Job Description
Role: Senior AI Engineer
Location: Remote - local preferred but not required
Start Date: 9/28/2026
Salary: $125,000 - $165,000, plus 8% AIP eligibility
POSITION SUMMARY:
The Senior AI/ML Engineer will play a crucial role in the AI Center of Excellence (CoE), supporting cross-functional teams across the organization. This position will focus on designing, developing, and developing machine learning (ML), artificial intelligence (AI), Generative AI (GenAI) and Agentic AI solutions. As a member of the AI Center of Excellence, this role will focus on addressing strategic AI needs across a wide range of business domains, contributing to scalable, high-impact solutions that accelerate innovation and improve outcomes.
ACCOUNTABILITIES:
Engineering:
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Design, develop, and deploy production-grade traditional ML models (e.g., regression, classification, clustering, recommender systems) for a variety of business use cases.
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Design, build and operationalize Gen AI (such as Retrieval Augmented Generation) and emerging Agentic AI solutions to address domain specific needs, improve user experiences and automate business workflows.
- Design, maintain, and optimize end-to-end AI/ML pipelines including data ingestion, training, evaluation, deployment, and monitoring on cloud infrastructure (e.g., AWS or equivalent).
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Integrate cloud-native and third-party AI SaaS solutions to accelerate delivery and reduce time to value.
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Ensure AI/ML solutions are scalable, dependable, secure, and cost-effective within cloud environments.
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Create reusable components, frameworks, and best practices to accelerate AI development.
Design and Innovation:
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Evaluating emerging AI technologies including GenAI and agentic AI (e.g., Model Context Protocol (MCP), Google’s Agent-to-Agent (A2A) protocol), as well as third-party low-code platforms) for their feasibility, scalability, and alignment with cross-functional business needs.
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Solve for business problems by applying novel techniques and Innovating thinking.
Collaboration:
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The Senior AI/ML Engineer will partner with data scientists, architects, product managers, business stakeholders, and technical teams across the organization to ensure AI solutions align with organizational goals.
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Providing direct technical support and mentorship to technical teams across the enterprise is essential for enabling successful AI/ML implementations.
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Enabling other teams to adopt AI Into their products
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Leverage diverse skills and perspectives, leading to more effective problem-solving and decision-making.
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Other duties as assigned.
REQUIRED QUALIFICATIONS:
Knowledge of:
- Machine learning algorithms, deep learning frameworks, Cloud AI technologies, GenAI technologies and emerging Agentic AI technologies.
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Cloud platforms (e.g., AWS, Azure, GCP) for scalable AI/ML development.
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Responsible AI principles, including bias mitigation and ethical deployment.
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ML Ops best practices including CI/CD for ML, model monitoring, and versioning.
- Proficient in Python and common ML/AI libraries (e.g., TensorFlow, PyTorch, scikit-learn).
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Strong understanding of data engineering, SQL, and feature engineering.
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Direct experience with cloud services such as AWS Sagemaker, Lambda, ECS, S3, and IAM.
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Familiarity with containerization (Docker) and orchestration (e.g., Airflow, Kubeflow).
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Working with version control and collaboration tools (Git, Jira, Confluence).
Ability to:
- Build robust, scalable, and efficient AI/ML solutions in cloud-native environments.
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Translate ambiguous business problems into clear, technical ML/AI tasks.
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Communicate complex ideas clearly to technical and non-technical stakeholders.
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Learn and adapt quickly to emerging AI technologies, techniques, and tools.
Education and/or Experience:
- A bachelor's degree in computer science, information technology, engineering, or a related field is required. However, equivalent related experience and/or education may be considered as a substitute for the degree requirement upon evaluation.
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5+ years of experience designing and deploying ML/AI solutions in real-world environments.
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Or a combination of 8 or more years of experience of software development/engineering, of which three or more years are AI/ML experience.
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Proven experience with GenAI tools and technologies (e.g., LLMs, prompt engineering, Vector databases, RAG, fine-tuning)
PREFERRED QUALIFICATIONS: (Additional qualifications that may make a person even more effective in the role, but are not required for consideration)
- Master’s or PhD in a related technical field.
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Hands-on experience with agentic AI frameworks.
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Prior contributions to open-source AI/ML projects or published research.
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AI/ML certifications from cloud providers
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Experience in highly regulated industries (e.g., healthcare, finance) a plus.
