to join their advanced AI initiatives focused on transforming investment decision-making. This role centers on building intelligent systems that empower financial professionals-portfolio managers, analysts, and researchers-with smarter, faster tools. You'll lead the development of scalable AI infrastructure and intuitive applications that merge cutting-edge machine learning with complex data environments.
What You'll Do
Architect and implement a next-generation financial data retrieval engine
Work closely with frontend teams to ensure seamless integration into live platforms
Partner with ML experts to prototype and deploy new AI-driven products
Own the full development lifecycle-from concept to deployment and ongoing support
Guide junior engineers and influence system architecture
Participate in on-call rotations to maintain mission-critical AI systems
What You Bring
8+ years in software engineering, including 3+ years focused on backend AI systems
Deep experience with graph databases (e.g., Neo4j), knowledge graph modeling, and large-scale data integration
Advanced proficiency in Python and ML libraries
Strong command of SQL/NoSQL, REST APIs, and gRPC
Familiarity with Docker, Kubernetes, CI/CD pipelines, and infrastructure-as-code
Clear communication skills across technical and non-technical audiences
Bonus Skills
Experience deploying LLMs and AI models in production
Familiarity with OpenAI, Claude, or similar APIs
Hands-on with vector databases and retrieval-augmented generation (RAG) systems
Understanding of financial markets and investment workflows
Cloud experience (AWS preferred), plus Kafka or RabbitMQ
Exposure to multi-agent AI systems and observability tools like Grafana or Sentry