Senior Engineer, Cloud Infrastructure

About the role

Code and Theory is seeking a senior cloud engineer to lead the technical lifecycle of enterprise client deployments. This role involves hands-on work with real clients, translating security and compliance requirements into concrete infrastructure decisions.

Responsibilities

• Assess each client's cloud infrastructure, data stack, and security perimeter before any build starts — translate findings into a concrete integration plan
• Design and provision client environments using Terraform — networking, IAM, container orchestration, managed storage, and secrets management across GCP, AWS, or Azure depending on the client
• Deploy and operate LLM inference pods in client cloud environments — managing API integration, rate limits, latency, and failure handling without needing a data scientist in the room
• Build and maintain integration layers that connect client data sources to the AI layer — you own the plumbing that makes inference useful; the data science team owns what runs on top of it
• Deploy and maintain containerized workloads via Helm — orchestration, ETL workers, and AI inference pods running inside the client's cloud perimeter
• Own data pipeline deployments end to end — scheduling, pagination, retry logic, and rate-limit management against client API gateways
• Manage distributed ETL jobs at scale — JSON flattening, schema enforcement, and structured output delivery
• Enforce data residency requirements — raw data stays inside the client's environment, only structured output leaves to our shared infrastructure
• Serve as the primary technical contact for each client's DevOps and infrastructure teams throughout the engagement
• Lead technical working sessions with client teams — validate configurations, confirm IAM and credential models, review cluster specs before deployment
• Triage and resolve pipeline and infrastructure failures across multiple client environments simultaneously
• Implement container security standards — non-root execution, read-only filesystems, startup integrity hashes, tamper protection
• Mentor junior and mid-level engineers and contribute implementation patterns to the shared playbook after every client engagement

Requirements

• 6+ years of cloud engineering experience — production experience on at least two of GCP, AWS, or Azure, and willing to operate across all three depending on client environment
• Deep Terraform experience — you have provisioned multi-environment, multi-tenant production infrastructure from scratch, not just applied existing configurations
• Comfortable with Kubernetes and Helm in production — deploying, debugging, scaling, and securing containerized workloads, not just running them
• Have run data pipelines in production — you know what breaks, how to recover, and how to build retry and backoff logic that actually holds up
• Hands-on experience with distributed processing at scale — not just theoretical knowledge
• Enterprise API integration experience — OAuth 2.0, API key management, rate limiting, API gateways — end to end
• Solid security fundamentals — container hardening, credential management, and data residency enforcement in environments where it actually matters
• Have worked directly with client or customer engineering teams — comfortable leading technical conversations with enterprise DevOps and infrastructure teams, not just supporting them
• You write things down — runbooks, integration notes, playbook contributions. The next engineer should be able to operate what you built
• Hands-on experience integrating LLM APIs (Anthropic, OpenAI, or equivalent) into production pipelines — not as an end user, but wiring inference into systems that run at scale across real client environments

Nice to have

• Experience with:
• LLM inference infrastructure
• Marketing technology stacks (DAM, CDP, CRM)
• Multi-tenant client environments

About us

Code and Theory is a digital-first creative agency that sits at the center of creativity and technology. We are looking for a senior cloud engineer to join our team. The target range of base compensation for this role is $110,000 - $150,000. Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, and location.