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

2. 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

3. 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

4. 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

5. 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