Infrastructure Engineer

Join a next-generation investment and technology team in New York City as an Infrastructure Engineer. This firm is building a proprietary AI and data platform that powers an end-to-end investment lifecycle—integrating structured and unstructured data, advanced analytics, and automated workflows to drive superior, risk-adjusted performance. Their multidisciplinary team of engineers and investors is redefining how institutional-grade decisions are made across private credit and structured finance.

Purpose

They are seeking an Infrastructure Engineer to build and operate the foundational systems that power data, analytics, and AI platform. This is, at its core, an infrastructure and DevOps role: you will own the cloud infrastructure, deployment pipelines, orchestration, networking, and observability that everything else runs on.

You will work across the infrastructure layer beneath the data and ML/AI workflows cloud provisioning, container orchestration, CI/CD, and monitoring keeping our platform reliable, scalable, and secure.

If you are excited about AI and want to grow into building, hosting, and operating agentic AI systems, you will have ample opportunity to do so. That work is a welcome bonus rather than a prerequisite the heart of this role is building and maintaining the infrastructure around those platforms.

Roles and Expectations

• Deploy, configure, and maintain shared platform services as containerized workloads including end-to-end ownership of networking, access, and connectivity between services.
• Manage cloud infrastructure, including container registries, managed identities, Key Vault secrets, storage backends, and virtual network configurations.
• Build and maintain CI/CD pipelines, branch protection policies, and release management workflows across repositories.
• Continuously evaluate and adopt tools and technologies that improve platform reliability, developer experience, and team velocity.

Required Skills

• 3+ years of experience in infrastructure, DevOps, platform engineering, or SRE roles with a clear track record of building and maintaining production systems.
• Solid understanding of containerization and cloud infrastructure — Docker, Kubernetes, and at least one major cloud provider.
• Hands-on experience deploying and operating containerized services in cloud environments, including configuring networking, load balancing, and service-to-service connectivity.
• Experience building and maintaining CI/CD pipelines, Git-based release management, and branch protection workflows.
• Experience with workflow orchestration tools (Prefect, Airflow, Dagster, or similar) in production environments.
• Familiarity with monitoring and observability tooling health metrics, alerting, logging, and tracing.
• Strong documentation habits and the ability to communicate technical architecture clearly to diverse stakeholders.

Nice to Have

• A genuine interest in AI and a desire to learn and grow into building, hosting, and operating AI agents and agentic systems.
• Familiar with agentic workflow frameworks (e.g., MCP, LangChain, or similar).
• Experience with MLOps or ML infrastructure, including model training, retraining, and inference workflows.
• Familiarity with model serving and deployment patterns (batch inference, real-time APIs, feature stores).
• Experience standing up and maintaining third-party AI/ML platform tools (e.g., Langfuse, MLflow, or similar observability and evaluation platforms).
• Experience managing internal Python package distribution (private PyPI, Artifactory, or similar).
• Openness to flexing into adjacent engineering work data engineering, software engineering, and similar to help fill extra capacity where the team needs it.

Benefits

• Performance-based bonus.
• Comprehensive health, dental, and vision insurance.
• Retirement savings plan with company match.
• Hybrid work structure with flexibility and strong team support.

Location

• Hybrid - 3 days per week in office
• Manhattan, New York City

About the Company

Join a team that blends deep technical expertise with institutional-level investing. This firm is building an advanced AI and data platform that powers the full investment lifecycle, enabling faster, smarter, and more transparent decision-making. Their approach combines engineering precision with financial insight—delivering systems that integrate diverse datasets, advanced analytics, and automated workflows. They value ownership, clarity, and innovation, and they are building a high-performance environment where technical talent can have direct impact on real-world investment outcomes.