Solutions Architect/Engineer - Data & Agentic AI Solutions

JOB TITLE- Solutions Architect/Engineer - Data & Agentic AI Solution Role Summary Client is seeking a highly technical, Agentic AI Solutions Architect/Engineer with deep expertise in Data Platforms, Cloud Architecture, AI/ML Operations, and Agentic AI solution implementation. This role is not a traditional delivery-only Data Architect role. The ideal candidate must be able to: Operate effectively in highly ambiguous environments Rapidly transform incomplete client requirements into structured technical solutions Build assumptions, workload models, LOE estimates, and delivery approaches Interface directly with Sales, Clients, Delivery, and Practice Leadership Prototype and operationalize modern data and AI architectures Support pre-sales, RFP responses, and technical solutioning Create reusable accelerators, frameworks, and implementation patterns The role combines: Data & AI Solution Architecture Forward Deployment Engineering Technical Consulting Solutioning & Estimation Client Engagement Prototype & Accelerator Development This individual will work closely with: Practice Leads Solutions Architects Proposal Managers Pricing Analysts Delivery Teams Sellers and Client Stakeholders What Success Looks Like Successful candidates are able to: Take vague business requirements and rapidly create structure, assumptions, and solution direction Build end-to-end data and AI implementation strategies with minimal guidance Clearly communicate architecture concepts to both technical and business stakeholders Develop practical LOE models and staffing approaches aligned to delivery realities Operate independently under tight timelines and incomplete information Build trust with sellers, practice leads, and clients through responsiveness, ownership, and communication Create reusable IP and technical accelerators for the Data Intelligence Practice Key Responsibilities 1. Forward Deployment Engineering & Client Solutioning Partner directly with clients, sellers, and practice leadership to understand business challenges and technical requirements Rapidly design and prototype scalable data and AI solutions Translate incomplete or evolving client requirements into actionable architecture and delivery plans Conduct technical discovery workshops and architecture whiteboarding sessions Support client demonstrations, proof-of-concepts, pilot implementations, and modernization initiatives Design and operationalize cloud-native and AI-enabled data platforms Troubleshoot and resolve architecture, integration, and deployment issues during solution development Data Platform & AI Architecture Design modern data platforms using: Snowflake Databricks Azure Synapse Microsoft Fabric AWS Data Services Lakehouse / Medallion Architectures Data Mesh Patterns Design scalable ingestion, transformation, orchestration, and analytics frameworks Implement metadata-driven and self-healing pipeline concepts Design lineage, governance, and cataloging approaches using: Microsoft Purview Collibra Alation Snowflake Horizon Design secure, compliant architectures aligned with enterprise governance requirements Implement AI-ready data architectures for: RAG systems Agentic AI frameworks Vector databases LLM integrations Semantic search AI orchestration frameworks Agentic AI & AI Enablement Build and operationalize AI workflows using: OpenAI Azure OpenAI Claude Gemini LangChain LangGraph Semantic Kernel Vector databases Support development of: AI agents AI copilots Retrieval Augmented Generation (RAG) AI orchestration pipelines Autonomous workflows Participate in AI governance, observability, prompt engineering, and model evaluation activities Develop reusable AI accelerators and implementation templates Pre-Sales, Estimation & Commercial Solutioning Participate in RFP, RFI, and proposal response development Build: Assumptions frameworks Workload models Staffing models LOE estimates Delivery approaches Pricing support inputs Collaborate with: Proposal Management Pricing Analysts Recruiting Delivery Leadership Translate technical architectures into delivery staffing and operational models Support architecture reviews, proposal reviews, and red team reviews Participate in technical orals and client solution presentations Practice Development & IP Creation Build reusable: Architecture templates Estimation frameworks Accelerators Governance models Technical playbooks AI implementation patterns Support development of the Data Intelligence Center of Excellence (COE) Contribute to GTM strategy and packaged service offerings Collaborate with Marketing on technical collateral and case studies Required/Desired Technical Skills Cloud & Data Platforms Azure Data Factory (ADF) Azure Synapse Databricks Snowflake Microsoft Fabric AWS Data Services (Glue, Redshift, Athena, Lambda, EMR) Data Lakes / Lakehouse architectures Kafka / Event Streaming AI / ML / Agentic AI OpenAI / Azure OpenAI LangChain / LangGraph RAG architectures Vector databases AI orchestration frameworks Prompt engineering LLM integration patterns AI observability concepts Engineering & DevOps Python SQL PySpark APIs & Microservices Terraform CI/CD pipelines GitHub / Azure DevOps Docker / Kubernetes Governance & Security RBAC / IAM Data lineage Metadata management Data governance frameworks Enterprise security and compliance standards Required Experience 8-15 years of experience in Data Engineering, Cloud Architecture, Analytics, AI/ML, or Solution Architecture Strong hands-on implementation experience in enterprise data platforms Experience supporting client-facing consulting or pre-sales activities Experience building technical proposals, architecture diagrams, and implementation approaches Experience of working directly with business stakeholders and enterprise clients Experience operating in ambiguous, fast-moving consulting environments Experience estimating projects and supporting staffing / LOE models