Description

Architect and deploy complex integration solutions centered around Generative AI and agentic systems.

Responsibilities

• Design, develop, and deploy GenAI and LLM-powered applications and products.
• Build and integrate Agentic AI systems featuring planning, reasoning, and decision-making components.
• Integrate AI models with enterprise IT systems using Agentforce or Salesforce Einstein.
• Apply Reinforcement Learning algorithms to agent training processes.
• Collaborate within Agile development environments to deliver scalable AI integrations.

Required Skills

• 8-10 years of experience as an Integration Architect.
• 2+ years of experience designing and deploying GenAI/LLM-powered products.
• 1+ years of experience building Agentic AI systems.
• Proficiency in Python and AI/ML libraries including TensorFlow, PyTorch, transformers, LangChain, LangGraph, AutoGen, and LlamaIndex.
• Experience with Natural Language Processing (NLP) techniques such as text generation, understanding, and summarization.
• Experience with Reinforcement Learning (RL) algorithms.
• Experience working with large datasets and cloud platforms including AWS, GCP, Azure, IBM, or Salesforce.
• Experience with version control systems like Git.
• Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (or equivalent practical experience).
• At least 2-3 certifications in AI, ML, GenAI, or Agentic AI disciplines from providers like Coursera, Udemy, or Deeplearning.AI.

Preferred Skills

• Experience with prompt engineering, fine-tuning LLMs, and multi-agent system coordination.
• Knowledge of knowledge graphs, semantic reasoning, and explainable AI (XAI) techniques.
• Experience with MLOps, model deployment pipelines, Docker, and Kubernetes.

Key Skills

Education

Any Gradute