Sr. Solutions Architect, AI Solutions

Trace3

8h•$190,000 - $200,000

About The Position

The Sr. Solutions Architect, AI Solutions is a hands-on technical presales role in Trace3’s Data & Analytics AI Solutions practice, reporting to the Practice Director, AI Solutions. The role designs and defends AI solutions for clients before a statement of work exists. It is presales-only and does not carry delivery execution, billable utilization, or project P&L responsibility. The work focuses on AI from a data and analytics perspective: connecting client data estates to business decisions and helping move agentic workflows from pilot to production. The architect leads discovery, designs solutions, builds working prototypes when appropriate, and creates technical content that informs proposal and statement-of-work scope. Solutions draw on data platforms, AI platforms, and security guardrails, and must be credible to both technical and executive audiences. The role is measured by architecture quality and commercial outcomes, including technical wins, delivery-ready scope, conversion of advisory work into full-stack programs, and the quality of handoffs to Services. The position requires approximately 30–50% travel, depending on region and pursuit load.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent experience.
7+ years of experience in technology, including 4+ years designing or building AI, machine learning, or data solutions.
2+ years in technical presales, solutions architecture, or consulting with responsibility for technical decisions on client pursuits.
Hands-on proficiency in Python, modern AI and ML frameworks, LLM application development, retrieval architectures, and agent orchestration frameworks.
Working experience with at least one major cloud AI stack: Azure AI Foundry, AWS Bedrock, or Google Vertex AI.
Working experience with at least one modern data platform: Databricks, Snowflake, or Microsoft Fabric.
Practical experience with model evaluation, cost and performance tradeoffs, and running AI systems in production.
Working knowledge of AI security and governance, including NIST AI RMF, data protection, and enterprise controls for production approval.
Ability to lead technical conversations with executives and engineers, including disagreeing with a client while maintaining the relationship.
Excellent written and verbal communication skills, with the ability to explain AI architecture to technical and non-technical audiences.
Highly organized and able to manage several concurrent pursuits in a fast-paced environment.
Willingness to travel approximately 30–50%, depending on region and pursuit load.

Nice To Haves

Experience in a consulting, advisory, or solutions firm where technical design drives commercial scope.
Certifications in cloud AI, data-platform, or ML-engineering disciplines.
Industry depth in one or more of healthcare, financial services, public sector, or manufacturing.
A visible body of applied AI work, such as published writing, open-source contributions, or conference talks.

Responsibilities

Own the technical solution for assigned AI pursuits, from discovery and qualification through solution design and defense of the approach.
Lead discovery sessions, whiteboards, and technical workshops with client engineers, architects, and business stakeholders.
Produce reference architectures, solution diagrams, assumptions, risks, and level-of-effort inputs for proposals, RFP responses, and statements of work.
Present and defend proposed architectures to technical and executive audiences, including CIO, CDO, and CISO stakeholders.
Partner with account executives to qualify opportunities, including advising clients when AI is not an appropriate solution.
Hand off documented designs to Services and support technical escalation during early delivery.
Assess client data estates for AI readiness, including quality, lineage, access patterns, latency, semantics, and governance.
Design data layers for AI, including retrieval and context pipelines, vector and semantic search, feature engineering, evaluation and ground-truth datasets, and supporting metadata.
Align AI architectures with client investments in Databricks, Snowflake, Microsoft Fabric, and cloud-native stacks.
Identify data-estate limitations and define the data work needed to support the client’s AI goals.
Collaborate with Data Strategy and Data Platforms architects so AI discovery informs data modernization scope.
Design end-to-end agentic workflows, including orchestration, tool and system integration, memory and state, human-in-the-loop controls, and evaluation.
Apply and improve reference patterns for agent design, model selection, context engineering, and protocol-level integration, including MCP.
Build proofs of concept and pilots integrated with client data and systems that demonstrate a credible path to production.
Test agentic solutions against production-readiness standards for security, monitoring, cost, and failure handling.
Advise clients on operating-model changes required for agentic AI, including ownership, change management, and cost control.
Engage AI Platforms architects on inference architecture, sizing, and on-premises versus cloud placement.
Work with Security and Risk on AI-specific exposure, including data leakage, prompt injection, agent identity and access, and alignment to NIST AI RMF.
Coordinate with Cloud, Applications, and Customer Experiences teams on cross-practice solutions and confirm scope ownership before proposals are issued.
Escalate architecture questions and scope conflicts to the Practice Director, AI Solutions early in pursuits.
Contribute reusable architecture patterns, demo assets, and discovery guides to the practice after pursuits.
Meet standards for architecture artifacts, including diagram quality, stated assumptions, and traceable sources for client-facing figures.
Enable sales and account teams to qualify and position AI solutions accurately.
Mentor less experienced architects and engineers through pursuit work and peer review.
Maintain hands-on knowledge of models, agent frameworks, AI platforms, and data platforms, including realistic assessments of vendor claims.
Build technical relationships with partner solution architects across hyperscalers, model providers, and data-platform vendors.
Support Trace3 thought leadership through client briefings, partner events, executive summits, and written perspectives.

Benefits

Comprehensive medical, dental, and vision plans for employees and dependents.
401(k) retirement plan with employer match.
529 College Savings Plan.
Health Savings Account.
Life insurance and long-term disability.
Competitive compensation; the stated estimated base pay range is $190,000–$200,000 USD. Certain positions may also be eligible for variable incentive compensation, such as bonuses or commissions.
Training and development programs.
Major offices stocked with snacks and beverages.
Collaborative culture.
Work-life balance and generous paid time off.