Sr. Manager, Analytics - AI

The purpose of this role is to lead and manage customer analysis deep dives, execute the strategies outlined by senior leadership, and manage the day-to-day communication with clients.

Job Description:

JOB DESCRIPTION:

Analytics Innovation Team

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 Engineering Lead 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/DevOps 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:

• 5+ 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 (LangChain, LlamaIndex), 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 with high accuracy rates

• Production experience with multiple LLM providers and understanding of their trade-offs for various use cases including SQL generation

• Demonstrated ability to translate complex business requirements into technical architectures and lead cross-functional teams through implementation

Qualifications:

Education:

• Bachelor's degree in Computer Science, Engineering, or related field; Master's degree preferred

Technical Skills:

• Expert-level Python programming and software engineering best practices

• Strong SQL proficiency and experience with query optimization across multiple platforms

• Experience with semantic layer tools (Unity Catalog, AWS Glue Data Catalog) and metadata management

• Strong experience with containerization (Docker, Kubernetes) and microservices

• Proficiency in infrastructure as code (Terraform, CloudFormation)

• Familiarity with front-end technologies for full-stack AI applications

AI/ML Expertise:

• Deep understanding of transformer architectures and LLM capabilities/limitations

• Experience with text-to-SQL evaluation metrics (execution accuracy, semantic correctness)

• Knowledge of fine-tuning approaches and retrieval-augmented generation (RAG)

• Understanding of AI safety, bias mitigation, and responsible AI practices

Leadership Skills:

• Proven ability to lead technical teams and drive architectural decisions

• Excellence in technical documentation and knowledge sharing

• Strong presentation skills with ability to communicate complex concepts to diverse audiences

• Experience working in agile environments and leading technical sprints

Additional Assets:

• Experience building golden datasets and evaluation frameworks for conversational AI

• Published work or presentations on AI/ML topics

• Specific experience with conversational insights in enterprise settings

• Background in data analytics or business intelligence

What Success Looks Like:

In this role, you'll be measured on your ability to deliver production-ready AI systems that meet our high standards for quality, reliability, and scalability. For conversational analytics implementations, this includes achieving high accuracy on text-to-SQL evaluations and successfully democratizing data access for business users. You'll establish our team as technical thought leaders in the AI space while ensuring every client deployment—from agentic systems to conversational interfaces—is a success story.

Your architectural decisions will enable rapid innovation while maintaining the stability and performance our enterprise clients demand. Success includes building reusable frameworks, establishing evaluation best practices, and delivering AI solutions that provide measurable business value across diverse use cases.

Location:

USA – Remote – Texas – Central Time

Brand:

Merkle

Time Type:

Full time

Contract Type:

Permanent