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About the Role
The Equities Platform and Cloud Engineering team operates at the intersection of applied AI, cloud infrastructure and DevOps, supporting production-grade platforms and systems in a fast-moving engineering environment.
Responsibilities
- Build and maintain secure, cloud-native infrastructure spanning compute, storage, networking, identity and access management, secrets management, logging and monitoring.
- Own CI/CD pipelines, infrastructure as code, containerization and deployment automation for AI and cloud platform services.
- Design, build and deploy production-ready LLM applications, multi-step AI agents and agentic workflows using orchestration, tool calling, memory and structured outputs.
- Integrate vector databases, graph databases, APIs and internal platforms to enable complex retrieval and automation use cases.
- Build Agent Harness infrastructure that manages LLM calls, tool usage, retries, policy enforcement and reusable agent execution patterns.
- Develop Agent Flywheel pipelines that capture traces, identify regressions, route failures into evaluation workflows and improve prompts, tools and models using production signals.
- Implement evaluation suites and deployment gates that measure task success, tool-selection accuracy, hallucination rates, latency, cost and overall agent quality.
- Partner across engineering and product teams to move solutions from prototype to production, prioritizing reliability, scalability, security and operational excellence.
Requirements
- Bachelor’s or master’s degree in Computer Science, Engineering or a related field, or equivalent practical experience.
- Hands-on experience developing LLM applications, AI agents, prompt engineering or retrieval-augmented generation systems.
- Experience with agentic AI frameworks such as Google ADK, PydanticAI, Claude Agent SDK or similar technologies, including tool-based architectures, MCP servers, hooks, plugins or skills.
- Strong Python software engineering skills and experience building production APIs and services.
- At least one year of experience with AWS, Azure or GCP and modern cloud architecture patterns.
- At least one year of experience with Docker, Kubernetes, Terraform and CI/CD workflows, with familiarity in deployment tools such as GitHub Actions or ArgoCD.
- Familiarity with vector and graph databases, data integration patterns and observability tools such as Grafana, Prometheus or Datadog.
- A proactive, creative and ownership-driven approach, with the ability to balance AI experimentation with disciplined engineering, security, access control and production reliability.
Skills
- LLM applications
- AI agents
- Prompt engineering
- Retrieval-augmented generation
- Agentic AI frameworks
- Google ADK
- PydanticAI
- Claude Agent SDK
- Python
- Production APIs
- Production services
- AWS
- Azure
- GCP
- Cloud architecture
- Docker
- Kubernetes
- Terraform
- CI/CD
- GitHub Actions
- ArgoCD
- Vector databases
- Graph databases
- Data integration
- Observability tools
- Grafana
- Prometheus
- Datadog
Location
- New York
Work Type
- Full-time
Experience Level
- Entry level
- Mid level
Education Level
- Bachelor's degree
- Master's degree
Salary/Compensations
- $100,000 to $175,000
Benefits
- Discretionary performance bonus
- Comprehensive benefits
About the Company
- Millennium is a global, diversified alternative investment firm, founded in 1989.
- Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors.
- Our people are empowered with both independence and support: the autonomy to pursue ideas with conviction and the backing of a global network committed to collaboration, disciplined risk management and continuous learning.
- With opportunities to deepen expertise and accelerate development, talent at Millennium is equipped to adapt, evolve and build lasting impact over time.
- Discover how transformative growth accelerates impact.
- Technology is core to the health and growth of Millennium’s business.
- The firm’s active, multi-manager model demands flexible, scalable technology and advanced proprietary systems, including the next generation of analytical and trading capabilities.