We are seeking a visionary leader to drive the architecture, development, and delivery of our next-generation AI platforms. This role will define the long-term technical roadmap, lead the engineering of scalable LLM agent frameworks, and ensure our AI capabilities empower business innovation across the enterprise and our customers.
Responsibilities
- Define and execute the strategic vision and roadmap for AI engineering within the AI Lab.
- Architect and deliver a scalable, high-performance GenAI platform with a robust LLM Agent Framework.
- Stay at the forefront of industry advancements in GenAI and agentic AI, adapting frameworks to leverage emerging technologies.
- Partner with business and technology teams to translate requirements into efficient agent solutions.
- Build and lead a high-performing team of AI specialists and full-stack engineers, fostering innovation and excellence.
- Establish engineering best practices, including CI/CD workflows, automated testing, observability, and reliability standards.
- Ensure compliance with architecture principles, technical standards, and security requirements.
- Drive continuous improvement in performance, scalability, and resilience of AI platforms.
Qualifications and Requirements
- B.S./M.S. in Computer Science, Software Engineering, or related field.
- Extensive experience and proven success in leading software engineering projects for financial institutions and clients
- Demonstrated expertise in Agentic AI, including planning, memory, and orchestration protocols such as Model Context Protocol (MCP)
- Deep hands-on experience in Java, Python and front-end frameworks like AngularJS, integrated with cloud-native stacks (OpenShift/Kubernetes)
- Strong exposure to Cloud and related technologies (AWS, Google Cloud)
- Proven expertise in designing and delivering large-scale LLM agent frameworks.
- Expert knowledge of CI/CD pipelines (e.g., LightSpeed), automated testing, and observability frameworks to measure team efficiency and software health.
- Deep understanding of agent paradigms (planning, memory, tool use, orchestration, evaluation).
- Hands-on experience with both high-code and low-code agent frameworks.
- Strong background in AI applications within financial services, including RPA + GenAI.
- Demonstrated success in managing large IT engineering teams.
- Excellent stakeholder management and communication skills, with the ability to influence senior leaders.
- Experience working in Agile environments with strong collaboration skills.
