Freddie Mac is looking to leverage Generative AI (Gen AI) to solve complex business problems by designing and developing cutting-edge AI Agents, Agentic Workflows, and Gen AI Applications to enhance operational efficiency, make data-driven decisions, and unlock new opportunities for growth.
Requirements
- Advanced proficiency in Prompt Engineering, Large Language Models (LLMs), RAG, Graph RAG, MCP, A2A, multi-modal AI, Gen AI Patterns, Evaluation Frameworks, Guardrails, data curation, and AWS cloud deployments.
- Experience training and testing Machine/Deep Learning, Natural Language Models
- Proven experience with AI development on AWS SageMaker, Bedrock, ML Flow on EKS
- Strong programming skills in Python and ML libraries (Transformers, Lang Chain, etc.)
- Deep understanding of Gen AI system patterns and architectural best practices, Evaluation Frameworks
- Deep expertise in prompt engineering, fine-tuning, RAG, Graph RAG, vector databases (e.g., AWS Knowledge Base / Elastic), and multi-modal models.
- Hands-on experience with enterprise AI governance and ethical deployment frameworks.
Responsibilities
- Design and implement scalable AI Agents, Agentic Workflows and GenAI applications to address diverse and complex business use cases.
- Evaluate and adapt models such as Claude (Anthropic), Azure OpenAI, and open-source alternatives for business use cases
- Train, Fine-tune, optimize and Test lightweight Large Language Models (LLMs) to address diverse and complex business use cases
- Design and deploy Retrieval-Augmented Generation (RAG) and Graph RAG systems using vector databases and knowledge bases.
- Curate enterprise data using connectors integrated with AWS Bedrock's Knowledge Base/Elastic
- Implement solutions leveraging MCP (Model Context Protocol) and A2A (Agent-to-Agent) communication
- Build and maintain Jupyter-based notebooks using platforms like SageMaker and MLFlow/Kubeflow on Kubernetes (EKS)
Other
- Demonstrated ability to work in cross-functional agile teams
- Collaborate with cross-functional teams of UI and microservice engineers, designers, and data engineers to build full-stack Gen AI experiences
- Collaborative Teamwork: Communicate effectively with cross-functional teams to integrate AI solutions seamlessly.
- AI Governance and Ethics: Implement robust validation procedures to ensure ethical and compliant AI solutions.
- Continuous Learning: Stay adaptable and keep up with the latest AI advancements.
