AI Architect

Job Summary:

We are seeking a technical and consultativeLead AI Solutions Engineer to join our IT Services team for a global manufacturing client. In this high-impact role, you will act as the strategic right-hand to the AI Lead; capturing visionary "loud thinking," converting abstract ideas into actionable blueprints, and building production-grade solutions.

You will bridge the gap between technical execution and business strategy: evaluating incoming AI requests, establishing secure experimentation guardrails on Azure and Databricks, and delivering scalable AI applications across GenAI, Agentic AI, and classical ML.

Key Responsibilities:

• Strategic Execution & Blueprinting:
• • Partner closely with the AI Lead to synthesize strategic goals into clear technical architectures, roadmaps, and execution plans.
  • Define end-to-end AI project lifecycles from proof-of-concept (PoC) to full production deployment.
• Use Case Triage & Business Consultation:
• • Evaluate business requests from the manufacturing user community; filter hype from high-value, credible AI use cases.
  • Guide business stakeholders on AI feasibility, ROI, risk, and expected outcomes with confidence and clarity.
• Hands-on Development & Deployment:
• • Design, build, test, and deploy robust AI solutions spanning Generative AI, Agentic workflows, and traditional machine learning models.
  • Integrate solutions seamlessly within Microsoft Azure and Databricks ecosystems.
• Infrastructure, Guardrails & Experimentation:
• • Provision and manage the required Azure/Databricks cloud infrastructure to enable safe sandbox experimentation for users.
  • Implement governance, security protocols, Responsible AI guardrails, cost-tracking, and telemetry across all AI deployments.
• Stakeholder Management:
• • Communicate complex technical concepts effectively to non-technical business leaders and operational teams.
  • Drive alignment across cross-functional enterprise teams, including IT, Data Engineering, Security, and Business Operations.

Technical Expertise

• AI & GenAI: Deep understanding of Machine Learning fundamentals, Deep Learning, Large Language Models (LLMs), Fine-Tuning, RAG (Retrieval-Augmented Generation), and Agentic Frameworks (e.g., LangChain, AutoGen, CrewAI, Semantic Kernel).
• Cloud Platform: Advanced hands-on experience withMicrosoft Azure (Azure OpenAI Service, Azure ML, Azure Functions, Azure Cosmos DB/Vector Stores).
• Data Engineering: Strong proficiency inDatabricks (PySpark, Delta Lake, MLflow, Unity Catalog) for data processing and model deployment.
• DevOps/MLOps: Experience setting up CI/CD pipelines, containerization (Docker, Kubernetes), and monitoring for AI workloads.

Core Competencies

• Consultative & Analytical Mindset: Strong capability to dissect hype, assess technical feasibility, and prioritize business impact.
• Communication: Exceptional verbal and written communication skills to manage stakeholders, lead technical reviews, and articulate complex solutions clearly.

Preferred Experience

• Proven track record of working on Microsoft Azure and Databricks platforms.
• 5+ years of experience in Data Science, Machine Learning, or AI Engineering.
• 2+ years of hands-on experience designing and deploying GenAI/Agentic solutions in enterprise environments.