Data Solutions Architect | AI

What You’ll Do 

As a Data Solutions Architect, you will own the end-to-end lifecycle of technical proof work across the Data and Experiences BU. Your work will directly support Practice Directors, field SAs, and the Delivery Organization across the Intelligent Enterprise, Consumer Experiences, and Data and Analytics practices. 

Pre-Sales and Client-Facing Technical Work 

You will design, build, and present client-facing proofs of concept (POCs) and proofs of value (POVs) that demonstrate Trace3’s technical differentiation. These are not vendor-provided sandbox logins or generic demos. They are live, configured, Trace3-branded environments built on the client’s data, the client’s workflows, and the client’s integration points. You will own the scoping, architecture, build, and presentation of these assets. 

You will lead AI capability demonstrations across the BU’s core technology plays, including agentic AI architectures, retrieval-augmented generation (RAG) systems, multimodal AI pipelines, MLOps platforms, and AI-native data and analytics stacks. You will be the person in the room who can answer the question “can you show me that working?” with a yes – and then show it. 

You will partner with Practice Directors and field SAs during active sales pursuits to define POC success criteria, scope minimum viable architectures, and ensure that every proof of concept is designed to answer a specific technical question – not to impress, but to advance the deal. 

AI Innovation and Capability Development 

You will be a visible, opinionated AI forward thinker within the BU. You will track emerging AI capabilities across the vendor ecosystem, evaluate their relevance to Trace3’s client base, and translate that evaluation into actionable technical assets: working prototypes, architecture reference guides, and intake recommendations for the Accelerators build pipeline. 

You will build reusable AI accelerator assets – prompt libraries, agent frameworks, RAG pipeline templates, evaluation harnesses, and fine-tuning playbooks – that reduce the time required to stand up AI capabilities from scratch on client engagements. You will not build these assets in isolation; you will build them in collaboration with the TAMs, Practice Directors, and Delivery teams who will use them. 

You will drive the Accelerators group’s contribution to the Pre-Sales Intelligence Evaluation Suite (CXE, DPE, SPE, IFE) – a set of AI-powered research evaluations that give Trace3 sellers an informed, opinionated starting position before the first client meeting. You will build, test, and refine the agent prompts, research workflows, and output templates that make these evaluations repeatable and high-quality. 

Delivery Enablement 

You will build technical tooling that makes the Delivery Organization faster and more consistent. This includes configuration automation scripts that reduce platform stand-up time, automated UAT frameworks that catch issues early in the delivery lifecycle, and documentation automation pipelines that generate as-built artifacts as a byproduct of the delivery process rather than a manual effort at the end. 

You will serve as the technical escalation path for Practice Directors and SAs who encounter questions they cannot answer – new vendor capabilities, integration edge cases, regulatory requirements that affect architecture decisions. You will research, document, and communicate findings in a form that the requesting team can use immediately. 

Thought Leadership and Team Contribution 

You will contribute to the Accelerators group’s internal knowledge base, publishing technical briefs, architecture patterns, and lessons learned from every significant POC or accelerator build. You will mentor junior team members and contribute to the continuous development of the team’s collective capability. You will represent the Accelerators group in vendor technical briefings, partner advisory boards, and internal BU forums. 

 

Required Qualifications  

• Bachelor’s degree in computer science, engineering, mathematics, or a related field, or equivalent professional experience 

• 5 or more years of experience in solutions architecture, data architecture, or AI architecture with a track record of client-facing technical delivery 

• 3 or more years of hands-on experience building and deploying AI or machine learning solutions in production or near-production environments 

• Demonstrated experience designing and building POCs and POVs for enterprise clients, including scoping, architecture, build, and executive presentation 

• Proficiency in Python and at least one additional language (SQL, Scala, JavaScript, or R) 

• Hands-on experience with cloud data platforms (Snowflake, Databricks, or equivalent) and at least one major cloud provider (AWS, Azure, or GCP) 

• Working knowledge of modern AI architectures including large language models (LLMs), RAG systems, vector stores, knowledge graphs, and agentic frameworks 

• Outstanding communication and presentation skills with both technical and executive audiences, including the ability to present complex AI concepts to non-technical stakeholders 

• Strong organizational and time management skills with the ability to manage multiple concurrent POC and accelerator builds in a fast-moving environment 

 

Preferred Qualifications  

• Master’s degree in computer science, AI, machine learning, or a related field 

• Experience with MLOps platforms and practices (model versioning, monitoring, drift detection, retraining pipelines) 

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