Sr. Lead AI Developer
Duration: 3- 6 Months (Contract to perm)
Pay:59/HR
Work Mode: Remote
Interview Type:  Not Mentioned 

Ropes Test: Yes
Location: 

Scottsdale, Arizona 85260

Position Overview: 

The Finance Technology AI Enablement team is seeking a Senior Lead AI Developer who can work independently and partner directly with business leaders and subject matter experts (SMEs) to understand current business processes and design AI-driven solutions that transform how those processes operate.

This role requires a hands-on technical leader who is equally comfortable architecting complex, distributed AI/ML systems and presenting solutions and roadmaps to business and IT leadership.

Key Responsibilities

• Business Partnership & Discovery: Work independently and collaborate directly with business leaders and SMEs to understand current business processes, pain points, and objectives.
• Solution Architecture: Design and propose AI-enabled solutions that transform and automate existing business processes end-to-end. Create automation, AI, and ML architecture, including detailed technical design, and lead the build-out of the resulting solutions.
• GenAI & Agentic Workflows: Design and implement Generative AI, Machine Learning, automation, and complex agentic workflow solutions.
• Advanced Semantic Layers: Build high-performing, complex semantic layers using advanced technologies such as RAG, Knowledge Graphs, and GraphRAG.
• Natural Language Processing (NLP): Enable natural language querying against large-volume databases with a large number of tables and complex relationships.
• Financial Analytics & AI: Architect and implement financial data processing and analytics solutions enabled by AI/ML. Develop analytics AI capabilities, including forecasting, fraud detection, and prediction models using Machine Learning.
• AI-First Architecture: Drive an AI-first architecture approach across data processing automation and business process automation initiatives.
• High-Volume Systems: Design solutions for high-volume processing using event-driven frameworks and platforms.
• Stakeholder Engagement: Present technical concepts, solution designs, and roadmaps clearly to business leaders and large IT audiences.
• Leadership & Mentorship: Provide technical leadership and mentorship within the AI Enablement team.

Required Qualifications

Experience

• Software & AI/ML Development: 8+ years of experience in software/AI/ML development, including cloud and distributed architecture and platform solutions.
• Cloud & Infrastructure: Hands-on experience with major cloud platforms (Azure, Google Cloud Platform, and AWS) as well as Kubernetes and container orchestration.
• High-Volume Data Processing: Experience with event-driven frameworks/platforms and high-volume data processing.
• GenAI & Agentic Systems: Extensive experience with Generative AI (GenAI) and Machine Learning solution design and implementation, including building complex agentic workflows and automation solutions.
• Financial Data & Analytics: Experience with financial data processing, analytics enabled by AI/ML, and analytics AI use cases such as forecasting, fraud detection, and prediction using ML.
• Advanced Data Architectures: Experience building semantic layers using RAG, Knowledge Graph, and GraphRAG technologies.
• Enterprise NLP: Experience enabling NLP-based querying against large, complex relational databases.

Skills & Competencies

• Technical Design: Strong ability to translate business processes into AI/automation architecture and detailed technical designs.
• Autonomy: Ability to work independently with minimal oversight while managing multiple stakeholders.
• Problem-Solving: Strong analytical and problem-solving skills with an AI-first mindset.
• Communication & Presentation: Excellent communication and presentation skills, with the ability to engage business leaders and large IT audiences effectively.
• Stakeholder Collaboration: Strong collaboration and soft skills, with the ability to build trust with business and technology stakeholders.

Preferred Attributes

• Domain Knowledge: Prior experience in Finance Technology or financial services domains.
• Track Record: Proven track record of leading AI transformation initiatives from concept through production deployment.
• Team Leadership: Experience mentoring junior developers and driving technical best practices.