AI Lead, Client Technology - SVP

• Design, implement, and deploy intelligent agents, including perception, reasoning, planning, and action execution modules
• Contribute to the development and implementation of generative AI solutions, ensuring they meet technical requirements and business objectives
• Develop scalable and robust architectures for agentic systems and generative AI applications, ensuring high performance, reliability, and security
• Integrate various machine learning models (e.g., LLMs, reinforcement learning, predictive models) to enhance agent capabilities and decision-making
• Implement LLM integration using platforms like OpenAI, Anthropic, and Bedrock APIs
• Develop agents that can automate complex tasks, optimize workflows, and solve real-world problems across various domains
• MVP first approach, iterative improvement approach with a focus on 'time to value' (quick iterations, hypothesis testing, A/B experiments)
• Utilize and contribute to agentic AI frameworks and development tools
• Build full-stack applications that integrate existing ML/LLM tools and services
• Design and implement metrics and evaluation strategies for agent performance, continuously optimizing and improving agent behavior
• Stay abreast of the latest advancements in AI, particularly in agent-based systems, autonomous AI, and related fields, and propose innovative solutions
• Demonstrate deep expertise in generative AI technologies, actively participating in the development of proofs of concept (POCs) and exploring new methodologies
• Work closely with cross-functional teams (AI researchers, data scientists, product managers, software engineers) to integrate agentic and generative AI solutions into broader products and services
• Lead technical teams through hands-on coding and architectural decisions, championing pragmatic 'buy and integrate' approaches
• Create comprehensive technical documentation for agent designs, implementations, and operational procedures
• Manage a small AI team to deliver on key AI initiatives in the client delivery space

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field
• 10+ years software engineering experience with recent hands-on coding, with a track record of rapid delivery and launching multiple AI features in production
• Minimum 3+ years of professional experience in software development with a focus on AI, prompt engineering, machine learning and/or agentic AI systems
• Strong proficiency in Python (FastAPI, Django, Flask, PySpark) or Java (Spring Boot, Spring Cloud, Spring Security), and SQL
• JavaScript (React, Next.js, Node.js, TypeScript)
• Full-stack development with a focus on rapid prototyping
• Solid understanding of core AI concepts, including knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and relevant libraries (e.g., Scikit-Learn, NumPy, Pandas)
• Familiarity with large language models (LLMs) like ChatGPT, LaMDA/Gemini, Llama, etc., and their application in agentic systems
• Familiarity with specific agent frameworks (e.g., LangChain, AutoGen, CrewAI, RAG) or research in multi-agent reinforcement learning
• Experience in designing and implementing APIs for AI services
• Experience with software development best practices, including version control (Git), CI/CD pipelines, testing, and code reviews
• Understanding of agile methodologies, application resiliency, and security applied to AI projects
• Proven experience in system design, application development, and operational stability in AI projects
• Experience with application and data architecture patterns and designs
• Thorough understanding of data flows from producer to consumer systems
• Familiarity with data engineering practices to support AI model training and deployment
• Leveraging managed services and existing platforms, with an API-First Design emphasizing microservices and event-driven architectures
• Experience with Docker and Kubernetes
• Excellent analytical and problem-solving skills with a creative approach to complex challenges
• Strong written and verbal communication skills, with the ability to articulate complex technical concepts to diverse audiences

Experience in the finance industry is a plus

• medical, dental & vision coverage
• 401(k)
• life, accident, and disability insurance
• wellness programs
• paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays
• discretionary and formulaic incentive and retention awards