Manager, Artificial Intelligence
Listed on 2026-06-03
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer
One Magnify is an AI native, platform-enabled B2B digital agency operating at the intersection of data, technology, and creativity. We help complex organizations drive measurable business outcomes by building smarter customer experiences and delivering highly integrated solutions across digital, media, and technology. By combining deep industry expertise with advanced analytics and artificial intelligence, we enable our clients to make better decisions, move faster, and compete more effectively in dynamic markets.
RoleSummary
The Manager of Artificial Intelligence sits at the center of One Magnify's AI practice — leading technical delivery, guiding client strategy, and translating complex data into decisions that move the needle. You'll work directly with clients to help them unlock the value in their data, while managing and mentoring a team of data scientists, AI engineers, and software engineers. This role shapes both how we deliver AI solutions and how our clients experience them.
ImpactYou'll Have
You'll be the connective tissue between what's technically possible and what clients actually need. That means pushing beyond theoretical AI capabilities to help organizations — many of them large, data‑rich B2B enterprises — build practical systems that inform strategy, automate workflows, and create measurable business outcomes. You’ll lead generative AI projects that integrate AI and data science work with broader digital strategy, analytics, and platform teams for an integrated solution that scales with the client’s growth.
WhatYou’ll DoClient Partnership & AI Strategy
- Collaborate with strategic clients to identify where AI and data can drive meaningful action — not just generate insights.
- Translate client business challenges into technical approaches that are both rigorous and achievable.
- Serve as a trusted advisor who can simplify complex AI concepts for non‑technical stakeholders.
- Provide hands‑on technical direction for generative AI projects, including architecture decisions and solution design.
- Apply expertise in LLMs, data science, and object‑oriented programming to guide delivery from prototype to production.
- Leverage tools like Databricks, Python, R, and SQL across the project lifecycle — including building and managing data pipelines, feature engineering, and model deployment within the Databricks ecosystem.
- Lead and develop a cross‑functional team of data scientists, AI engineers, and software engineers.
- Set clear expectations, support career growth, and build a team culture oriented around craft and client outcomes.
- Model the technical and communication standards you expect from the team.
- Drive alignment across AI, analytics, strategy, and engineering disciplines within One Magnify.
- Partner with delivery and operations teams to ensure AI work streams integrate cleanly into broader project execution.
- Represent the AI practice in client‑facing settings alongside strategy and creative counterparts.
- Stay current on the evolving AI landscape — new models, platforms, tools, and use cases — and bring relevant developments into client conversations and internal delivery.
- Contribute to One Magnify's point of view on AI‑enabled solutions and how the practice continues to grow.
- Bachelor's degree in computer science, data science, engineering, or a related field;
Master’s degree preferred. - 6+ years of experience in AI, data science, or ML engineering — with at least 2 years managing technical teams (data scientists, AI/ML engineers, or software engineers).
- Proven ability to take AI projects from conception through production, including architecture decisions, model deployment, and stakeholder communication.
- Hands‑on experience with LLMs, generative AI, and object‑oriented programming.
- Proficiency in Python, R, and SQL.
- Hands‑on experience with Databricks, including MLflow, Delta Lake, Unity Catalog, or Databricks‑native model serving.
- Working knowledge of MLOps practices — model versioning, monitoring, retraining pipelines, and scaling models in production environments.
- Exposure to…
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