Senior Platform Engineer - Cloud Architecture & AI Platforms

Who We Are
Derivative Path empowers institutions across the capital markets with innovative, AI-driven technology and expert advisory solutions. Our award-winning cloud platform supports banks, credit unions, private equity firms, hedge funds, asset managers, and insurance companies in managing interest rate, FX, and commodity risks, optimizing hedging strategies, and streamlining cross-border payments. With a client base spanning over 250 financial institutions and leading private equity firms, we deliver scalable solutions that enhance risk management and drive operational performance. Through strategic partnerships with Goldman Sachs, Wells Fargo, FNBO, Q2, and Jack Henry, we provide best-in-class capabilities to help clients achieve their financial objectives in an ever-evolving market.

With a team of seasoned professionals comprised of decades of industry experience, Derivative Path offers a flexible, hybrid work environment to its 125+ employees with the ability to work remotely and from one of four offices in San Francisco, New York, Chicago, and Manila. The Company is dedicated to building a diverse environment and has an unwavering commitment to creating a sense of belonging for all employees.

The Opportunity
Are you ready to build the foundation for the next generation of financial intelligence? At Derivative Path, we are leveraging cutting-edge AI to reshape how financial institutions operate.
We are seeking a Senior AI Platform Engineer to join our Delivery Infrastructure team. In this role, you will be the bridge between our robust DevOps practices and our AI Innovation Group, designing the scalable, secure cloud infrastructure that powers our AI and machine learning capabilities. What You Will Do
As a Senior AI Platform Engineer, you will operate as a core member of the Delivery Infrastructure (DevOps) team, sharing in day-to-day operational responsibilities while leading the architecture and implementation of infrastructure for our AI initiatives. You will work primarily within AWS, while leveraging specific Azure capabilities, to build a seamless environment for model training, deployment, and inference.

You will move beyond traditional infrastructure management to define MLOps standards, automate complex pipelines, and ensure our AI workloads are secure and reliable. You will empower our data scientists to move faster by providing them with a robust, self-service platform.

Key Responsibilities

• Design and own AWS multi-account architectures, including VPC networking, security controls, and shared-services patterns to support AI workloads.
• Build and maintain scalable compute environments using ECS Fargate, EKS, and Lambda for both application and model hosting.
• Implement Infrastructure as Code (IaC) using AWS CDK (preferred) or Terraform to define and manage the entire AI platform stack.
• Develop and manage CI/CD pipelines using GitHub Actions, incorporating blue/green and canary strategies for model deployments.
• Architect and operate data services including RDS (Aurora), S3, and Vector Databases (e.g., Pinecone, pgvector) to support RAG and other AI patterns.
• Partner with the AI Innovation Group to operationalize models using AWS SageMaker, Bedrock, and Azure OpenAI Service.
• Implement comprehensive observability for infrastructure and model performance, monitoring for latency, drift, and resource utilization.
• Ensure platform resilience and security, defining disaster recovery strategies and enforcing strict IAM policies for sensitive data.

Essential Qualifications

• 5+ years of experience in DevOps, Platform Engineering, or Cloud Infrastructure.
• Deep expertise in AWS core services (EC2, VPC, IAM, S3) and networking (Transit Gateways, Route 53).
• Strong proficiency in Infrastructure as Code, specifically AWS CDK or Terraform.
• Experience with container orchestration (Kubernetes/EKS or ECS) and Docker.
• Proficiency in Python for scripting and automation; experience with API frameworks (FastAPI) is a plus.
• Familiarity with MLOps practices and tools (SageMaker, MLflow, Kubeflow) and deploying LLMs in production.
• Experience designing CI/CD pipelines (GitHub Actions) for both code and data/model workflows.
• Understanding of database architecture, including relational (PostgreSQL) and vector stores.
• Bachelor’s degree in computer science, Engineering, or equivalent practical experience.

Location

• Canada

Benefits

• Competitive bonus, base salary, and equity compensation
• 23 days of PTO
• Fully remote
• RRSP contribution at 3%
• Competitive health benefits

The expected salary for this position is  $110K to $140K CAD and is eligible for a discretionary bonus and equity. We will consider your skills, experience, and location when determining your pay. 
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Derivative Path is an equal opportunity employer and does not discriminate based on any of the following: race, religious creed, color, age, sex, sexual orientation, gender identity, gender expression or gender characteristic, national origin, religion, marital status, medical condition, physical or mental disability, military service or veteran status, pregnancy, childbirth and related medical conditions, or any other classification protected by federal, state, and local laws and ordinances. Derivative Path offers a comprehensive benefits package, including health, dental, vision, retirement plan, contribution, and a generous paid time off policy.  As part of Derivative Path’s hiring process, interviews and evaluations may be conducted using AI-assisted technology.