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Location: London Workplace: Hybrid We are looking for an AI Infra engineer to join our growing team. We work with Kubernetes, Slurm, Python, C++, PyTorch, and primarily on AWS. As an AI Infrastructure Engineer, you will be partnering closely with our Inference and Research teams to build, deploy, and optimize our large-scale AI training and inference clusters. RESPONSIBILITIES - Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training workloads - Manage and optimize Slurm-based HPC environments for distributed training of large language models - Develop robust APIs and orchestration systems for both training pipelines and inference services - Implement resource scheduling and job management systems across heterogeneous compute environments - Benchmark system performance, diagnose bottlenecks, and implement improvements across both training and inference infrastructure - Build monitoring, alerting, and observability solutions tailored to ML workloads running on Kubernetes and Slurm - Respond swiftly to system outages and collaborate across teams to maintain high uptime for critical training runs and inference services - Optimize cluster utilization and implement autoscaling strategies for dynamic workload demands QUALIFICATIONS - Strong expertise in Kubernetes administration, including custom resource definitions, operators, and cluster management - Hands-on experience with Slurm workload management, including job scheduling, resource allocation, and cluster optimization - Experience with deploying and managing distributed training systems at scale - Deep understanding of container orchestration and distributed systems architecture - High level familiarity with LLM architecture and training processes (Multi-Head Attention, Multi/Grouped-Query, distributed training strategies) - Experience managing GPU clusters and optimizing compute resource utilization REQUIRED SKILLS - Expert-level Kubernetes administration and YAML configuration management - Proficiency with Slurm job scheduling, resource management, and cluster configuration - Python and C++ programming with focus on systems and infrastructure automation - Hands-on experience with ML frameworks such as PyTorch in distributed training contexts - Strong understanding of networking, storage, and compute resource management for ML workloads - Experience developing APIs and managing distributed systems for both batch and real-time workloads - Solid debugging and monitoring skills with expertise in observability tools for containerized environments PREFERRED SKILLS - Experience with Kubernetes operators and custom controllers for ML workloads - Advanced Slurm administration including multi-cluster federation and advanced scheduling policies - Familiarity with GPU cluster management and CUDA optimization - Experience with other ML frameworks like TensorFlow or distributed training libraries - Background in HPC environments, parallel computing, and high-performance networking - Knowledge of infrastructure as code (Terraform, Ansible) and GitOps practices - Experience with container registries, image optimization, and multi-stage builds for ML workloads REQUIRED EXPERIENCE - Demonstrated experience managing large-scale Kubernetes deployments in production environments - Proven track record with Slurm cluster administration and HPC workload management - Previous roles in SRE, DevOps, or Platform Engineering with focus on ML infrastructure - Experience supporting both long-running training jobs and high-availability inference services - Ideally, 3-5 years of relevant experience in ML systems deployment with specific focus on cluster orchestration and resource management

Location: London Workplace: Hybrid We are looking for an AI Infra engineer to join our growing team. We work with Kubernetes, Slurm, Python, C++, PyTorch, and primarily on AWS. As an AI Infrastructure Engineer, you will be partnering closely with our Inference and Research teams to build, deploy, and optimize our large-scale AI training and inference clusters. RESPONSIBILITIES - Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training workloads - Manage and optimize Slurm-based HPC environments for distributed training of large language models - Develop robust APIs and orchestration systems for both training pipelines and inference services - Implement resource scheduling and job management systems across heterogeneous compute environments - Benchmark system performance, diagnose bottlenecks, and implement improvements across both training and inference infrastructure - Build monitoring, alerting, and observability solutions tailored to ML workloads running on Kubernetes and Slurm - Respond swiftly to system outages and collaborate across teams to maintain high uptime for critical training runs and inference services - Optimize cluster utilization and implement autoscaling strategies for dynamic workload demands QUALIFICATIONS - Strong expertise in Kubernetes administration, including custom resource definitions, operators, and cluster management - Hands-on experience with Slurm workload management, including job scheduling, resource allocation, and cluster optimization - Experience with deploying and managing distributed training systems at scale - Deep understanding of container orchestration and distributed systems architecture - High level familiarity with LLM architecture and training processes (Multi-Head Attention, Multi/Grouped-Query, distributed training strategies) - Experience managing GPU clusters and optimizing compute resource utilization REQUIRED SKILLS - Expert-level Kubernetes administration and YAML configuration management - Proficiency with Slurm job scheduling, resource management, and cluster configuration - Python and C++ programming with focus on systems and infrastructure automation - Hands-on experience with ML frameworks such as PyTorch in distributed training contexts - Strong understanding of networking, storage, and compute resource management for ML workloads - Experience developing APIs and managing distributed systems for both batch and real-time workloads - Solid debugging and monitoring skills with expertise in observability tools for containerized environments PREFERRED