Senior AI/ML Engineer

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:

• Design, develop, and deploy production-grade traditional ML models (e.g., regression, classification, clustering, recommender systems) for a variety of business use cases.

• 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).

• Integrate cloud-native and third-party AI SaaS solutions to accelerate delivery and reduce time to value.

• Ensure AI/ML solutions are scalable, dependable, secure, and cost-effective within cloud environments.

• Create reusable components, frameworks, and best practices to accelerate AI development.

Design and Innovation:

• 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.

• Solve for business problems by applying novel techniques and Innovating thinking.

Collaboration:

• 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.

• Providing direct technical support and mentorship to technical teams across the enterprise is essential for enabling successful AI/ML implementations.

• Enabling other teams to adopt AI Into their products

• Leverage diverse skills and perspectives, leading to more effective problem-solving and decision-making.

• Other duties as assigned.

REQUIRED QUALIFICATIONS:
Knowledge of:

• Machine learning algorithms, deep learning frameworks, Cloud AI technologies, GenAI technologies and emerging Agentic AI technologies.

• Cloud platforms (e.g., AWS, Azure, GCP) for scalable AI/ML development.

• Responsible AI principles, including bias mitigation and ethical deployment.

• 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).

• Strong understanding of data engineering, SQL, and feature engineering.

• Direct experience with cloud services such as AWS Sagemaker, Lambda, ECS, S3, and IAM.

• Familiarity with containerization (Docker) and orchestration (e.g., Airflow, Kubeflow).

• Working with version control and collaboration tools (Git, Jira, Confluence).

Ability to:

• Build robust, scalable, and efficient AI/ML solutions in cloud-native environments.

• Translate ambiguous business problems into clear, technical ML/AI tasks.

• Communicate complex ideas clearly to technical and non-technical stakeholders.

• 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.

• 5+ years of experience designing and deploying ML/AI solutions in real-world environments.

• Or a combination of 8 or more years of experience of software development/engineering, of which three or more years are AI/ML experience.

• 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.

• Hands-on experience with agentic AI frameworks.

• Prior contributions to open-source AI/ML projects or published research.

• AI/ML certifications from cloud providers

• Experience in highly regulated industries (e.g., healthcare, finance) a plus.
   

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