AI Engineer
Core
Design and implement single-agent and multi-agent architectures for enterprise workflows, translating Trading, Risk, Compliance, Finance, and Operations processes into agent-driven automation.
Role type
Senior IC AI Engineer (Agent Systems)
Builds
Reusable agent patterns, templates, goal-driven automation systems, and production agent deployments.
Domain
Enterprise AI / Financial Services
Deliverable
production ML models
Required skills
Python, LLM-based applications, agent systems, API development, microservices, tool orchestration, vector databases, RAG pipelines, prompt engineering, cloud platforms, Docker, Kubernetes, production deployment, observability
Preferred skills
LangChain, LangGraph, AutoGen, CrewAI, evaluation pipelines, cost-latency-performance trade-off assessment
Technologies
Anthropic, Azure OpenAI, GCP Vertex AI, LangChain, LangGraph, AutoGen, CrewAI, AWS, Azure, GCP, Docker, Kubernetes
Responsibilities
Design and implement single-agent and multi-agent architectures; Develop reusable agent patterns, templates, and goal-driven automation systems; Deploy agents using Anthropic, Azure OpenAI, and GCP Vertex AI platforms; Configure secure execution environments, lifecycle management, session handling, human-in-the-loop approvals, and escalation workflows; Own prompt and configuration versioning, staged rollouts, canary releases, and the agent release lifecycle; Integrate agents with internal data platforms, APIs, services, and structured knowledge layers; Implement RAG pipelines, vector databases, evaluation frameworks, fallback mechanisms, error handling, cost controls, and usage guardrails; Monitor production agent behavior and performance while maintaining audit trails and explainability; Ensure agents comply with security policies, data-access constraints, and regulatory frameworks; Translate workflows from Trading, Risk, Compliance, Finance, and Operations into agent-driven automation.
