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
Human Work
Lead technical discovery sessions and scoping workshops with financial services clients to understand needs and challenges
Take ownership of technical sales process to ensure proposed AI solutions align with client requirements
Lead solution architecture and design where AI agents require custom integration with financial systems
Own quality and performance of developed AI solutions for banking, insurance, and asset management clients
Communicate technical progress and milestones to stakeholders, focusing on business impact and strategic value
Define prompts, context, verification processes, and fine-tuning strategies for AI agents
Establish best practices for prompt engineering and context management in financial use cases
Architecture & Design
Develop comprehensive AI solution visions and architectures for financial services clients
Design scalable AWS-based AI architectures that meet regulatory requirements
Create compelling presentations and demos showcasing proposed AI solutions for call centers and document processing
Provide accurate estimates for timelines, resources, costs, and delivery milestones
Rapidly prototype AI/ML solutions to validate capabilities for financial use cases
Lead implementation of emotionally intelligent agents for customer service applications
Leadership
Mentor and lead teams of ML Engineers deploying GenAI solutions
Establish technical standards and quality gates for AI implementations
Bridge communications between technical teams and business stakeholders
Identify and mitigate technical risks in AI deployments within regulated environments
Skills
Expert-level solution architecture skills with AWS AI/ML services
Advanced technical leadership and team coordination abilities
Exceptional client-facing communication and presentation skills
Hands-on experience with:
AWS AI/ML stack (Bedrock, SageMaker, Lambda, Connect, Comprehend)
LLM frameworks and their enterprise integration (Anthropic Claude, LangChain)
System design for high-compliance environments
Technical sales and solution demonstrations
Strong technical writing and documentation capabilities
Rapid prototyping and proof-of-concept development
Knowledge
Deep understanding of enterprise architecture patterns for AI systems
Comprehensive knowledge of AI agent frameworks and orchestration
Expert understanding of AWS AI/ML services and architectural best practices
Strong awareness of financial services regulations and compliance requirements
In-depth knowledge of:
Call center technologies and integration points
Document processing workflows in financial institutions
Emotional intelligence capabilities in customer-facing AI solutions
Financial domain processes (lending, claims, advisory, etc.)
Security and privacy considerations for financial data
Experience
5+ years of experience leading technical teams in banks, insurance companies, or financial technology providers
5+ years of proven track record designing and implementing enterprise-grade AI solutions
3+ years of client-facing technical leadership in solution architecture or forward-deployed engineering roles
3+ years of experience with AWS architecture and services, particularly AI/ML offerings
Bachelor's degree in Computer Science, Engineering, or related field (Master's preferred)
Successful delivery of multiple large-scale AI projects from concept to production