What are the responsibilities and job description for the Artificial Intelligence Solution Engineer position at Idexcel?
About the Role
This isn't a traditional software engineering role, and it isn't a consulting role. As an AI Solutions Engineer, you'll own customer success from architecture through deployment while writing production code every week — one week building an AI workflow that extracts financial data from 500-page loan packages, the next designing an agentic workflow that applies lending policies across an enterprise portfolio. You'll work alongside product managers, engineers, credit officers, and CIOs to turn real banking problems into scalable AI capabilities that improve the platform for every customer.
What You'll Do
- Design and deploy enterprise AI solutions for commercial lenders — AI agents, RAG pipelines, and intelligent workflows integrated with core banking systems, LOS platforms, document repositories, and CRMs
- Write production software that becomes part of the Cync platform: agent skills, banking integrations, document intelligence pipelines, policy engines, credit analysis workflows, and multi-agent systems
- Move fast — prototype in days, deploy in weeks, measure adoption, and iterate continuously
What We're Looking For
- Strong engineering skills across several of: TypeScript/Node.js, Python, React, PostgreSQL, GraphQL, REST APIs, AWS
- Hands-on AI experience with LLMs, Amazon Bedrock, Anthropic Claude, agent frameworks, MCP, RAG, vector databases, and prompt engineering — production deployment experience highly valued
- Customer obsession — you ask "why" before building and measure success by customer outcomes, not story points
- A builder mindset and high ownership — you prototype, ship, and stay with a problem from discovery through production success
Bonus Points
Commercial lending, loan origination systems, credit underwriting, financial spreading, banking integrations, enterprise SaaS, document AI/OCR, compliance systems, security/identity (OAuth, Cognito, JWT), event-driven architectures, or AWS serverless.
Technologies You'll Use
Amazon Bedrock, Claude, Node.js, Python, React, TypeScript, PostgreSQL, GraphQL, AWS Lambda, API Gateway, Cognito, S3, CloudFront, EventBridge, Docker, GitHub Actions, Terraform/CloudFormation.