AI Engineering Lead

Job Description:

AI Engineering Lead

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. Youll 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:

• Bachelors degree in Computer Science Engineering or related field; Masters 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 youll 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. Youll establish our team as technical thought leaders in the AI space while ensuring every client deploymentfrom agentic systems to conversational interfacesis 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.

Additional Information

The anticipated base salary range for this position is $113000 - $182850. Placement within the salary range is based on a variety of factors including relevant experience knowledge skills and other factors permitted by law.

Benefits available with this position include:

Medical vision and dental insurance

Life insurance

Short-term and long-term disability insurance

401k

Flexible paid time off

At least 15 paid holidays per year

Paid sick and safe leave and

Paid parental leave.

Dentsu also complies with applicable state and local laws regarding employee leave benefits including but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act in accordance with its plans and policies. For further details regarding Dentsu benefits please visit .

To begin the application process please click on the Apply button at the top of this job posting. Applications will be reviewed on an ongoing basis and qualified candidates will be contacted for next steps. #LI-RB1 #LI-Hybrid

At dentsu we believe great work happens when were connected. Our way of working combines flexibility with in-person collaboration to spark ideas and strengthen our teams. Employees who live within a commutable distance of one of our hub offices currently located in Chicago metro Detroit Los Angeles and New York City are required and expected to work from the office three days per week (two days per week for employees based in Los Angeles). Dentsu may designate other Hub offices at any time. Those who live outside a commutable range may be designated as remote depending on the role and business needs. Regardless of your work location we expect our employees to be flexible to meet the needs of our Company and clients which may include attendance in an office.

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