Director, Applied AI

American Tower

Director of Applied AI managing AI and machine learning systems at American Tower. Collaborating with teams to deliver scalable, impactful solutions for enterprise insights.

Posted 5/6/2026full-timeWoburn • Massachusetts • 🇺🇸 United StatesLead💰 $182,000 - $228,000 per yearWebsite

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Lead the Applied AI function, including the development of machine learning, optimization, generative AI, and Agentic AI systems that perform multi-step reasoning, autonomous workflows, and decision support.
Oversee model and agent lifecycle development, including methodology design, feature engineering, validation, safety constraints, agent orchestration, and performance monitoring.
Partner with Data Engineering to enable MLOps, AgentOps, deployment, observability, retraining, and production reliability.
Collaborate with the Data Product and Adoption team to translate models and agents into user-facing products that drive adoption and measurable value realization.
Establish and enforce enterprise standards for documentation, scientific rigor, reproducibility, Responsible AI, and safe Agentic AI practices, including human-in-the-loop oversight.
As a Director, you are responsible for the recruitment, performance management, and career development of Data Scientists, ML Engineers, and AI Engineers. You will cultivate a collaborative team dynamic that enables us to meet our business objectives.
Other duties as assigned.

Requirements

What you’ll need

Bachelor’s degree in Data Science, Computer Science, Engineering, Mathematics, Operations Research, or a related field required.
Advanced degree (Master’s or PhD) preferred.
A minimum of 10 years of data science, machine learning, advanced analytics, or applied AI experience required, with 5 or more years leading technical AI teams strongly preferred.
Success developing and deploying production-grade ML, generative AI, optimization models, or Agentic AI systems in complex or asset-intensive environments.
Experience with experimental design, causal inference, predictive modeling, reinforcement learning, and autonomous decisioning systems.
Strong expertise in Python, ML frameworks, LLMs, vector search, embeddings, and agent-orchestration frameworks.
Experience with MLOps, AgentOps, model and agent registries, feature stores, monitoring, and AI safety tooling.
Strong business acumen with the ability to quantify impact, communicate model and agent behavior, and influence senior stakeholders.
Familiarity with Responsible AI practices for autonomy, including safety constraints, guardrails, alignment testing, and human-in-the-loop design.
Experience in global, matrixed environments preferred.
Approximately 20%–30% travel may be required.
Strong organization, planning, and project management skills; ability to prioritize tasks for yourself and a team.
Ability to work with different functional groups and levels of employees to effectively and professionally achieve results.
Strong leadership skills with ability to drive and motivate a team to achieve results.

Benefits

Comp & perks

healthcare coverage
401(k) savings plan
paid time off
company holidays
sick leave
parental leave
access to an Employee Assistance Program focused on mental and financial wellness

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningoptimizationgenerative AIAgentic AIfeature engineeringexperimental designcausal inferencepredictive modelingreinforcement learningPython

Soft Skills

leadershipcollaborationorganizationplanningproject managementcommunicationinfluenceteam dynamicperformance managementcareer development

Certifications

Bachelor’s degreeMaster’s degreePhD