Offer summary

Qualifications:

Bachelor's degree in Mathematics, Computer Science, Statistics, or related fields., 3+ years of professional experience in financial services, including banks and insurance companies., In-depth knowledge of AWS AI/ML services and conversational AI technologies., Advanced English proficiency, both written and verbal..

Key responsabilities:

Implement generative AI and LLM-based solutions for financial services clients independently.

Design and build AI agents for customer support in banking, insurance, and asset management.

Develop intelligent call center solutions integrating LLMs with voice technologies.

Create document processing workflows for financial documents using multimodal LLMs.

Job description

About the project

We have multiple projects in the FSI industry—banking, insurance, and asset management—with use cases related to front-office optimization, such as customer support and call centers using chatbots and voice solutions. We also handle back-office optimization, like document workflow and OCR-related automations.

Objective + KPI

Ensure deploying developed in-house AI and solutions on 80% of the projects
Maintain customer satisfaction index (CSI) at 100%

Areas of Responsibility

Fully independent implementation of generative AI and LLM-based solutions end-to-end for financial services clients
Designing and building AI agents for banking, insurance, and asset management customer support (text and voice)
Creating intelligent call center solutions that combine LLMs with voice technologies
Developing document processing workflows for financial documents using multimodal LLMs
Implementing emotional intelligence capabilities in AI agents for improved customer interactions

Skills

Hands-on machine learning and engineering with:
- AWS AI/ML stack (Bedrock, SageMaker, Lambda, Comprehend, Connect)
- LLM frameworks (Anthropic Claude, LangChain, LlamaIndex)
- Voice and conversational AI solutions for financial services
Hands-on machine learning models debugging:
- AWS CloudWatch and SageMaker debugging tools
- Experimentation frameworks (SageMaker Experiments, W&B)
- Call center AI agent optimization and evaluation
Advanced English (written and verbal)
Comprehensive documentation development

Knowledge

In-depth machine learning knowledge with specialization in conversational AI and document processing
In-depth knowledge of AWS AI/ML services and best practices for financial services
Expert in at least one specific GenAI technology:
- Conversational AI agents for call centers
- Emotional intelligence in AI systems
- Document processing with multimodal LLMs
- Voice synthesis and analysis
Domain expertise in financial services:
- Call center and customer support operations in banking/insurance
- Financial document workflows and processing requirements
- Compliance requirements for customer interactions (GDPR, MiFID II, DPA)
- Risk assessment and customer service protocols

Experience

3+ years of professional experience in banks, insurance companies, asset management firms, or financial technology service providers
2+ years of specific experience building GenAI solutions for financial services customer interactions
Demonstrated success implementing AWS AI/ML solutions in production environments
Experience with call center technologies and voice-based AI systems
Independent contractor experience (>2 projects >10k)
Bachelor's degree in Mathematics / Computer Science / Statistics or related fields (>4 years)

Required profile