SKILLS - Experience with Kubernetes operators and custom controllers for ML workloads - Advanced Slurm administration including multi-cluster federation and advanced scheduling policies - Familiarity with GPU cluster management and CUDA optimization - Experience with other ML frameworks like TensorFlow or distributed training libraries - Background in HPC environments, parallel computing, and high-performance networking - Knowledge of infrastructure as code (Terraform, Ansible) and GitOps practices - Experience with container registries, image optimization, and multi-stage builds for ML workloads REQUIRED EXPERIENCE - Demonstrated experience managing large-scale Kubernetes deployments in production environments - Proven track record with Slurm cluster administration and HPC workload management - Previous roles in SRE, DevOps, or Platform Engineering with focus on ML infrastructure - Experience supporting both long-running training jobs and high-availability inference services - Ideally, 3-5 years of relevant experience in ML systems deployment with specific focus on cluster orchestration and resource management

Location: San Francisco; Palo Alto; New York City We build and run the inference engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL - and we need another engineer to join us. WHAT YOU WILL WORK ON Examples of real work the team does: - New models support. Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading, request scheduling and KV-cache management to support in API Gateway. - GPU kernels migration to CuTe DSL. Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow. - Rust-native serving runtime. Develop our internal Rust-based inference server to solve all Python pains and keep up with rapidly growing traffic. - Performance optimisation. Profile and fix bottlenecks from network ingress through continuous batching and GPU kernel interleaving. - Reliability and observability. Build dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents. WHO WE'RE LOOKING FOR - Deep experience with GPU programming and performance work (CUDA, Triton, CUTLASS, or similar). Any other deep systems programming experience is a plus. - You understand modern LLM architectures and are able to bring them up reliably in a production environment. - You've built and operated production distributed systems under real load - ideally performance-critical ones. - Comfortable working across languages and layers: Rust for the serving runtime, Python for model code, CUDA/CuteDSL for kernels. - You own problems end-to-end. You can read a research paper on Monday, write a kernel on Wednesday, and debug a production incident on Friday. - Self-directed. You do well in fast-moving environments where the path forward isn't laid out for you. GOOD IF YOU TOUCHED ANY OF - ML compilers and framework internals: PyTorch internals, torch.compile, custom operators. - Distributed GPU communication: NCCL, NVLink, InfiniBand, RDMA libraries, model/tensor parallelism. - Low-precision inference: INT8/FP8/FP4 quantization, mixed-precision serving. - Profiling and debugging tools: Nsight Compute/Systems, CUDA-GDB, PTX/SASS analysis. - Container orchestration: Kubernetes, GPU scheduling, autoscaling inference workloads. QUALIFICATIONS - 3+ years of professional software engineering experience with meaningful work on ML inference or high-performance systems. - Familiarity with at least one deep learning framework (PyTorch, JAX, TensorFlow). - Understanding of GPU architectures (memory hierarchy, warp scheduling, tensor cores). - Understanding of common LLM architectures and inference optimization techniques (e.g. quantization, speculative decoding, prefill-decode disaggregation).

Location: San Francisco; Palo Alto; New York City We build and run the inference engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL - and we need another engineer to join us. WHAT YOU WILL WORK ON Examples of real work the team does: - New models support. Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading, request scheduling and KV-cache management to support in API Gateway. - GPU kernels migration to CuTe DSL. Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow. - Rust-native serving runtime. Develop our internal Rust-based inference server to solve all Python pains and keep up with rapidly growing traffic. - Performance optimisation. Profile and fix bottlenecks from network ingress through continuous batching and GPU kernel interleaving. - Reliability and observability. Build dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents. WHO WE'RE LOOKING FOR - Deep experience with GPU programming and performance work (CUDA, Triton, CUTLASS, or similar). Any other deep systems programming experience is a plus. - You understand modern LLM architectures and are able to bring them up reliably in a production environment. - You've built and operated production distributed systems under real load - ideally performance-critical ones. - Comfortable working across languages and layers: Rust for the serving runtime, Python for model code, CUDA/CuteDSL for kernels. - You own problems end-to-end. You can read a research paper on Monday, write a kernel on Wednesday, and debug a production incident on Friday. - Self-directed. You do well in fast-moving environments where the path forward isn't laid out for you. GOOD IF YOU TOUCHED ANY OF - ML compilers and framework internals: PyTorch internals, torch.compile, custom operators. - Distributed GPU communication: NCCL, NVLink, InfiniBand, RDMA libraries, model/tensor parallelism. - Low-precision inference: INT8/FP8/FP4 quantization, mixed-precision serving. - Profiling and debugging tools: Nsight Compute/Systems, CUDA-GDB, PTX/SASS analysis. - Container orchestration: Kubernetes, GPU scheduling, autoscaling inference workloads. QUALIFICATIONS - 3+ years of professional software engineering experience with meaningful work on ML inference or high-performance systems. - Familiarity with at least one deep learning framework (PyTorch, JAX, TensorFlow). - Understanding of GPU architectures (memory hierarchy, warp scheduling, tensor cores). - Understanding of common LLM architectures and inference optimization techniques (e.g. quantization, speculative decoding, prefill-decode disaggregation).

