Senior Manager, Analytics - Applied AI

Merkle is a leading data-driven, technology-enabled, global performance marketing agency that specializes in the delivery of unique, personalized customer experiences across platforms and devices. Our Analytics Innovation team is at the forefront of implementing cutting-edge artificial intelligence solutions, from sophisticated agentic AI systems to enterprise-scale LLM deployments, with particular expertise in conversational analytics and text-to-SQL systems that transform how our clients engage with their data and customers.

The AI Director, Analytics is a critical senior technical leadership role within our growing practice. This position sits at the intersection of technical architecture
, implementation excellence
, and innovation leadership for complex AI systems. You will be responsible for designing and building production-grade AI solutions that leverage the latest technology, agentic architectures, and cloud-native infrastructure, with a strong focus on natural language interfaces and data democratization through conversational insights.

We are looking for a deeply technical leader who combines hands‑on engineering expertise with strategic thinking about AI system design, including semantic layer architecture and SQL generation quality. You'll work closely with the client and our technical team to translate business requirements into scalable, reliable AI systems while establishing best practices that ensure successful deployments across our client base.

Responsibilities:

Architect and build enterprise‑scale AI systems including agentic workflows, RAG architectures, conversational analytics platforms, and text‑to‑SQL solutions that are built to scale

Design and implement semantic layers that enable accurate natural language to SQL translation across complex enterprise data warehouses in Databricks, Snowflake, or AWS platforms

Lead MLOps/Dev Ops practices for AI systems including CI/CD pipelines, infrastructure as code, automated testing frameworks, and production monitoring solutions

Develop robust evaluation frameworks including golden datasets for text‑to‑SQL accuracy, agent quality metrics, and comprehensive system performance benchmarks

Design data architectures for AI systems including knowledge base design, vector databases, retrieval optimization, semantic modeling, and real‑time data pipelines

Build conversational insights systems following proven methodologies: requirements gathering, semantic layer implementation, evaluation framework creation, and successful client handoff

Own the technical roadmap for AI capabilities including evaluation of emerging technologies, proof of concepts for new approaches, and strategic partnerships with cloud providers

Lead technical client engagements as the engineering SME for complex implementations, providing architectural guidance for both traditional AI and conversational analytics deployments

Establish engineering standards for prompt engineering, SQL generation quality, model selection, and guardrails implementation that ensure consistent, high‑quality AI experiences

Mentor and develop a team of AI engineers while fostering a culture of technical excellence and continuous learning

Experience:

7+ years of software engineering experience with at least 2 years focused on AI/ML systems in production environments, preferably including text‑to‑SQL or conversational analytics implementations

Deep hands‑on experience building LLM‑based applications including prompt engineering, RAG implementations, multi‑agent systems, and natural language interfaces for data

Proven expertise in cloud platforms (AWS/Azure/GCP) with specific experience in Databricks (Unity Catalog, Genie) or Snowflake (Cortex, Native Apps) highly preferred

Strong background in MLOps practices and data engineering including semantic layer design, SQL optimization, and evaluation pipeline implementation

Experience with modern AI stack including vector databases, orchestration frameworks (Lang Chain, Llama Index), and specialized evaluation tools for conversational AI quality

Track record of building high‑throughput, low‑latency systems that handle enterprise scale, including text‑to‑SQL systems…