Manhattan designs, builds and delivers market-leading supply chain technology solutions for leading companies around the world. We help drive the commerce revolution with unmatched insight and unrivaled technology, connecting front-end revenue and relationships with back-end execution and efficiency—optimized on a common technology platform. This platform-based approach is enabling leading companies across the globe to Push Possible® by getting closer to customers and achieving real-world results.

The Principal AI Engineer is a senior technical leader responsible for designing, developing, and guiding the implementation of advanced artificial intelligence systems that support Manhattan’s business goals. This role combines deep expertise in machine learning, data science, and software engineering with strategic leadership to drive AI initiatives across the organization.

The Principal AI Engineer will define AI/ML architecture and technical roadmaps, lead development of production-grade ML and generative AI solutions, and champion the adoption of scalable and responsible AI capabilities across products and business processes.

Key responsibilities include:

AI Architecture & Strategy:

Design scalable AI/ML architectures and define long‑term AI technology strategy aligned with business objectives.
Model Development:

Lead development of machine learning, deep learning, computer vision, NLP, and generative AI models for production environments.
Platform & MLOps:

Oversee model deployment, monitoring, optimization, and lifecycle management in cloud and on‑prem environments using modern MLOps practices.
Technical Leadership:

Mentor AI engineers, data scientists, and ML engineers; establish engineering standards, best practices, and reusable patterns for AI solutions.
Research & Innovation:

Evaluate emerging AI technologies and frameworks; integrate cutting‑edge methods into Manhattan’s products and platforms.
Cross‑Functional Collaboration:

Partner with product managers, data engineers, and business stakeholders to translate requirements into practical AI solutions that deliver measurable outcomes.
Responsible AI & Governance:

Ensure ethical AI practices, model explainability, fairness, privacy, and regulatory compliance are built into AI solutions.
Performance Optimization:

Continuously improve model accuracy, efficiency, scalability, and reliability for enterprise‑scale systems.
Ownership & Impact:

Independently drive complex projects, determine approaches to solutions, and use sound judgment to prioritize work with limited direction.

MINIMUM REQUIREMENTS

7+ years of industry experience in software engineering, machine learning, or AI roles with a focus on developing, deploying, and scaling ML/AI solutions.
3+ years of proven experience in designing large‑scale AI systems and defining technical roadmaps.
Strong experience developing AI‑driven workflows using knowledge platforms and AI agent frameworks (e.g., Microsoft Copilot, Glean, Google Agentspace).
Deep knowledge of:
Machine Learning (classification, regression, clustering, recommendation systems)
Deep Learning (CNNs, RNNs, Transformers, GANs)
Natural Language Processing (BERT, GPT, LLM fine‑tuning)
Computer Vision (YOLO, ResNet, object tracking, OCR)
Expertise in:
Python and relevant ML libraries (TensorFlow, PyTorch, Scikit‑learn, Hugging Face)
Data engineering and pipeline development (Airflow, Spark, ETL systems)
MLOps, model lifecycle management, and production‑grade deployment
Cloud platforms (AWS, GCP, Azure), containerization (Docker), and orchestration (Kubernetes)
Proven track record of scaling ML models from experimentation to production across teams or business units.
Experience designing and implementing integrations using Model Context Protocol to connect AI models with external tools, APIs, and data sources.
Demonstrated ability to set research and development direction based on business needs and to apply deep product or platform knowledge to complex assignments.
3+ years of experience interfacing and partnering with vendors and contributing to strategy/roadmap and planning activities.
2+ years of experience leading or mentoring more junior staff members.
Strong communication skills with the ability to work effectively across technical and business audiences.
Highly self‑motivated and results‑driven, able to work independently and in a collaborative, geographically distributed team environment.
Experience working with common enterprise collaboration and delivery tools (e.g., SharePoint, ServiceNow or other IT ticketing tools, Jira, Bitbucket, Confluence) and in agile and/or waterfall software delivery methodologies.
Bachelor’s degree or foreign equivalent in computer science, engineering or related field, or equivalent work experience.

Job description