VP, AI Solutions Architect

Job Description:

The Role We’re seeking a hands‑on AI Solutions Architect at the Vice President level to join Merkle’s Office of the CTO. You will personally design, code, prototype, and deploy AI solutions that solve real business problems, while shaping our architecture, platform, and engineering standards as a founding member of a new AI Solutions team.

Reporting to the SVP, AI Solutions, you will combine the implementation depth of a senior individual contributor with the judgment and communication skills to advise enterprise clients. The VP title reflects the scope of your technical ownership and influence. Writing code, debugging systems, and shipping working software are core, ongoing responsibilities. You should enjoy moving between business discovery, architecture decisions, and implementation.

You’ll work directly with clients and a globally distributed team of AI specialists to turn ambiguous requirements into working prototypes, develop promising solutions for production, and improve them through evaluation and real‑world feedback. We welcome candidates from Staff or Principal Engineer, hands‑on Technical Lead, founding engineer, and similar backgrounds. You should bring recent experience building AI systems yourself and a desire to remain deeply involved in delivery.

• Build and ship AI solutions
• Personally implement AI applications and agentic workflows, including application code, orchestration, APIs, data integrations, and deployment pipelines.
• Take solutions from technical discovery and rapid prototyping through production deployment, monitoring, and iteration, working with client and internal engineering teams.
• Build integrations between AI services and enterprise systems using APIs, event‑driven patterns, and Model Context Protocol (MCP) where appropriate.
• Apply LLMs, retrieval‑augmented generation (RAG), agent orchestration, and other AI techniques to concrete business needs, including customer service, marketing personalization, and analytics automation.
• Write tests, build evaluation datasets, implement observability, and debug failures. Use evidence to improve output quality, reliability, latency, and cost.

• Design and implement architectures that meet enterprise requirements for scalability, security, privacy, reliability, and performance.
• Make and explain practical tradeoffs across models, frameworks, cloud services, and build‑versus‑buy decisions.
• Turn successful implementations into reusable components, reference architectures, integration patterns, and delivery templates.
• Help evolve Merkle’s AI platform through direct engineering contributions and standards for orchestration, evaluation, deployment, monitoring, and responsible AI.
• Integrate relevant partner technologies across platforms such as Salesforce, Adobe, Microsoft, AWS, Google Cloud, Databricks, and Snowflake.

• Run technical discovery with clients to identify valuable use cases, understand their systems and constraints, and define an achievable implementation approach.
• Build and demonstrate working prototypes with clients and internal teams; lead hands‑on technical workshops and hackathons.
• Explain architecture decisions, implementation risks, and results to both executive and technical audiences.
• Mentor architects and engineers through pairing, code reviews, architecture reviews, and shared problem‑solving.
• Partner with Technology Strategy, Data Science, Security, Cloud, and Practice teams to meet enterprise requirements and support deployment.
• Support Sales with technical solution design, working demos, and delivery estimates grounded in implementation experience.

• 12+ years of progressive…