AI & Agentic Systems Engineering, AVP

Lead architecture and delivery of enterprise-grade AI solutions incorporating Generative AI, Large Language Models, and agentic frameworks with human-in-the-loop controls and safety mechanisms.

Develop and operationalize LLM-powered applications and retrieval-augmented generation (RAG) solutions using cloud platforms and AI tools, establishing LLMOps capabilities for monitoring, evaluation, and responsible AI.

Design and build scalable full-stack data and cloud engineering solutions, supporting machine learning and financial analytics models for asset management contexts, driving measurable business outcomes.

Hands-on software engineering experience including enterprise-scale distributed applications and production-grade AI/Generative AI solutions.

Strong skills in ReactJS, TypeScript, Python or Java along with API, microservices, asynchronous application design; familiarity with FastAPI or Spring Boot beneficial.

Experience with data platforms (BigQuery, PostgreSQL), cloud-native architectures, CI/CD, containerization (Docker, Kubernetes), infrastructure as code (Terraform), and observability tools (OpenTelemetry).

Bachelor’s degree in Computer Science, Engineering, Science or related discipline, or equivalent professional experience. Work Experience Required: Not explicitly mentioned in the JD.

Experienced in developing AI agents and LLM applications with practical expertise in orchestration, evaluation, and observability tools for AI workflows.

Strong understanding of financial markets, investment products, and asset management relevant to applying predictive/analytical models for ETFs, mutual funds, and risk/performance metrics.

Able to translate complex business and investment challenges into scalable technical solutions, collaborating effectively with product, business, and control functions to deliver measurable impact.