Solution Architect

Job Description

• We are seeking a Solution Architect - Data & AI to lead end-to-end architecture across presales and delivery.
• The role will translate business requirements into scalable, secure, and commercially viable Data & AI solutions while providing technical leadership throughout implementation.

Key Responsibilities

• Lead Data & AI solutioning for RFPs, RFIs, tenders, proposals, and client engagements.
• Understand business objectives, data maturity, technical requirements, and AI opportunities.
• Develop solution architectures, estimates, delivery roadmaps, risks, dependencies, and implementation approaches.
• Design enterprise data platforms, analytics, AI/ML, GenAI, integration, security, and governance solutions across cloud, hybrid, and on-premises environments.
• Architect data lakes, data warehouses, lakehouses, streaming, ETL/ELT, metadata, lineage, and data quality solutions.
• Design GenAI solutions involving LLMs, RAG, embeddings, vector databases, and enterprise knowledge search.
• Define MLOps/ModelOps, model monitoring, AI lifecycle management, and responsible AI practices.
• Establish data and AI governance covering privacy, security, access control, compliance, transparency, and model risk.
• Evaluate and recommend technologies based on performance, scalability, security, reliability, and cost.
• Provide architecture leadership during delivery and ensure implementation aligns with approved designs.
• Conduct architecture reviews, resolve technical issues, and guide engineering teams.
• Develop architecture diagrams, solution blueprints, technical specifications, and design documentation.
• Present technical solutions and recommendations to senior business and technical stakeholders.

Minimum Requirements

• Bachelor's or Master's degree in Computer Science, Data Engineering, AI, Software Engineering, or a related field.
• 15+ years of technology experience, including significant experience in solution/data/AI architecture.
• Proven experience in both presales solutioning and delivery architecture for enterprise Data & AI projects.
• Strong knowledge of cloud platforms, modern data architecture, AI/ML, GenAI, integration, security, and governance.
• Experience with AWS, Azure, GCP, Databricks, Snowflake, Microsoft Fabric, Synapse, BigQuery, or equivalent platforms.
• Strong understanding of RAG, LLMs, vector databases, MLOps/ModelOps, and AI governance.
• Experience in consulting, technology services, or large-scale enterprise transformation.
• Excellent client-facing communication, presentation, documentation, and stakeholder management skills.
• Strong commercial awareness, analytical thinking, and problem-solving abilities.

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