Location: London We are looking for an AI Inference Engineer to join our growing team. We build and run the inference engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL. RESPONSIBILITIES: - New models support. Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading, request scheduling and KV-cache management to support in API Gateway. - GPU kernels migration to CuTe DSL. Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow. - Rust-native serving runtime. Develop our internal Rust-based inference server to solve all Python pains and keep up with rapidly growing traffic. - Performance optimisation. Profile and fix bottlenecks from network ingress through continuous batching and GPU kernels interleaving. - Reliability and observability. Build dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents. WHO WE'RE LOOKING FOR: - Deep experience with GPU programming and performance work (CUDA, Triton, CUTLASS, or similar). Any other deep systems programming experience is a plus. - You understand modern LLM architectures and are able to bring them up reliably in a production environment. - You've built and operated production distributed systems under real load - ideally performance-critical ones. - Comfortable working across languages and layers: Rust for the serving runtime, Python for model code, CUDA/CuteDSL for kernels. - You own problems end-to-end. You can read a research paper on Monday, write a kernel on Wednesday, and debug a production incident on Friday. - Self-directed. You do well in fast-moving environments where the path forward isn't laid out for you. NICE-TO-HAVE: - ML compilers and framework internals: PyTorch internals, torch.compile, custom operators. - Distributed GPU communication: NCCL, NVLink, InfiniBand, RDMA libraries, model/tensor parallelism. - Low-precision inference: INT8/FP8/FP4 quantization, mixed-precision serving. - Profiling and debugging tools: Nsight Compute/Systems, CUDA-GDB, PTX/SASS analysis. - Container orchestration: Kubernetes, GPU scheduling, autoscaling inference workloads. QUALIFICATIONS: - 3+ years of professional software engineering experience with meaningful work on ML inference or high-performance systems. - Familiarity with at least one deep learning framework (PyTorch, JAX, TensorFlow). - Understanding of GPU architectures (memory hierarchy, warp scheduling, tensor cores). - Understanding of common LLM architectures and inference optimization techniques (e.g. quantization, speculative decoding, prefill-decode disaggregation). Final offer amounts are determined by multiple factors including experience and expertise. Equity: In addition to the base salary, equity may be part of the total compensation package.

Location: London We are looking for an AI Inference Engineer to join our growing team. We build and run the inference engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL. RESPONSIBILITIES: - New models support. Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading, request scheduling and KV-cache management to support in API Gateway. - GPU kernels migration to CuTe DSL. Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow. - Rust-native serving runtime. Develop our internal Rust-based inference server to solve all Python pains and keep up with rapidly growing traffic. - Performance optimisation. Profile and fix bottlenecks from network ingress through continuous batching and GPU kernels interleaving. - Reliability and observability. Build dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents. WHO WE'RE LOOKING FOR: - Deep experience with GPU programming and performance work (CUDA, Triton, CUTLASS, or similar). Any other deep systems programming experience is a plus. - You understand modern LLM architectures and are able to bring them up reliably in a production environment. - You've built and operated production distributed systems under real load - ideally performance-critical ones. - Comfortable working across languages and layers: Rust for the serving runtime, Python for model code, CUDA/CuteDSL for kernels. - You own problems end-to-end. You can read a research paper on Monday, write a kernel on Wednesday, and debug a production incident on Friday. - Self-directed. You do well in fast-moving environments where the path forward isn't laid out for you. NICE-TO-HAVE: - ML compilers and framework internals: PyTorch internals, torch.compile, custom operators. - Distributed GPU communication: NCCL, NVLink, InfiniBand, RDMA libraries, model/tensor parallelism. - Low-precision inference: INT8/FP8/FP4 quantization, mixed-precision serving. - Profiling and debugging tools: Nsight Compute/Systems, CUDA-GDB, PTX/SASS analysis. - Container orchestration: Kubernetes, GPU scheduling, autoscaling inference workloads. QUALIFICATIONS: - 3+ years of professional software engineering experience with meaningful work on ML inference or high-performance systems. - Familiarity with at least one deep learning framework (PyTorch, JAX, TensorFlow). - Understanding of GPU architectures (memory hierarchy, warp scheduling, tensor cores). - Understanding of common LLM architectures and inference optimization techniques (e.g. quantization, speculative decoding, prefill-decode disaggregation). Final offer amounts are determined by multiple factors including experience and expertise. Equity: In addition to the base salary, equity may be part of the total compensation package.

