Finance AI Transformation Lead

Deloitte France; Indianapolis (IN); On-site; USD 170,000 - 210,000; Full time

Job summary

Deloitte seeks a senior AI Solutions Architect to lead development and deployment of AI-enabled finance transformation engagements in a client-facing role. You will bridge business needs with technical delivery, guiding design, build, testing, and deployment across teams.

Ideal candidates have extensive Python, cloud, and data-engineering experience, with a focus on finance data use cases and strong stakeholder collaboration.

Qualifications

• Bachelor's degree or equivalent practical experience in Engineering/CS.
• 6+ years of software development experience.
• Experience architecting AI systems on cloud platforms (GCP, AWS, Azure).
• Experience delivering AI-driven solutions end-to-end.
• Experience leading technical discovery with customers.
• Experience building data pipelines for structured/unstructured data.

Responsibilities

• Lead AI solution development and deployment with client relationships.
• Serve as techno-functional bridge between stakeholders and delivery teams.
• Lead engagements within larger programs for AI-enabled solutions.
• Translate requirements into build specifications across the project lifecycle.
• Shape AI use cases and solution design requirements with clients.
• Define scope, objectives, and delivery plans; manage architecture through delivery.
• Support proposals and mentoring of team members.

Skills

Python

Cloud architecture

AI systems

Data pipelines

SQL

AWS/GCP/Azure

Generative AI

Finance data

Client discovery

Project leadership

Education

Bachelor's degree in Engineering, Computer Science, or related field

Master's degree (preferred)

Tools

NVIDIA

GPT-4o

LangGraph

CrewAI

ADK

Job description

Deloitte seeks a senior AI Solutions Architect to lead development and deployment of AI-enabled finance transformation engagements in a client-facing role. You will bridge business needs with technical delivery, guiding design, build, testing, and deployment across teams.

Ideal candidates have extensive Python, cloud, and data-engineering experience, with a focus on finance data use cases and strong stakeholder collaboration.