Senior Manager, AI & Analytics Engineering

Description

The company wants a hands-on technical leader to turn high-value business and analytical problems into production agents and analytical solutions. The solutions will serve more than 1,000 users across Commercial, Strategy, Customer, Marketing, Category Advisory, and Executive Leadership.

You will work across those groups and with analytics, data science, engineering, and product teams to find opportunities, shape practical approaches, build working capabilities, and drive adoption across North America.

The work blends applied AI, analytics engineering, and system design. You will build agents and analytical applications and also strengthen the shared services, governed data access, evaluation, security, observability, and deployment patterns beneath them, balancing speed and business value against analytical integrity, reliability, scale, and cost.

The company has operated for 130+ years.

Responsibilities

• Build AI and analytics solutions that create value.
• Work with business leaders to choose high-value use cases and turn unclear questions and analytical needs into clear designs, working prototypes, and production tools used in real decisions and workflows.
• Personally build AI agents, analytical applications, and supporting services, owning work from framing and architecture through testing, deployment, adoption, and improvement.
• Pick the right method for each problem, using deterministic analytics, machine learning, retrieval, large language models, and agentic workflows where each adds value.
• Connect AI with trusted analytics.
• Work with business experts, analysts, data scientists, and data engineers to keep business definitions, metric grain, filters, source, freshness, lineage, and authorization intact in AI-enabled analysis.
• Integrate solutions with Microsoft Fabric, OneLake, Lakehouses, Warehouses, Power BI semantic models, Azure Machine Learning, Azure AI Search, and other approved enterprise capabilities.
• Build secure, parameterized APIs and tools, including MCP-compatible services, that connect agents to governed data, analytical methods, applications, and business workflows.
• Strengthen the reusable engineering foundation.
• Build reusable patterns for model access, orchestration, retrieval, context and memory, tool execution, structured responses, human approvals, workflow recovery, and automation.
• Write production Python and API services with automated testing, CI/CD, monitoring, and clear operational ownership, designing for performance, concurrent demand, reliability, scale, and cost efficiency.
• Test frameworks and managed services with working prototypes and measured trade-offs, favouring simple architecture that avoids unnecessary complexity and lock-in.
• Ensure quality, governance, and continuous improvement.
• Build evaluation and regression capabilities using benchmark datasets, known-answer tests, adversarial scenarios, release gates, end-to-end tracing, and production telemetry.
• Measure analytical accuracy, task completion, adoption, latency, throughput, reliability, token and compute use, and cost per successful workflow, then use the results to improve solutions through controlled, versioned releases.
• Put in place secure identity, authorization, guardrails, audit logging, human review, and responsible AI controls with the Architecture, Security, Privacy, and Data Governance teams.
• Provide hands-on technical leadership.
• Work as a player-coach: write production code, lead system-design decisions, review code and architecture, mentor engineers, and set practical standards that improve delivery across the team.
• Explain technical choices, risks, and trade-offs clearly to business and technical stakeholders, and help teams turn new AI capabilities into useful, supportable products.

Requirements

• A bachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems, Engineering, Analytics, or a related field, or equivalent practical experience.
• At least 8 years of experience in AI, software, data, platform, analytics, or machine-learning engineering, shipping solutions that people use.
• Recent hands-on experience personally building and shipping AI, analytical, machine-learning, or data products with Python, SQL, APIs, or similar tools, plus practical exposure to large language models or agentic workflows.
• Strong analytical reasoning and experience with SQL-based data systems, semantic models, Lakehouse architecture, governed data products, or comparable enterprise analytical environments.
• Solid cloud and system-design fundamentals, covering testing, asynchronous workloads, security, observability, reliability, deployment, performance, scalability, and cost management.
• Ability to take an unclear problem from business need through architecture and implementation to adoption, influencing engineering, data science, analytics, security, and business teams.
• Preferred: experience with Microsoft Fabric, OneLake, Power BI semantic models, Azure Machine Learning, Microsoft Foundry/Azure OpenAI, Azure AI Search, and related Azure services.
• Preferred: hands-on work with AI development tools and platforms such as OpenAI Codex, Anthropic Claude, Azure OpenAI, or comparable enterprise-approved options.
• Preferred: familiarity with modern agent frameworks and interoperability patterns such as LangGraph, LangChain, Microsoft Agent Framework, Semantic Kernel, PydanticAI, MCP, or A2A.
• Preferred: MLOps, LLMOps, or AgentOps practice covering evaluation, experimentation, deployment, observability, governance, and production operations.
• Preferred: experience building and scaling AI or analytical products in a complex enterprise with several business domains, sensitive data, and diverse users.
• The company will not offer sponsorship for employment status, including H-1B and other employment-based nonimmigrant visas, for this role. Applicants must already be authorized to work in the United States full-time and must not need the company's sponsorship to keep working there legally.
• Relevant skills include analytical thinking, analytics, big data, business analytics, computer programming, data analysis, data mining, data science, machine learning (ML), statistics, and Structured Query Language (SQL).

Conditions

Base pay range in the United States: $143,400 - $169,300 USD. Pay may vary by geography, job-related knowledge, skills, and experience.

Location: Atlanta, United States of America.

Travel: 00% - 25%.

Relocation is not provided.

Applications close on November 6, 2026.

The company is an equal opportunity employer and does not discriminate on the basis of protected characteristics.

Benefits

• A full range of medical, financial, and/or other benefits is offered, depending on the position.
• Annual incentive reference value: 15%. This is a market-based value for the role, set at the middle of the range, reflecting performance at target.