AI/ML Engineer

Job Description

The 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 to address domain specific needs, improve user experiences and automate business workflows.

ACCOUNTABILITIES: (The primary functions, scope and responsibilities of the role)

Engineering:


* Work across diverse GenAI platforms like AWS, Salesforce, Oracle, Snowflake, MS Copilot, and other 3rd party GenAI platforms and libraries.


* Automate workflows involving extraction of complex, multimodal unstructured content from variety of sources in to highly accurate and reliable structured content using platforms like AWS Textract and Bedrock


* Design and build MCP hosts, clients and servers


* Establish and use frameworks for automated LLM testing


* Create regression test suites to detect drift or prompt breakage


* Integrate with internal and external web services using secure authentication and authorization mechanisms


* Adopt and ensure safe practices to protect against prompt injections, jailbreaks, and conform to enterprise security guidelines


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


* 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)


* Ensure AI/ML solutions are scalable, reliable, secure, and cost-effective within cloud environments


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

Design and Innovation:


* Design and develop GenAI solutions using prompt engineering, Context Engineering, Retrieval-Augmented Generation (RAG), and custom pipelines


* Design and develop interoperable AI agents using Model Context Protocol (MCP) and/or Google A2A

Collaboration and Enablement:


* Partner with data scientists, architects, product managers, business stakeholders and technical teams across organization to align AI solutions with organizational goals.


* Provide hands-on technical support and mentorship to technical teams across the enterprise.

REQUIRED QUALIFICATIONS: (Minimum qualifications needed for this position including education, experience, certification, knowledge and/or physical requirements)

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...