Location: Lanham, MD OR RN II Position Objective: The Registered Nurse in surgery provides expert, professional nursing care to patients during the perioperative course. The RN assesses, plans, implements, and evaluates the care of patients throughout surgical intervention. The RN in surgery will supervise Operating Room Technicians and ancillary personnel. The primary responsibility of the RN will be to perform the duties of a circulator in the Operating Room. The RN may also be competent in the role of a scrub nurse and perform the duties of that role, as staffing requires. Job Responsibilities: Clinical Decision-Making / Judgment The nurse applies expert clinical knowledge to ensure safe and effective perioperative care. Responsibilities include: Assessing, planning, implementing, and evaluating patient care throughout the surgical experience. Performing comprehensive preoperative assessments, including verification of the procedure, operative site, allergies, and risk factors. Applying the nursing process effectively with attention to patient safety, sterile technique, and evidence-based standards. Organizing and reprioritizing patient care based on clinical changes and environmental factors. Monitoring patients intraoperatively, including EKG, vital signs, and sedation levels, and responding promptly to emergent situations such as codes or airway compromise. Administering medications, managing pain, and performing unit-specific technical skills (e.g., moderate sedation, hemodynamic monitoring). Ensuring aseptic technique, accurate sponge and needle counts, and specimen handling per protocol. Preparing and positioning patients safely for procedures. Nurse–Patient Family Relationships The nurse fosters therapeutic relationships with patients and families to promote trust, comfort, and learning. Responsibilities include: Introducing self and role to the patient and family in the preoperative area, assuring the patient of nursing presence throughout the procedure. Demonstrating compassion, professionalism, and cultural sensitivity in all interactions. Assessing patient and family learning needs, readiness, and potential barriers to understanding. Developing and implementing individualized teaching plans that address physical, psychosocial, spiritual, and educational needs. Providing thorough and accurate handoff reports to PACU staff to ensure continuity of care. Clinical Scholarship The nurse maintains professional competence and contributes to quality initiatives to improve patient outcomes. Responsibilities include: Meeting all continuing education requirements and remaining current with evolving health care practices. Participating in unit and organizational quality improvement, clinical practice improvement, and risk management activities. Supporting evidence-based practice by adhering to organizational policies, standards, and benchmarks. Updating and maintaining accuracy of surgeon preference cards to enhance efficiency and safety. Clinical Leadership The nurse contributes to team effectiveness through guidance, mentorship, and shared decision-making. Responsibilities include: Supervising Operating Room Technicians and ancillary personnel to ensure quality care delivery. Delegating tasks appropriately and evaluating delegated activities for patient outcomes. Educating, orienting, and mentoring new staff members within the department. Actively participating in shared governance and contributing to departmental decision-making. Utilizing real-time electronic documentation to maintain accurate patient records. Communicating effectively with surgical, anesthesia, and leadership teams regarding patient care and equipment needs. Professional Practice & Teamwork Some responsibilities extend beyond direct patient care and fit best within a broader domain of professional practice. These include: Assisting anesthesia personnel with supply and medication readiness, induction, and procedural support. Supporting patient transport to and from the operating room. Assisting with securing dressings, transferring patients post-procedure, and supporting recovery. Participating in room turnover, cleaning, and restocking of instruments and supplies. Offering assistance to other operating rooms and departments as time and need allow. Keeping leadership informed about equipment repairs or supply needs. Representing the hospital and surgical services professionally both at work and within the community. Educational/Experience Requirements: • Graduate of an accredited school of nursing BSN • Adherence to the credentialing requirements of Luminis Health as stated in the nursing bylaws. • Minimum 2 years of operating room experience Required License/Certifications: • Current licensure as a registered nurse by the Maryland Board of Nursing • BLS, ACLS- American Heart Association Health Provider • Certification preferred Working Conditions, Equipment, Physical Demands: Employees in this position may be exposed to blood-borne pathogens. The role requires sustained concentration on moderate to fine details and the ability to lift and carry items up to 50 pounds. Candidates must be able to hear normal sounds, even with background noise, and maintain attention to schedules, tasks, and ongoing activities. The position involves prolonged periods of sitting, standing, and walking. Staff must be able to conceptualize and carry out tasks effectively and adhere to radiation safety precautions, with protective equipment provided. Work is primarily on the day shift with rotating on-call responsibilities, including nights, weekends, and holidays. The above job description is an overview of the functions and requirements for this position. This document is not intended to be an exhaustive list encompassing every duty and requirement of this position; your supervisor may assign other duties as deemed necessary. Pay Range $39 — $60 USD Luminis Health Benefits Overview: •    Medical, Dental, and Vision Insurance •    Retirement Plan (with employer match for employees who work more than 1000 hours in a calendar year) •    Paid Time Off •    Tuition Assistance Benefits •    Employee Referral Bonus Program •    Paid Holidays, Disability, and Life/AD&D for full-time employees •    Wellness Programs •    Employee Assistance Programs and more *Benefit offerings based on employment status Opt-in for text notifications! Luminis Health's two-way SMS texting platform lets you receive notifications and messages from our Talent Acquisition team directly on your phone. To enable this feature, select "yes" when asked to "opt-in to receive text messages" and to "Receive updates from a recruiter about this job via SMS" when completing your application. Once you are opted in, you can easily opt-out at any time. Standard text messaging rates may apply based on the candidate's mobile carrier plan. Luminis Health is not responsible for any charges incurred by the recipient. Candidates are encouraged to review their mobile carrier's plan for applicable text messaging rates and usage charges.

