Overview
Remote
Depends on Experience
Contract - Independent
Contract - W2
No Travel Required
Skills
Amazon S3
Amazon SageMaker
Amazon Web Services
Artificial Intelligence
Business Systems
Cloud Computing
Collaboration
Communication
Computer Science
Continuous Improvement
Data Engineering
Data Governance
Data Modeling
Data Science
Decision Support
Design Patterns
Emerging Technologies
Enterprise Application Integration
Financial Services
IT Management
Innovation
Large Language Models (LLMs)
Legal
Machine Learning (ML)
Management
Mentorship
Microsoft Certified Professional
LangChain
Mortgage
Orchestration
Presentations
Prompt Engineering
Regulatory Compliance
Snow Flake Schema
Software Development
Unstructured Data
Workflow
Job Details
Position: Lead AI and Data Solutions Engineer
Remote
Experience in the financial services or mortgage industry is preferred.
The ideal candidate will have deep expertise in data engineering, agentic AI systems, large language models (LLMs), and Model Context Protocol (MCP). The preferred candidate will bring deep experience with AWS and Snowflake services, including a strong understanding of security best practices for cloud-based AI and data solutions. This role requires a hands-on leader who can design scalable, secure, and innovative data pipelines and AI solutions that deliver business value.
Key Job Functions
- Solution Engineering: Lead the design, development, and deployment of enterprise-scale data and AI solutions, ensuring alignment with business objectives and technical best practices.
- LLM and Agentic AI: Architect, implement, and optimize large language models and agentic AI workflows for business automation and decision support.
- Framework Expertise: Design and deploy AI solutions using leading frameworks such as LangChain, LangGraph, and n8n for scalable agent orchestration, workflow automation, and integration with business systems
- Model Context Protocol (MCP):Develop, integrate, and manage MCP-based solutions to enhance model interpretability, context management, and deployment at scale.
- Cloud and Data Engineering: Leverage AWS and Snowflake to build scalable, secure, and efficient data pipelines for structured and unstructured data.
- Collaboration: Partner with cross-functional teams, including other technology, business, risk, legal, and compliance stakeholders, to deliver integrated solutions.
- Innovation: Stay current with emerging technologies and industry trends in AI, data engineering, and cloud computing, driving continuous improvement and innovation.
- Governance and Compliance:Ensure all solutions meet regulatory, security, and compliance requirements relevant to the financial services industry.
- Mentorship:Provide technical leadership and mentorship to junior team members.
Qualifications:
Education
- Bachelor s or Master s degree in Computer Science, Data Science, Engineering, or a related field.
Minimum Experience
- 8+ years of experience in data engineering, AI solution development, or related roles.
- Proven expertise in large language models (LLMs), agentic AI systems, and Model Context Protocol (MCP).
- Good working experience developing and integrating AI solutions using AWS Bedrock, including prompt engineering, RAG, and enterprise application integration.
- Strong experience with Snowflake and AWS services (Glue, S3, Lambda, SageMaker, etc.).
.
Specialized Knowledge & Skills
- Deep understanding of AI/ML frameworks, data pipelines, and cloud-native architectures.
- Hands-on experience with LLM deployment, fine-tuning, and integration.
- Proficiency in agentic AI design patterns and implementation.
- Expertise in Model Context Protocol (MCP) for context-aware model deployment and management.
- Strong knowledge of Snowflake, AWS, and advanced data modeling.
- Experience with data governance, security, and compliance best practices.
- Excellent communication, collaboration, and presentation skills.
- Ability to translate complex technical concepts for non-technical stakeholders.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.