Solutions Architect - Data & AI

Overview

Elliott Moss Consulting is looking for an experienced Solutions Architect specialized in Data and AI to oversee the architecture lifecycle from presales through delivery. The position involves converting business goals into scalable, secure, commercially sound Data & AI solutions while guiding technical implementation.

Key Responsibilities

• Lead Data & AI solution design activities for proposals, tenders, RFPs, and client interactions.
• Analyze business goals, data maturity level, technical needs, and AI opportunities to tailor solutions.
• Create architectures, project estimates, delivery roadmaps, identify risks and dependencies, and propose implementation strategies.
• Design enterprise data platforms incorporating analytics, AI/ML, Generative AI (GenAI), integration, security, and governance across cloud, hybrid, and on-premises setups.
• Architect components such as data lakes, warehouses, lakehouses, streaming pipelines, ETL/ELT processes, metadata management, lineage tracking, and data quality frameworks.
• Develop GenAI solutions including large language models (LLMs), retrieval augmented generation (RAG), embeddings, vector databases, and enterprise search implementations.
• Define MLOps/ModelOps processes, including model monitoring, AI lifecycle and responsible AI governance.
• Establish comprehensive data and AI governance encompassing privacy, security, access controls, compliance, transparency, and model risk assessment.
• Evaluate and recommend technology platforms considering performance, scalability, security, reliability, and cost efficiency.
• Provide leadership during solution delivery ensuring adherence to architectural plans.
• Perform architecture reviews, troubleshoot technical challenges, and steer engineering teams.
• Create detailed architecture diagrams, solution blueprints, technical specifications, and documentation.
• Communicate technical recommendations to senior business and technical stakeholders effectively.

Candidate Requirements

• Bachelor's or Master's in Computer Science, Data Engineering, AI, Software Engineering or similar disciplines.
• Minimum 15 years of professional experience in technology, with substantial focus on solution, data, and AI architecture.
• Demonstrated expertise in both presales solutioning and delivery of complex enterprise Data & AI projects.
• Deep familiarity with cloud platforms, contemporary data architectures, AI/ML techniques, GenAI, integration methodologies, security, and governance frameworks.
• Hands-on experience with AWS, Azure, GCP, Databricks, Snowflake, Microsoft Fabric, Synapse, BigQuery, or comparable cloud/data platforms.
• Strong understanding of advanced AI concepts such as RAG, LLMs, vector databases, and MLOps/ModelOps practices along with AI governance.
• Prior consulting, technology services, or enterprise transformation experience preferred.
• Exceptional client communication, presentation skills, and ability to engage multiple stakeholders.
• Strong commercial insight coupled with analytical reasoning and problem-solving capabilities.