Location: Lanham, MD OR RN II Position Objective: The Registered Nurse in surgery provides expert, professional nursing care to patients during the perioperative course. The RN assesses, plans, implements, and evaluates the care of patients throughout surgical intervention. The RN in surgery will supervise Operating Room Technicians and ancillary personnel. The primary responsibility of the RN will be to perform the duties of a circulator in the Operating Room. The RN may also be competent in the role of a scrub nurse and perform the duties of that role, as staffing requires. Job Responsibilities: Clinical Decision-Making / Judgment The nurse applies expert clinical knowledge to ensure safe and effective perioperative care. Responsibilities include: Assessing, planning, implementing, and evaluating patient care throughout the surgical experience. Performing comprehensive preoperative assessments, including verification of the procedure, operative site, allergies, and risk factors. Applying the nursing process effectively with attention to patient safety, sterile technique, and evidence-based standards. Organizing and reprioritizing patient care based on clinical changes and environmental factors. Monitoring patients intraoperatively, including EKG, vital signs, and sedation levels, and responding promptly to emergent situations such as codes or airway compromise. Administering medications, managing pain, and performing unit-specific technical skills (e.g., moderate sedation, hemodynamic monitoring). Ensuring aseptic technique, accurate sponge and needle counts, and specimen handling per protocol. Preparing and positioning patients safely for procedures. Nurse–Patient Family Relationships The nurse fosters therapeutic relationships with patients and families to promote trust, comfort, and learning. Responsibilities include: Introducing self and role to the patient and family in the preoperative area, assuring the patient of nursing presence throughout the procedure. Demonstrating compassion, professionalism, and cultural sensitivity in all interactions. Assessing patient and family learning needs, readiness, and potential barriers to understanding. Developing and implementing individualized teaching plans that address physical, psychosocial, spiritual, and educational needs. Providing thorough and accurate handoff reports to PACU staff to ensure continuity of care. Clinical Scholarship The nurse maintains professional competence and contributes to quality initiatives to improve patient outcomes. Responsibilities include: Meeting all continuing education requirements and remaining current with evolving health care practices. Participating in unit and organizational quality improvement, clinical practice improvement, and risk management activities. Supporting evidence-based practice by adhering to organizational policies, standards, and benchmarks. Updating and maintaining accuracy of surgeon preference cards to enhance efficiency and safety. Clinical Leadership The nurse contributes to team effectiveness through guidance, mentorship, and shared decision-making. Responsibilities include: Supervising Operating Room Technicians and ancillary personnel to ensure quality care delivery. Delegating tasks appropriately and evaluating delegated activities for patient outcomes. Educating, orienting, and mentoring new staff members within the department. Actively participating in shared governance and contributing to departmental decision-making. Utilizing real-time electronic documentation to maintain accurate patient records. Communicating effectively with surgical, anesthesia, and leadership teams regarding patient care and equipment needs. Professional Practice & Teamwork Some responsibilities extend beyond direct patient care and fit best within a broader domain of professional practice. These include: Assisting anesthesia personnel with supply and medication readiness, induction, and procedural support. Supporting patient transport to and from the operating room. Assisting with securing dressings, transferring patients post-procedure, and supporting recovery. Participating in room turnover, cleaning, and restocking of instruments and supplies. Offering assistance to other operating rooms and departments as time and need allow. Keeping leadership informed about equipment repairs or supply needs. Representing the hospital and surgical services professionally both at work and within the community. Educational/Experience Requirements: • Graduate of an accredited school of nursing BSN • Adherence to the credentialing requirements of Luminis Health as stated in the nursing bylaws. • Minimum 2 years of operating room experience Required License/Certifications: • Current licensure as a registered nurse by the Maryland Board of Nursing • BLS, ACLS- American Heart Association Health Provider • Certification preferred Working Conditions, Equipment, Physical Demands: Employees in this position may be exposed to blood-borne pathogens. The role requires sustained concentration on moderate to fine details and the ability to lift and carry items up to 50 pounds. Candidates must be able to hear normal sounds, even with background noise, and maintain attention to schedules, tasks, and ongoing activities. The position involves prolonged periods of sitting, standing, and walking. Staff must be able to conceptualize and carry out tasks effectively and adhere to radiation safety precautions, with protective equipment provided. Work is primarily on the day shift with rotating on-call responsibilities, including nights, weekends, and holidays. The above job description is an overview of the functions and requirements for this position. This document is not intended to be an exhaustive list encompassing every duty and requirement of this position; your supervisor may assign other duties as deemed necessary. Pay Range $39 — $60 USD Luminis Health Benefits Overview: •    Medical, Dental, and Vision Insurance •    Retirement Plan (with employer match for employees who work more than 1000 hours in a calendar year) •    Paid Time Off •    Tuition Assistance Benefits •    Employee Referral Bonus Program •    Paid Holidays, Disability, and Life/AD&D for full-time employees •    Wellness Programs •    Employee Assistance Programs and more *Benefit offerings based on employment status Opt-in for text notifications! Luminis Health's two-way SMS texting platform lets you receive notifications and messages from our Talent Acquisition team directly on your phone. To enable this feature, select "yes" when asked to "opt-in to receive text messages" and to "Receive updates from a recruiter about this job via SMS" when completing your application. Once you are opted in, you can easily opt-out at any time. Standard text messaging rates may apply based on the candidate's mobile carrier plan. Luminis Health is not responsible for any charges incurred by the recipient. Candidates are encouraged to review their mobile carrier's plan for applicable text messaging rates and usage charges.

