Senior Solutions Architect

Senior Solution Architect – Agentic AI & Enterprise Data (Microsoft Ecosystem)

We are seeking a high-caliber Principal Solution Architect to spearhead the strategy, design, and technical delivery of next-generation Agentic AI use-cases for our enterprise clients. This is a high-visibility, client-facing role that requires a rare mix of deep Microsoft Copilot/Generative AI expertise and a rock-solid background in Data & Analytics
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The ideal candidate must be comfortable navigating a "mixed bag" enterprise environment—seamlessly bridging legacy data warehouses with modern cloud data platforms. You will confidently lead "nuts and bolts" technical workshops, transform abstract client business problems into sophisticated solution architectures, and command the technical respect required to win new client engagements.

• Technical Client Advisory: Partner with client stakeholders to analyze enterprise use-cases, deconstruct complex business processes, and translate them into production-ready AI solutions.
• Solution Architecture & Design: Architect end-to-end agentic AI workloads, multi-agent orchestrations, hybrid code/low-code agent logic, and secure Retrieval-Augmented Generation (RAG) frameworks.
• Nuts-and-Bolts Engineering Leadership: Deeply engage with client enterprise architects, data engineers, and security teams. You must be able to white-board, code-review, and defend architecture patterns (e.g., API security, model orchestration, data pipelines).
• Enterprise Data Integration: Connect autonomous agents to a diverse data estate. Design optimal semantic layers, data schemas, and pipelines across legacy systems and modern data lake houses.
• 3rd Party Integration (Read/Write): Enable agents to securely interact with external enterprise ecosystems (SAP, Salesforce, Oracle, etc.) through custom connectors and robust API handling.
• AI Guardrails & Compliance Advisory: Assess the client's current maturity level regarding AI safety and compliance. Provide actionable blueprints and recommendations to mature their AI guardrails (data masking, tokenization, and responsible AI practices).

• Data & Analytics Background: 4–5 years of foundational experience in enterprise data engineering, data modeling, or data architecture across hybrid environments:
• Legacy: SQL Server, Azure SQL, and Azure Synapse.
• Modern: Microsoft Fabric, One Lake, Databricks, and Delta Lake.
• Copilot & GenAI Expertise: 4–5 years of progressive experience working with Conversational AI, Large Language Models (LLMs), and deep technical implementation of the Microsoft Copilot ecosystem (Copilot Studio, Azure OpenAI, Azure AI Foundry).
• Foundational Coding
  
  Languages:
  
  Strong proficiency in programming and data processing using Python, PySpark, and SQL to support custom agentic logic and data transformations.
• Integration Depth: Proven experience orchestration workflows that require reading and writing data into 3rd party enterprise applications like SAP, Salesforce, or Oracle using custom Power Platform connectors, Graph Connectors, and OAuth/API integration.
• The Microsoft Stack: Advanced technical depth across:
• AI/Agents: Copilot Studio, Azure AI Search, Semantic Kernel, Prompt Flow, or Lang Chain.
• Security/Governance: Microsoft Purview, Azure Entra , and Azure AI Content Safety.
• Communication Style: Exceptional presentation and articulation skills. Able to pivot seamlessly between high-level business value for C-suite executives and deep technical mechanics for engineering teams.

• Cross-Platform Cloud & AI Expertise: Hands-on experience with alternative cloud platforms and AI ecosystems, specifically:
• Google Cloud: Vertex AI, Gemini, or Big Query ML.
• Independent AI Tools: Experience with OpenAI Enterprise APIs, Anthropic Claude API, or Snowflake (Cortex AI).
• Certifications: Microsoft Certified:
  Azure AI Engineer Associate, Power Platform Solution Architect Expert, AWS Certified Solutions Architect, or Google Cloud Professional Cloud Architect.

Please reach out to rithika.