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Job Description
Structured overview of role & requirementsAbout This Role
Lead design and delivery of enterprise-grade AI solutions using Generative AI, LLMs, and agentic frameworks, including AI copilots and multi-agent workflows.
Develop scalable, production-ready AI services, LLM-powered applications, and implement retrieval-augmented generation (RAG) leveraging semantic search and vector databases.
Build full-stack applications and data solutions with modern cloud-native architectures, ensuring engineering excellence through CI/CD, observability, and site reliability practices.
Minimum Requirements
Hands-on experience in software engineering including enterprise-scale distributed applications and production-grade AI or Generative AI solutions.
Proficiency in ReactJS, TypeScript, Python or Java; experience with API, microservices design, and frameworks like FastAPI or Spring Boot.
Experience with cloud platforms (e.g. Azure, Google Vertex AI), BigQuery, PostgreSQL, Docker, Kubernetes, Terraform, and CI/CD pipelines.
Bachelor’s degree in Computer Science, Engineering, Science or related discipline or equivalent experience; Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Practitioner with strong engineering ownership and ability to translate ambiguous business challenges into pragmatic technical solutions at scale.
Experienced in integrating AI technologies (LLMs, RAG architectures, vector databases, LLMOps) aligned with enterprise deployment and responsible AI practices.
Familiarity with financial markets, asset management products, and key investment risk/performance metrics to design relevant machine learning and analytical models.