Location: Lanham, MD OR RN II Position Objective: The Registered Nurse in surgery provides expert, professional nursing care to patients during the perioperative course. The RN assesses, plans, implements, and evaluates the care of patients throughout surgical intervention. The RN in surgery will supervise Operating Room Technicians and ancillary personnel. The primary responsibility of the RN will be to perform the duties of a circulator in the Operating Room. The RN may also be competent in the role of a scrub nurse and perform the duties of that role, as staffing requires. Job Responsibilities: Clinical Decision-Making / Judgment The nurse applies expert clinical knowledge to ensure safe and effective perioperative care. Responsibilities include: Assessing, planning, implementing, and evaluating patient care throughout the surgical experience. Performing comprehensive preoperative assessments, including verification of the procedure, operative site, allergies, and risk factors. Applying the nursing process effectively with attention to patient safety, sterile technique, and evidence-based standards. Organizing and reprioritizing patient care based on clinical changes and environmental factors. Monitoring patients intraoperatively, including EKG, vital signs, and sedation levels, and responding promptly to emergent situations such as codes or airway compromise. Administering medications, managing pain, and performing unit-specific technical skills (e.g., moderate sedation, hemodynamic monitoring). Ensuring aseptic technique, accurate sponge and needle counts, and specimen handling per protocol. Preparing and positioning patients safely for procedures. Nurse–Patient Family Relationships The nurse fosters therapeutic relationships with patients and families to promote trust, comfort, and learning. Responsibilities include: Introducing self and role to the patient and family in the preoperative area, assuring the patient of nursing presence throughout the procedure. Demonstrating compassion, professionalism, and cultural sensitivity in all interactions. Assessing patient and family learning needs, readiness, and potential barriers to understanding. Developing and implementing individualized teaching plans that address physical, psychosocial, spiritual, and educational needs. Providing thorough and accurate handoff reports to PACU staff to ensure continuity of care. Clinical Scholarship The nurse maintains professional competence and contributes to quality initiatives to improve patient outcomes. Responsibilities include: Meeting all continuing education requirements and remaining current with evolving health care practices. Participating in unit and organizational quality improvement, clinical practice improvement, and risk management activities. Supporting evidence-based practice by adhering to organizational policies, standards, and benchmarks. Updating and maintaining accuracy of surgeon preference cards to enhance efficiency and safety. Clinical Leadership The nurse contributes to team effectiveness through guidance, mentorship, and shared decision-making. Responsibilities include: Supervising Operating Room Technicians and ancillary personnel to ensure quality care delivery. Delegating tasks appropriately and evaluating delegated activities for patient outcomes. Educating, orienting, and mentoring new staff members within the department. Actively participating in shared governance and contributing to departmental decision-making. Utilizing real-time electronic documentation to maintain accurate patient records. Communicating effectively with surgical, anesthesia, and leadership teams regarding patient care and equipment needs. Professional Practice & Teamwork Some responsibilities extend beyond direct patient care and fit best within a broader domain of professional practice. These include: Assisting anesthesia personnel with supply and medication readiness, induction, and procedural support. Supporting patient transport to and from the operating room. Assisting with securing dressings, transferring patients post-procedure, and supporting recovery. Participating in room turnover, cleaning, and restocking of instruments and supplies. Offering assistance to other operating rooms and departments as time and need allow. Keeping leadership informed about equipment repairs or supply needs. Representing the hospital and surgical services professionally both at work and within the community. Educational/Experience Requirements: • Graduate of an accredited school of nursing BSN • Adherence to the credentialing requirements of Luminis Health as stated in the nursing bylaws. • Minimum 2 years of operating room experience Required License/Certifications: • Current licensure as a registered nurse by the Maryland Board of Nursing • BLS, ACLS- American Heart Association Health Provider • Certification preferred Working Conditions, Equipment, Physical Demands: Employees in this position may be exposed to blood-borne pathogens. The role requires sustained concentration on moderate to fine details and the ability to lift and carry items up to 50 pounds. Candidates must be able to hear normal sounds, even with background noise, and maintain attention to schedules, tasks, and ongoing activities. The position involves prolonged periods of sitting, standing, and walking. Staff must be able to conceptualize and carry out tasks effectively and adhere to radiation safety precautions, with protective equipment provided. Work is primarily on the day shift with rotating on-call responsibilities, including nights, weekends, and holidays. The above job description is an overview of the functions and requirements for this position. This document is not intended to be an exhaustive list encompassing every duty and requirement of this position; your supervisor may assign other duties as deemed necessary. Pay Range $39 — $60 USD Luminis Health Benefits Overview: •    Medical, Dental, and Vision Insurance •    Retirement Plan (with employer match for employees who work more than 1000 hours in a calendar year) •    Paid Time Off •    Tuition Assistance Benefits •    Employee Referral Bonus Program •    Paid Holidays, Disability, and Life/AD&D for full-time employees •    Wellness Programs •    Employee Assistance Programs and more *Benefit offerings based on employment status Opt-in for text notifications! Luminis Health's two-way SMS texting platform lets you receive notifications and messages from our Talent Acquisition team directly on your phone. To enable this feature, select "yes" when asked to "opt-in to receive text messages" and to "Receive updates from a recruiter about this job via SMS" when completing your application. Once you are opted in, you can easily opt-out at any time. Standard text messaging rates may apply based on the candidate's mobile carrier plan. Luminis Health is not responsible for any charges incurred by the recipient. Candidates are encouraged to review their mobile carrier's plan for applicable text messaging rates and usage charges.