Kofax/Tungsten AI Engineer– IDP || Minneapolis, MN (Onsite)

Kofax/Tungsten AI Engineer– IDP

Minneapolis, MN (Onsite)

Phone + Video

Job Description:

Support Ameriprise’s AI platform team in implementing Intelligent Document Processing (IDP) solutions that extract and structure information from financial and business documents using large language models and AWS AI services.

The role will help accelerate delivery of multiple AI use cases across the organization by designing document understanding pipelines and configuring LLM-based extraction workflows.

 

Required Skills:

• 4 – 5 Years of hands-on experience within Tungsten/ KOFAX Total Agility
• hands-on experience within Tungsten/ KOFAX Capture
• .NET development experience
• Software design experience for large customer scalability
• Experience with AWS hosted applications
• Hands-on experience with integration and building restful APIs
• 1-year Hands on experience with Prompt engineering within AI models
• Experience working with JIRA and Confluence
• Ability to work independently
• Good communication skills

 

Preferred Skills

3 Years experience leading a team of junior developers

3 Years experience with distributed Application design

 

Key Responsibilities

1. Intelligent Document Processing Development

Design and implement AI pipelines that extract structured data from unstructured documents such as:

• financial forms
• contracts
• estate planning documents
• advisor documentation
• client onboarding materials
• disclosures

Tasks likely include:

• document classification
• entity extraction
• document summarization
• field mapping
• validation workflows

2. LLM Integration & Prompt Engineering

Develop prompts and model configurations to optimize document understanding and extraction.

Work with models such as:

• Anthropic Claude
• OpenAI GPT
• Azure OpenAI
• Google Gemini

Responsibilities may include:

• prompt design and optimization
• evaluating model output accuracy
• implementing prompt templates
• configuring model behavior for different document types

 

AI Architecture Implementation

Build and configure AI pipelines within the Ameriprise environment using AWS services.

Likely stack:

• AWS Bedrock
• AWS Textract
• Amazon SageMaker
• S3
• Lambda
• Glue
• API integrations

Responsibilities may include:

• integrating document ingestion workflows
• connecting extraction pipelines to internal systems
• implementing scalable AI inference workflows

 

4. Model Evaluation & Use Case Delivery

Support multiple AI use cases across Ameriprise teams.

HM said he went from:

2 use cases → 60 use cases

The engineer will likely:

• onboard new document types
• tune models for extraction accuracy
• configure new pipelines quickly
• help scale AI capabilities across business teams

5. Collaboration with AI Platform Team

Work with:

• AI platform engineers
• data engineers
• enterprise architects
• business stakeholders

The role will help translate business needs into AI document processing solutions.

Required Skills

AI / LLM

• Experience with Large Language Models
• Prompt engineering
• LLM evaluation and tuning
• Document understanding workflows

IDP / Document Processing

Experience with technologies such as:

• AWS Textract
• Azure Document Intelligence
• Google Document AI
• ABBYY
• LLM-based document extraction

Understanding of:

• OCR
• document classification
• entity extraction
• structured data generation

Cloud

Strong experience with AWS:

• Bedrock
• SageMaker
• Lambda
• S3
• API integrations

Programming

Likely languages:

• Python
• possibly some Java or Node

Used primarily for:

• pipeline orchestration
• API integration
• model interaction