Director, Cloud Infrastructure

Convene Hospitality Group•New York, NY

4d•$180,000 - $220,000

About The Position

Convene Hospitality Group is hiring a hands-on Director of Cloud Infrastructure to join its Technology organization. This individual will lead through the platform, redesign deployment processes, and establish standards for product and corporate engineering teams. The role will run cloud, AI, and venue infrastructure across the company’s portfolio, spanning client-facing experiences and systems supporting nearly 40 venues. There are no direct reports currently, and the role offers significant autonomy and decision-making authority. AWS is the committed cloud platform; the director will select and implement many of the tools and patterns layered on top of it, then lead related legacy migrations. The director will rebuild the deployment path from manual releases to automated, safe, secure, and governed CI/CD. Responsibilities also include operating an AI gateway, enabling AI-first and spec-driven development, forecasting and managing cloud and AI costs, supporting applications used by venue networking teams, and building observability on the Loki/Grafana stack. The role will coordinate across product and corporate engineering and establish documentation, runbooks, and backup operators so critical systems do not depend on a single person. The position requires deep production cloud infrastructure experience, especially with AWS, infrastructure as code, CI/CD, security and governance, and production AI systems. The successful candidate sets direction, makes and documents platform decisions, owns migrations, collaborates with application and data teams, communicates trade-offs to technical and nontechnical audiences, and shares knowledge through review, pairing, and mentoring. Experience with MLOps is a plus.

Requirements

9+ years of experience building and running production cloud infrastructure.
Deep AWS experience, including multi-account structure, networking, IAM, and container orchestration on EKS and/or ECS.
Experience operating production workloads through incidents, upgrades, and growth.
Fluency in infrastructure as code, such as Terraform or equivalent, and a practice of making infrastructure changes reviewed, versioned, and reproducible.
Experience building or rebuilding CI/CD pipelines that teams use, including moving an organization from manual to automated deployments.
Treat security and governance as design inputs, including secrets, least privilege, audit trails, environment isolation, and deployment permissions.
Experience running AI systems in production, including gateway-layer access control, provider routing, cost attribution, observability, and LLM-backed features with evaluation, monitoring, and versioning.
Ability to model architecture costs before implementation, defend estimates, and adjust designs when needed.
High agency in setting direction, making consequential platform decisions, owning migrations, and documenting decisions.
Collaborative problem-solving skills for architecture, debugging, and trade-off analysis with application and data teams.
Ability to document runbooks, train backup operators, and deliberately hand off work.
Ability to communicate decisions, risks, and trade-offs clearly to technical and nontechnical audiences, including executives.
Experience using AI agents for real multi-step work beyond autocomplete and verifying their outputs.

Nice To Haves

MLOps experience.

Responsibilities

Own and rebuild CI/CD end to end, including build, release, and rollback, moving deployments from manual processes to an automated path.
Establish access controls, audit trails, secrets management, environment separation, and an executable rollback path.
Select, document, and migrate source control, CI tooling, orchestration, and infrastructure-as-code patterns.
Build and operate the AI gateway, including provider routing, key management, rate limits, token metering, and usage logging.
Build environments, pipelines, and guardrails for AI-first, spec-driven development, including ephemeral environments, fast feedback, and automated verification.
Forecast AI-system costs and provide Finance with planning estimates; monitor cloud spending and partner with teams to manage costs.
Provide the venue networking team with visibility to monitor and support applications used for access control, connectivity, and on-site A/V and production.
Build logging, metrics, alerting, and routing on the Loki/Grafana stack so failures reach a named owner.
Coordinate with product engineers and establish documented runbooks, backup operators, and knowledge sharing across product and corporate engineering.
Collaborate with application and data teams on architecture, debugging, and trade-off analysis.
Explain decisions, risks, and trade-offs to engineers, non-engineers, and executives; support teammate development through code review, pairing, and mentoring.
Use AI agents for multi-step work and verify their outputs against the real system.