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic’s Product Engineering org is looking for experienced engineers with strong full-stack fundamentals to join one of teams owning our current or emergent products. You'll be a technical leader who thinks holistically about the consumer and/or enterprise end user experience - be that via Claude.ai , the Anthropic API, enterprise deployments, Claude Code, or mission-driven applications - and carry real end-to-end ownership. You'll partner with engineering managers, product leaders, designers, and researchers to understand new model capabilities and redefine what is possible for users in the world of LLMs - and how to build it. We’ll look to you to have a product-oriented mindset and input, own technical quality across the stack (performance, accessibility, reliability, and developer experience), scale your efforts to millions of users on a global scale, and carry genuine excitement about what AI makes possible. We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the backend product efforts where they'll have the greatest impact and growth potential. What you'll do: Platform Ecosystem: The Ecosystem team is empowering the next big industries beyond coding to build on our platform & creating the right commercial rails to let any business in our ecosystem profit from building on Claude. As an early member of this foundational effort, you'd identify and build for the next 10x markets starting with Life Sciences and Healthcare. We also build the commercial rails and controls that let the platform do business anywhere, with anyone, and turn Claude from a cost line into a revenue line. Beneficial Deployments: Beneficial Deployments Engineering brings Claude to organizations doing the most good with the fewest resources — nonprofits, schools, healthcare providers, researchers, and economic mobility programs.We're looking for a full-stack engineer to build the access programs, tooling, and product work that make frontier AI usable for teams that couldn't afford this capacity any other way. Vertical AI Products: Purpose-built experiences for specific industries where Claude can transform complex professional work. We're currently building for three verticals, with more to come: Life Sciences — an agentic research platform for scientists: specialist agents for computational biology, literature review, and regulatory review, built on model capabilities we're investing in for biology and chemistry. Live with early customers and expanding fast. Enterprise AI Products: You'll work on the products that make Claude a daily-use tool for enterprise customers across industries – the connective tissue that lets Claude operate effectively across workflows. On this team you will systematically understand why Enterprise users aren't activating, what's blocking adoption, and building the capabilities to close those gaps.Some of our focuses are: Extensibility — plugins, skills, connectors, and the MCP ecosystem that lets a company shape Claude around their specific workflows and distribute that work across teams. Context — enterprise knowledge, organizational memory, and the retrieval layer that makes Claude genuinely aware of a company's people, documents, and workflows. A connected, contextual Claude is the difference between a general-purpose chatbot and a real coworker. Proactivity — Cowork suggestions, workflow capture, ambient Claude inside the apps people already use. Moving from "Claude answers when asked" to "Claude notices what you need". Public Sector: Build products that deliver Claude to the U.S. federal & state governments and allied democracies — from FedRAMP environments to classified networks. We're a startup-minded team with huge surface area: we own Claude for Government, ship zero-to-one products into the most regulated environments in the world, and work directly with the agencies using them Enterprise Foundations: You'll build the systems large organizations require before they can adopt Claude at scale: identity and permissions, security and compliance controls, and the admin analytics that let them see how it's being used. This is the work that turns "we love the demo" into a signed enterprise deal.The role is part product, part platform. You'll work closely with Product and GTM to understand what our largest customers need, then build it once in a way that works across Claude.ai, Claude Code, and Cowork. Growth: Drive user acquisition, engagement, retention, and monetization through data-driven strategies and technical implementations. At Anthropic, we're not just building AI tools; we're reimagining how AI can enhance and expand its user base! As a member of the growth team, you will have a unique opportunity to shape our growth strategy. You will work with a cross-functional team of engineers, data scientists, marketers, and product managers to design, implement, and optimize growth initiatives that scale our AI-powered tools and maximize their impact. You might be a good fit if you: Have a minimum of 8 years of practical full-stack engineering experience, ideally with 2+ years operating at a Staff or equivalent technical leadership level Have led the design and delivery of complex, consumer or B2B user-facing products across the full stack Are a technical expert in modern frontend and backend development, with demonstrated depth in key languages and frameworks (ie. React, Typescript) Take a product-focused approach to building solutions that are robust, scalable, and easy to use Have worked in early start-up or otherwise fast moving, rapidly evolving environments, and have ideally built products from 0 to 1 Care deeply in investing in the mentorship and growth of your peers Have successfully driven cross-team/cross-org organizational alignment to get impactful work shipped, and work with influence over authority Have experience establishing engineering standards, component architectures, and development best practices Thrive in fast-paced environments and can navigate ambiguity to deliver high-quality products Deadline to apply: None. Applications will be reviewed on a rolling basis. Location Preference: Preference will be given to candidates based in NY, NJ, SEA, SF or the Bay Area given the current location of team. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: Anthropic is looking for experienced, product-minded engineers to own the backend systems that power user experiences across our API, Claude Code, and Claude.ai. You'll independently scope complex, multi-month projects through ambiguous problem spaces and lead peers through technical and product decisions; you'll drive alignment with product, peer engineering teams, and research to identify capability gaps and translate frontier model improvements into shipped products. You'll make architectural decisions that affect the reliability and scalability of systems serving hundreds of thousands of global users (including internal teams), and design processes that help your team operate effectively and never fail the same way twice - all while staying hands-on with the code and our models. We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the backend product efforts where they'll have the greatest impact and growth potential: Platform Intelligence: You'll build and scale the foundation of the Claude API—the systems that deliver Claude's intelligence to every developer, from startups to enterprise. You'll own the performance, reliability, and efficiency of our core serving path, ensuring users get the most speed and value from our models. You'll partner closely with inference and safeguards to optimize the full stack. Platform Ecosystem: The Ecosystem team is empowering the next big industries beyond coding to build on our platform & creating the right commercial rails to let any business in our ecosystem profit from building on Claude. As an early member of this foundational effort, you'd identify and build for the next 10x markets starting with Life Sciences and Healthcare. We also build the commercial rails and controls that let the platform do business anywhere, with anyone, and turn Claude from a cost line into a revenue line. We are hiring founding engineers for these two pillars. We are looking for engineers who have good product and business sense to drive strategy, dive into different stacks, and break through walls to drive