project lifecycle, from concept to deployment and maintenance.

Requirements

• Bachelor's or higher degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field.
• 2-4 years of hands-on experience in AI/ML, specifically in Generative AI and Agentic AI.
• Strong grasp of computer architecture, data structures, and AI fundamentals.
• Experience in design and optimization of agentic AI workflows using frameworks like LangChain, LangGraph, or CrewAI.
• Experience with Vector databases such as Qdrant, ChromaDB, Pinecone, or PGVector.
• Experience with LLM integration frameworks like LlamaIndex or Ragas.
• Proficiency in Python development in a Linux environment.
• Experience deploying AI workloads on distributed systems.
• Knowledge of cloud computing platforms such as AWS, Azure, or Google Cloud.

Nice to Have

• Experience with ML model lifecycle management, including training, quantization, and deployment.
• Experience with deep learning frameworks such as PyTorch, TensorFlow, Keras, or Spark.
• Working knowledge of architectures like ANNs, CNNs, RNNs, and GANs.
• Experience with Computer Vision (e.g., ResNet) or Recommendation Systems (e.g., DLRM).

Skills

• Python
• LangChain
• PyTorch
• Vector Databases
• AWS