Dentsu Aegis Network
Senior Manager, Analytics - Applied AI
Dentsu Aegis Network, Chicago, Illinois, United States, 60290
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. 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 client’s 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 $113,000 - $182,850. Placement within the salary range is based on a variety of factors, including relevant experience, knowledge, skills, and other factors permitted by law.
Benefits
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
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 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-RB1 #LI-Hybrid
At dentsu, we believe great work happens when we’re 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.
Location Chicago - N. State
Brand Merkle
Time Type Full time
Contract Type Permanent \ Dentsu is committed to providing equal employment opportunities to all applicants and employees. We do this without regard to race, color , national origin, sex , sexual orientation, gender identity, age, pregnancy, childbirth or related medical conditions, ancestry, physical or mental disability, marital status, political affiliation, religious practices and observances, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law.
Dentsu is committed to providing reasonable accommodation to, among others, individuals with disabilities and disabled veterans. If you need an accommodation because of a disability to search and apply for a career opportunity with us, please send an e‑mail ApplicantAccommodations@dentsu.com by clicking on the link to let us know the nature of your accommodation request and your contact information. We are here to support you.
#J-18808-Ljbffr
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 client’s 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 $113,000 - $182,850. Placement within the salary range is based on a variety of factors, including relevant experience, knowledge, skills, and other factors permitted by law.
Benefits
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
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 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-RB1 #LI-Hybrid
At dentsu, we believe great work happens when we’re 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.
Location Chicago - N. State
Brand Merkle
Time Type Full time
Contract Type Permanent \ Dentsu is committed to providing equal employment opportunities to all applicants and employees. We do this without regard to race, color , national origin, sex , sexual orientation, gender identity, age, pregnancy, childbirth or related medical conditions, ancestry, physical or mental disability, marital status, political affiliation, religious practices and observances, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law.
Dentsu is committed to providing reasonable accommodation to, among others, individuals with disabilities and disabled veterans. If you need an accommodation because of a disability to search and apply for a career opportunity with us, please send an e‑mail ApplicantAccommodations@dentsu.com by clicking on the link to let us know the nature of your accommodation request and your contact information. We are here to support you.
#J-18808-Ljbffr