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
Areas of Responsibility
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Fully independent implementation of generative AI and LLM-based solutions end-to-end for financial services clients
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Designing and building AI agents for banking, insurance, and asset management customer support (text and voice)
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Creating intelligent call center solutions that combine LLMs with voice technologies
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Developing document processing workflows for financial documents using multimodal LLMs
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Implementing emotional intelligence capabilities in AI agents for improved customer interactions
Skills
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Hands-on machine learning and engineering with:
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AWS AI/ML stack (Bedrock, SageMaker, Lambda, Comprehend, Connect)
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LLM frameworks (Anthropic Claude, LangChain, LlamaIndex)
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Voice and conversational AI solutions for financial services
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Hands-on machine learning models debugging:
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AWS CloudWatch and SageMaker debugging tools
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Experimentation frameworks (SageMaker Experiments, W&B)
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Call center AI agent optimization and evaluation
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Advanced English (written and verbal)
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Comprehensive documentation development
Knowledge
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In-depth machine learning knowledge with specialization in conversational AI and document processing
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In-depth knowledge of AWS AI/ML services and best practices for financial services
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Expert in at least one specific GenAI technology:
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Conversational AI agents for call centers
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Emotional intelligence in AI systems
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Document processing with multimodal LLMs
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Voice synthesis and analysis
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Domain expertise in financial services:
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Call center and customer support operations in banking/insurance
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Financial document workflows and processing requirements
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Compliance requirements for customer interactions (GDPR, MiFID II, DPA)
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Risk assessment and customer service protocols
Experience
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3+ years of professional experience in banks, insurance companies, asset management firms, or financial technology service providers
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2+ years of specific experience building GenAI solutions for financial services customer interactions
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Demonstrated success implementing AWS AI/ML solutions in production environments
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Experience with call center technologies and voice-based AI systems
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Independent contractor experience (>2 projects >10k)
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Bachelor's degree in Mathematics / Computer Science / Statistics or related fields (>4 years)
