Merkle Schweiz
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/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:
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 (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.
The annual base salary range for this position is $136,000 - $209,650. 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,
Short‑term and long‑term disability insurance,
Flexible paid time off,
At least 15 paid holidays per year,
Paid sick and safe leave, and
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 www.dentsubenefitsplus.com.
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-RL1 #LI-hybrid
Beware of Job Scams We are aware of several scams targeting job seekers and candidates. Please be vigilant. All communication throughout the recruitment process will be from an official member of the dentsu recruitment team, using corporate email addresses (e.g., @dentsu.com or @merkle.com). We will never ask you to send money or vouchers to secure employment. If you suspect you have been a victim of a scam, please report the incident to your bank, local police, or fraud protection authority immediately. Additionally, you can report the scam to us at jobfraud@dentsu.com so we can take appropriate action to request the website is taken down. Please note that Merkle and dentsu are not responsible for any losses incurred as a result of these scams. We advise all individuals to exercise caution and verify the authenticity of any job offers or communications received.
#J-18808-Ljbffr
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/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:
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 (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.
The annual base salary range for this position is $136,000 - $209,650. 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,
Short‑term and long‑term disability insurance,
Flexible paid time off,
At least 15 paid holidays per year,
Paid sick and safe leave, and
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 www.dentsubenefitsplus.com.
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-RL1 #LI-hybrid
Beware of Job Scams We are aware of several scams targeting job seekers and candidates. Please be vigilant. All communication throughout the recruitment process will be from an official member of the dentsu recruitment team, using corporate email addresses (e.g., @dentsu.com or @merkle.com). We will never ask you to send money or vouchers to secure employment. If you suspect you have been a victim of a scam, please report the incident to your bank, local police, or fraud protection authority immediately. Additionally, you can report the scam to us at jobfraud@dentsu.com so we can take appropriate action to request the website is taken down. Please note that Merkle and dentsu are not responsible for any losses incurred as a result of these scams. We advise all individuals to exercise caution and verify the authenticity of any job offers or communications received.
#J-18808-Ljbffr