Senior Cloud Architect

Robots and Pencils

2d•$53 - $73

About The Position

We’re looking for a Senior Cloud Architect to contribute to the design and delivery of complex, multi-domain systems spanning cloud, data, and AI. This role is ideal for an experienced engineer growing into architectural ownership — someone who enjoys hands-on development, contributes to system design decisions, and is ready to take on larger pieces of the architecture. In this role, you will work as a delivery-embedded contributor on a cross-functional team, helping shape architecture across cloud infrastructure, data platforms, and AI/ML workloads. You’ll collaborate closely with senior architects, engineers, and product partners to deliver solutions that are scalable, secure, and maintainable, and develop the technical instincts that come from shipping things that matter.

Requirements

5+ years of professional software engineering experience, with exposure to architectural decision-making
Working knowledge of cloud platforms and cloud-native architectures (e.g., AWS, Azure, GCP)
Proficiency in Python and at least one other language commonly used in modern stacks (e.g., Java, Scala, TypeScript)
Hands-on experience with containerization and orchestration (e.g., Docker, Kubernetes)
Experience with infrastructure as code and CI/CD pipelines (e.g., Terraform, CloudFormation, GitHub Actions)
Working knowledge of relational and NoSQL databases, plus data pipelines and ETL/ELT concepts (e.g., PostgreSQL, MongoDB, Airflow, dbt)
Familiarity with AI/ML system design, including model deployment, MLOps, and LLM integration (e.g., SageMaker, Vertex AI, MLflow, Hugging Face)
Understanding of microservices, serverless, and event-driven architectures
Awareness of security, compliance, and observability fundamentals (e.g. GDPR, HIPAA, SOC2)
Strong problem-solving skills and the ability to navigate ambiguous technical challenges
Demonstrable usage of AI-forward tools such as Claude and Cursor

Nice To Haves

A doer. You see something broken and fix it. You'd rather move on clarity than wait for certainty.
A fast learner who knows you don't know everything. The AI landscape changes weekly. You're senior enough to know better and curious enough to keep learning anyway.
Direct in a way that makes the work better. You give honest feedback. You'd rather have the hard conversation than blow smoke.
Obsessed with craft. You know genius is in the details. You ship exceptional, not perfect, and you don't put your name on work you wouldn't stand behind.
Built for ownership. You honor commitments, admit mistakes fast, and back your teammates when a decision costs something. No handoffs, no finger-pointing.
All in. You treat clients' businesses like your own. You take the work seriously without taking yourself seriously.
Resourceful when the budget, timeline, or team is tight. Constraints don't slow you down. They sharpen you.
Glad to be in the room with people who care as much as you do. Our teams average fifteen-plus years of experience. We hire people who push each other to do better work.

Responsibilities

Contribute to architectural design across cloud, data, and AI/ML systems, taking ownership of meaningful components
Build and integrate cloud-native solutions including microservices, serverless, and containerized workloads (e.g., AWS, Azure, GCP, Kubernetes, Docker)
Implement infrastructure as code and CI/CD pipelines (e.g., Terraform, CloudFormation, GitHub Actions)
Design and contribute to data architectures including pipelines, warehouses, and modeling (e.g., Snowflake, BigQuery, Airflow, dbt)
Support AI/ML system design, including model serving, MLOps pipelines, and integration of LLM-based capabilities (e.g., SageMaker, Vertex AI, MLflow)
Implement monitoring, logging, and observability across deployed systems (e.g., Prometheus, Grafana, CloudWatch)
Bring an AI-forward mindset to your daily work, using tools like Claude, Cursor, and other modern AI assistants to ship higher-quality work at pace
Collaborate with engineers, data, AI, and product teams to translate requirements into sound technical solutions
Communicate technical tradeoffs and design decisions clearly across functions
Maintain architecture documentation that supports reproducibility, onboarding, and shared understanding
Participate actively in design reviews, raising concerns and offering constructive feedback
Take ownership of system components end-to-end with growing scope of architectural responsibility
Contribute to architectural standards and best practices that lift the quality of work across the team
Begin mentoring more junior engineers, sharing knowledge and supporting their growth