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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building production-ready ML infrastructure, focusing on secure execution environments, model routing, and orchestration. Proficient in developing scalable, fault-tolerant distributed systems and managing identity and authentication for agentic systems.
Highest-signal resume keywords
Production ML Infrastructure DevelopmentAgentic Systems ExperienceKubernetes ProficiencyCode Execution Sandboxes KnowledgeIdentity and Capability-Based Security
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Build the next generation of agentic AI infrastructure
- Develop secure execution environments for agent-generated code
- Design identity, authentication, and trust boundaries for agents
- Build model routing and orchestration across different model types and environments
- Implement rate limiting, quotas, and resource management for agent workflows
- Create state management, memory, and filesystem abstractions for agents
- Turn emerging ML research ideas into production-ready infrastructure
- Build core platform capabilities for execution, storage, and state management
- Prototype and evaluate new technologies and help decide what moves into production
- Partner with research teams to shape infrastructure for future agent systems
Requirements
What you’ll need- Experience building production ML infrastructure with strong systems fundamentals
- Hands-on work with agentic systems, multi-agent workflows, or agent development frameworks
- Familiarity with model routing and LLM provider frameworks across different model types and environments
- Experience with scalable, fault-tolerant distributed systems and Kubernetes
- Track record of moving quickly on prototypes and making good decisions about productionization
- Experience across on-prem, private cloud, and public cloud environments
- Familiarity with storage systems, embedded databases, or filesystem abstractions
- Experience with code execution sandboxes such as gVisor, Firecracker, Kata, or WASM runtimes
- Interest in emerging ML infrastructure, edge inference, or browser-native models
- Open-source contributions to LLM or agent infrastructure projects
- Experience with identity, workload auth, or capability-based security systems
- Must be authorized to work in the country currently residing in
Benefits
Comp & perks- A weekly lunch stipend of $75/£75 or equivalent in your local currency
- Full health and dental benefits, including a separate budget for mental health
- RRSP matching, 401K, Pension Scheme
- 100% Parental Leave top-up for up to 6 months, for either parent
- Annual enrichment benefits: arts & culture, fitness/wellness, quality time, and a workspace improvement credit
- Education & learning stipend for conferences, courses, and coaching
- 6 weeks of paid vacation (30 working days)
- Budget for traveling to other offices if you are remote
- Annual company offsite
- Daily lunch program, snacks, and regular community and social events for office-based employees
- Co-working benefit for employees not near an office
- $500 home office stipend
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Model RoutingMulti-Agent WorkflowsDistributed SystemsScalable Systems DesignFilesystem AbstractionsRate Limiting ImplementationResource ManagementState ManagementEmerging ML InfrastructurePrototyping and Productionization
Tools & Technologies
KubernetesGVisorFirecrackerKataWASM RuntimesEmbedded DatabasesStorage Systems
Industry Keywords
Agent Development FrameworksTrust BoundariesCloud EnvironmentsOpen-Source ContributionsWorkload Authentication