Job Title: Infrastructure Engineer (Cloud/MLOps)

Role Type: Full-time

Location: In-office

Compensation Range: 250,000 – 325,000 USD

About the Company

This organization is an AI-native platform purpose-built to eliminate legal drudgery. Every major business has an overworked in-house legal team—lawyers burning 80-hour weeks on contract-reading death marches. Until recently, technology offered little relief. Large language models changed that.

The company’s mission is to give these legal professionals their lives back. Since launching in early access in 2023, the platform has achieved the highest trial win rate in a competitive market (85%). Clients include Uber, Reddit, IBM, Canva, Pinterest, and WordPress. The company 6x’d ARR in the last 12 months and is scaling rapidly.

The Role: Why, What, and Who

Why this role exists

Infrastructure Engineers build the foundation for the entire platform. Clients are understandably protective of their contracts, so each customer receives an isolated environment with containers, databases, VPCs, and strict boundaries. Service disruptions occur. Cloud and LLM providers have incidents. Customers still expect service-level agreements to be met. This role exists to ensure that happens—reliably, securely, and at scale.

What the role owns

The company is seeking a Cloud/MLOps Engineer to join the Infrastructure team. Responsibilities include:

1. Owning and evolving the Kubernetes platform across AWS, GCP, and Azure
2. Designing and operating multi-cluster, multi-region architectures with failover and disaster recovery strategies that enforce secure cluster isolation boundaries
3. Building internal tooling for cluster provisioning and lifecycle management, standardizing environments from development through staging to production
4. Designing strategies to isolate machine learning workloads from API workloads while optimizing for cost, performance, and reliability
5. Implementing security and compliance controls at the platform layer using RBAC, workload identity, and secrets management—while preserving data isolation aligned with residency requirements and enterprise auditability
6. Partnering with Site Reliability Engineering and machine learning teams to ensure service-level objectives are realistic, enforceable, and that models deploy successfully into production environments

Who they are looking for

The ideal candidate brings:

1. Deep, hands-on production experience with Kubernetes (has debugged cluster issues at 2 a.m., not just deployed to them)
2. Strong experience with infrastructure as code using tools such as Pulumi or Terraform
3. Strong understanding of cluster architecture, scheduling, networking, storage primitives, and failure modes in distributed systems
4. Experience managing multi-cluster or multi-region setups with GitHub CI/CD

This is not a “keep the lights on” role. The person in this position will build the system that keeps the entire company running. Beyond running a solid, high-performance distributed system, the team is looking for someone genuinely excited about large language models. This engineer will be deeply embedded into the engineering organization and highly encouraged to push technical frontiers.

Who Thrives Here

The company might be the right fit for a candidate who:

1. Loves writing code but cares about impact more. This is a team of engineers at heart, but the number-one goal is building the best possible product—which means making pragmatic choices and finding 80/20 solutions.
2. Would describe themselves as relentlessly resourceful.
3. Has a strong internal sense of urgency and a bias toward doing things today rather than tomorrow.
4. Has experience working in a startup environment (preferred but not required).
5. Is genuinely excited about the adventure of building a company.

To Apply

Qualified candidates are encouraged to submit their resume along with a brief note describing a production Kubernetes failure they debugged and what they learned from the experience.