Chief GenAI Engineer
Machine Learning Engineering
& 20 others
Mexico
We are seeking a skilled Chief GenAI Engineer to lead the design and implementation of advanced AI-powered workflows for automating mortgage document review, data extraction, and due diligence on a large scale.
This role offers the chance to work with innovative technologies like AWS Bedrock, LLMs, RAG, and serverless architectures, while collaborating with a multidisciplinary team to create impactful enterprise solutions.
Responsibilities
- Deliver solutions for automating mortgage document OCR, data extraction, and due diligence using AWS Bedrock and supporting cloud services
- Integrate and optimize GenAI/RAG systems with Bedrock Prompt Engineering, Blueprints, Knowledge Base, chunking strategies, and LLM customization
- Create scalable and reliable cloud pipelines using Python or Node.js, as well as tools like Lambda functions, Aurora RDS, Step Functions, EventBridge, and SQS
- Design systems to handle up to 2 million documents per hour with high reliability, robustness, and low latency
- Ensure efficient workflows and system health by implementing monitoring, error tracking, and metrics
- Partner with AI PODs, product owners, and technical leads to accelerate workflow onboarding and improve delivery speed without sacrificing quality
- Apply industry standards in code quality, infrastructure security, compliance, and data privacy for enterprise-ready solutions
- Incorporate approved AI tools, including GitHub Copilot and ChatGPT Sandbox, to enhance productivity and ensure secure code development
Requirements
- 7+ years of experience in Machine Learning Engineering
- Knowledge of AWS Bedrock components such as BDA, Blueprints, Knowledge Base, and Agents, including Prompt Engineering and Management
- Background with LLM architectures, RAG frameworks, and document chunking techniques for retrieval and extraction
- Proficiency in Python or Node.js for creating serverless pipelines
- Demonstrated experience delivering and maintaining high-throughput workflow solutions using Lambda Functions, Lambda Layers, Step Functions, SQS, EventBridge, Aurora RDS Serverless, and Amazon Textract
- Competency in deploying high-volume, high-velocity workflows in enterprise environments
- Understanding of cloud architecture patterns, security, performance optimization, and cost-efficient designs for serverless and distributed systems
- Strong ability to resolve issues during debugging and effectively manage production incidents
- Effective communication skills with the ability to collaborate in dynamic, remote, cross-functional teams
- Flexibility to manage tight deadlines and changing priorities while maintaining high-quality delivery
Nice to have
- Familiarity with mortgage and real estate document workflows, compliance standards, and data models
- Expertise in enhancing large-scale document processing workflows for higher throughput
- Background in AI/ML Ops, monitoring tools, governance frameworks, and compliance best practices in enterprise cloud environments
- Advanced understanding of prompt engineering methods for improving GenAI/LLM performance in document automation use cases
- Capability to use GitHub Copilot to improve developer productivity and code quality
Benefits
- International projects with top brands
- Work with global teams of highly skilled, diverse peers
- Healthcare benefits
- Employee financial programs
- Paid time off and sick leave
- Upskilling, reskilling and certification courses
- Unlimited access to the LinkedIn Learning library and 22,000+ courses
- Global career opportunities
- Volunteer and community involvement opportunities
- EPAM Employee Groups
- Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn