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.