We're building AI solutions for major banks, insurance companies, and asset management firms. Our work covers customer-facing chatbots and voice agents for support calls, plus back-office automation for document processing and workflows.

You'll independently work with advanced LLMs, voice technology, and multimodal AI that integrates seamlessly with existing banking systems.

Each project is technically challenging and high-impact, directly improving how millions of customers interact with their financial institutions. We're deploying our proprietary AI solutions across 80% of projects while maintaining perfect customer satisfaction, building both client value and our own IP platform.

The work requires deep technical skills and financial services expertise—you'll be creating solutions that work flawlessly in high-stakes, compliance-heavy environments.

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)

AI Engineer (BFSI)