Designs, develops, evaluates, and implements enterprise AI solutions that address business challenges and improve operational outcomes.
Possesses both a strong understanding of AI concepts, model architectures, and emerging technologies, as well as hands-on experience developing AI applications using enterprise-approved AI platforms, frameworks, and development tools.
Demonstrates the ability to assess and apply diverse AI model types including large language models (LLMs), machine learning models, agent-based frameworks, retrieval-augmented generation (RAG), and other AI technologies to deliver practical business value.
Has real-world experience taking AI initiatives from problem definition and requirements gathering through solution design, model selection, implementation, testing, deployment, monitoring, and continuous improvement.
Primary Responsibilities:
• Partner with business and technology teams to identify and evaluate opportunities for AI-driven solutions
• Design, prototype, develop, test, and deploy AI applications and intelligent automation solutions
• Evaluate and select appropriate AI models, frameworks, and architectures to meet specific business objectives
• Develop and refine prompts, workflows, agents, and retrieval strategies to improve AI solution effectiveness
• Integrate AI capabilities with enterprise systems, databases, APIs, and business processes
• Monitor AI solution performance, accuracy, reliability, and adoption, and recommend improvements as needed
• Ensure compliance with enterprise security, governance, privacy, and Responsible AI standards
• Document solution designs, technical specifications, key decisions, testing results, and implementation procedures
• Stay current with emerging AI technologies, tools, and industry best practices, and recommend adoption where appropriate
• Achieve assigned deliverables with high quality within defined budgets and timelines
• Ability to interface with technology managers and business users throughout the company
• Design and implement AI-driven monitoring pipelines that ingest server, database, and application logs to predict system anomalies, suggest real-time resolutions, and automate post-incident root-cause analysis (RCA)
TECHNICAL SKILLS:
Must Have
Ability to evaluate, compare, and select appropriate AI technologies based on business and technical requirements
Experience integrating AI solutions with enterprise systems, APIs, databases, and business applications
Experience with cloud-based AI services and enterprise AI platforms
Experience working with Large Language Models (LLMs), Retrieval Augmented Generation (RAG), AI Agents, prompt engineering, and model orchestration frameworks
Git, DevOps, CI/CD practices, and version control
Hands-on experience with Azure AI, Microsoft Copilot Studio, Gemini Enterprise, Spark AI development platforms, frameworks, and tools
Python development and AI-related libraries/frameworks
SQL and data analysis skills
Strong understanding of AI/ML concepts, model evaluation techniques, model limitations, and responsible AI practices
Nice To Have
Experience applying AI/ML to IT operations (AIOps), specifically in predictive log analysis, automated incident remediation, and automated root-cause analysis
