Description

Key Responsibilities:

• 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 Lang Chain, Lang Graph, 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 Client 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.

Key Requirements and Technology Experience:

• Must have skills: - Generative AI, Python , AWS Bedrock
• Deep understanding of AI/ML frameworks, data pipelines, and cloud-native architectures.
• Hands-on experience with LLM deployment, fine-tuning, and integration.
• Advanced proficiency in Python programming with the ability to design, develop, test, and troubleshoot production-grade AI/ML applications and reusable frameworks.
• Proficiency in agentic AI design patterns and implementation.
• Expertise in Model Context Protocol (MCP) for context-aware model deployment and management.
• Strong knowledge of Client, AWS, and advanced data modeling.
• Experience with data governance, security, and compliance best practices.
• Excellent communication, collaboration, and presentation skills.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• 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.
• Hands-on experience building AI applications using Python frameworks such as Lang Chain, Llama Index, Fast API, and AWS/Open AI SDKs.
• Strong experience with Client and AWS services (Glue, S3, Lambda, Sage Maker, etc.).
• Experience in the financial services or mortgage industry is preferred

Key Skills

Education

Any Graduate