Senior AI Engineer

Senior AI Engineer

Role Overview

• Lead the design, development, and deployment of advanced AI systems
• Build cutting-edge solutions across machine learning, NLP, generative AI, LLMs, and multi-agent orchestration
• Drive innovation across our product portfolio by solving real-world problems

Key Responsibilities

• Architect, build, and deploy production-grade AI/ML systems at scale
• Design and develop RAG pipelines, agentic AI systems, and multi-agent orchestration solutions
• Build intelligent automation flows and conversational AI agents using frameworks like LangGraph, LangChain, and Microsoft Copilot Studio
• Develop time-series forecasting and anomaly detection models for real-world business use cases
• Apply advanced prompt engineering and integrate Model Context Protocol (MCP) to connect AI agents with enterprise systems
• Own the full AI project lifecycle - from data ingestion and preprocessing through model training, evaluation, deployment, and monitoring
• Collaborate with data scientists, software engineers, and product managers to translate business needs into AI-powered solutions
• Optimize model performance and ensure robustness, fairness, and explainability
• Stay current with the latest AI/ML research and bring relevant advancements into our stack

Our Technology Landscape

• Retrieval-Augmented Generation (RAG) pipelines
• Agentic AI frameworks (e.g., LangGraph, LangChain)
• Multi-agent orchestration systems
• Model Context Protocol (MCP) integrations
• Advanced prompt engineering
• Time-series modeling, forecasting, and anomaly detection
• Intelligent automation flows and workflow orchestration
• Microsoft Copilot Studio for building and deploying custom copilots and conversational AI agents

Required Qualifications

• Bachelors or Masters degree in Computer Science, AI, Machine Learning, or a related field (PhD preferred)
• 5+ years of AI/ML engineering experience with a proven track record of shipping models to production
• Proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
• Experience with cloud platforms (AWS, Azure) and MLOps tools
• Strong understanding of data structures, algorithms, and software engineering principles
• Solid grounding in software engineering best practices and system design
• Experience designing and building automation workflows or process automation systems
• Excellent problem-solving and communication skills