Infrastructure & IT Systems Engineer

Cellular Intelligence•Boston, MA

2d•Onsite

About The Position

Cellular Intelligence is seeking a hands-on Infrastructure & IT Systems Engineer to manage and enhance internal systems and automation critical for the company's research and operations. This role will evolve to encompass broader ownership of the engineering platform and infrastructure, including identity and access management, endpoint and SaaS systems, internal automation, AWS environment, research compute, CI/CD, production applications, and employee IT support. As an AI-first company, this role emphasizes automating routine operational tasks across IT and infrastructure, such as access workflows, endpoint management, and internal support, using AI-assisted systems, self-service, and robust documentation. The engineer will also handle complex exceptions that cannot be automated, working directly with research and operations teams. This is an owner-operator position, focused on simplifying and strengthening existing systems, with a structured handoff for AWS environment ownership over the first three to six months.

Requirements

3+ years owning internal IT systems, including identity and access, SaaS administration, endpoint management, automation, and user support.
Meaningful exposure to cloud infrastructure or DevOps work.
Demonstrated record of using AI and LLM tooling to eliminate or automate operational work.
Experience supporting and securing company endpoints using MDM, EDR, or comparable fleet-management tooling.
Practical scripting and automation skills, with the ability to troubleshoot and make small changes to existing tools; Python experience is preferred.
Linux fluency, including SSH, permissions, services, and diagnosis from logs.
Working familiarity with AWS services such as IAM, EC2, and S3.
Clear written communication for runbooks, policies, and documentation used by scientists and other non-specialists.

Nice To Haves

Deeper AWS experience, including VPC networking, and experience defining infrastructure as code with tools such as CloudFormation, CDK, or Terraform and shipping changes through code review.
Experience building production services or internal automation in Python.
Experience using large language models to build internal automation, including agent workflows, reusable skills, or MCP servers.
Experience with Google Workspace, Slack, GitHub, and modern identity or SSO platforms.
Experience with HPC schedulers such as Slurm or batch compute for GPU training jobs.
Prior ownership of a GDPR, SOC 2, ISO 27001, GxP, or comparable compliance program in a technical role.
Experience managing cloud costs at scale.
Prior experience in a startup or fast-paced, interdisciplinary environment.

Responsibilities

Own the internal IT systems, improving systems and automation for research and company operations by simplifying fragile processes, eliminating repetitive work, and creating reliable self-service.
Administer the SaaS estate, managing identity, email, collaboration, source-control, and other SaaS platforms with least-privilege access and reliable audit trails.
Manage the endpoint fleet, owning device security, inventory, and the provisioning lifecycle for Mac and Windows systems.
Run the AI-assisted IT support system, ensuring its integrations with identity, device-management, and SaaS platforms are functional, reviewing automated actions, and adding new automated resolutions.
Make onboarding and offboarding reliable by automating account, device, and access provisioning and deprovisioning, while remaining accountable for completion and exceptions.
Resolve user, access, connectivity, endpoint, office, and laboratory-computer issues when automation or self-service is insufficient.
Build durable processes for IT migrations, security awareness, equipment requests, and procurement handoffs.
Operate and improve the AWS environment, covering networking, identity and access, infrastructure as code, reliability, storage, backups, and cost management.
Own research compute, supporting GPU and Slurm workloads and shared Linux hosts.
Keep production services healthy by operating the infrastructure behind production applications and research services, improving observability, deployment safety, incident response, and recovery.
Improve engineering productivity by owning CI/CD, repository controls, internal web applications, and AI-enabled automation.
Run GDPR and SOC 2 day-to-day, maintaining policies, controls, and evidence for compliance.
Translate security guidance into technical controls across cloud infrastructure, internal applications, endpoints, research systems, and data handling.
Maintain the control set, including data retention, least-privilege access, audit logging, encryption, backups, incident response, and compliant data handling.
Coordinate recurring compliance work such as access reviews, policy updates, audit evidence, vendor-security requests, security awareness, and remediation of identified gaps.