these 0 -> 1 efforts. You'll be working closely with product, design, GTM, FDE, and other internal & external customers to build out and deliver on the strategy. Platform Serving: You'll focus on transforming Claude into a true knowledge worker by ensuring the model has access to and understanding of the right knowledge at the right time. You'll work on making it possible for developers to securely give Claude access to their data while automatically processing and retrieving relevant information. You'll partner directly with research to bring state-of-the-art retrieval advancements to developers. Developer Experience: You’ll focus on building products and tools to enable developers to harness the full power of LLMs to create successful, reliable, and groundbreaking applications with ease. You’ll build the tools to accelerate developers from idea to deployment. You'll help figure out how to leverage Claude to improve developer's usage of the API, such as generating and evaluating prompts while collaborating closely with the teams above to bring Claude's current and future capabilities to developers. Agentic Systems: You'll build the infrastructure and APIs that let developers create powerful agentic applications on the Claude API — including Claude Managed Agents, our managed platform for deploying and running agents in production. Your work spans the primitives agent developers depend on: tool use, multi-step reasoning, durable sessions and environments, and long-running task execution that lets Claude take actions and accomplish complex goals on a user's behalf. You'll make this platform ready for the largest enterprises to adopt, and partner with research to bring cutting-edge agent capabilities into production. Auth & Identity: We build and maintain the critical infrastructure and control interfaces that power identity and authentication across Anthropic's product suite. We work closely with product teams, security, support, and trust & safety as customers. We create scalable solutions for user authentication, authorization, role-based access control, and single sign-on that form the backbone of our company's identity management operations. We maintain a user-centric approach, building reliable systems that our users and company can depend on as we tackle complex challenges at the intersection of security, scalability, and user experience. Platform Distribution: The Claude API today is a rapidly growing platform serving developers and enterprises at scale—but reaching the next tier of enterprise customers requires transforming how and where we deploy it. The Distributability team owns that transformation: making the Claude API a cloud-native, managed product that runs wherever our customers need it, cross-cloud and on Anthropic's own infrastructure, with the enterprise-grade security, compliance, and operational capabilities to support it. Enterprise Foundations: We're looking for a software engineer to join our Enterprise Foundations team—the team that makes Claude enterprise-ready at scale. When a Fortune 500 company wants to roll out Claude to 100,000 employees, we're the team that makes it possible.You'll build the foundational systems that large organizations require before they can deploy AI at scale: user and permissions management, security and compliance features, and analytics infrastructure. This work directly converts product-market fit into revenue by removing the deployment blockers that prevent large organizations from adopting Claude broadly. Platform Safety: We're building the identity and verification product layer that enables safe model launches as Claude's capabilities expand. This critical effort partners with Safeguards, Auth & Identity, Policy, and Product teams across API, Claude.ai , and third-party platforms as customers, creating the systems for KYC/KYB, trust grant issuance and inheritance, and end-user verification that flow across every Anthropic surface. We sit at the intersection of trust, compliance, and product velocity, delivering the verification primitives that let Anthropic ship advanced model capabilities to the right users at massive scale. You Might Be a Good Fit If You: Have 8+ years of relevant experience as a backend or product engineer, with a track record of leading complex, multi-month projects or teams as a tech lead or equivalent Have strong coding fundamentals and are comfortable working across backend systems, APIs, and integrations — and can reach into the frontend when needed to ship an effective solution Have led the design and delivery of large-scale backend systems in production that power high-adoption B2B or consumer facing products Are skilled at driving alignment across technical and non-technical teams; you communicate clearly, influence technical decisions beyond your immediate team, and help others ramp effectively on your systems Take a product-focused approach to your work work and care about building solutions that are robust, scalable, and easy to use Care deeply about investing in the mentorship and growth of your peers Have experience with distributed systems, API design, and cloud infrastructure at scale Thrive in fast-paced environments and can navigate ambiguity to find the highest-leverage path forward The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: We are looking for experienced software engineers to join our Platform organization. We build the foundational primitives that accelerate product development across Anthropic, and own infrastructure and systems that teams depend on to ship reliably and at scale - either internally or by hundreds of thousands of external global users and companies at all stages. You'll independently scope complex, multi-month projects, drive cross-org alignment through ambiguous problem spaces, and make architectural decisions that shape how Anthropic builds and scales its products. You'll partner directly with research to productize cutting-edge capabilities, and will have lasting impact on the platform that hundreds of thousands of companies and internal/external engineers depend on every day. We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the backend product efforts where they'll have the greatest impact and growth potential. You might be a good fit if you: Have a minimum of 8 years of practical experience as a backend or platform engineer building scalable distributed systems, ideally operating at tech lead level or equivalent distributed systems, cloud-native products, developer tools, or external developer facing products Have strong fundamentals in service-oriented architectures, networking, and systems design, ideally having owned both the technical vision and execution of a foundational platform system end to end Are proficient in Python, Go, Rust, or similar systems languages Have experience with cloud infrastructure (GCP, AWS, or Azure), container orchestration (Kubernetes), and/or multi-cloud networking Take full ownership of your work—from design through deployment and operations Can navigate ambiguity and make sound technical decisions independently, and have ideally operated in 0 to 1 and more mature team or company settings Take a product-focused approach to platform work and care about building solutions that are robust, scalable, and easy to use Care about building systems that other engineers love to use Deadline to apply: None. Applications will be reviewed on a rolling basis. Location Preference: Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of team. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Espoo; Berlin Workplace: Hybrid - Title: Staff Platform Engineer - Department: Platform & Release Engineering - Location: Espoo, Finland / Berlin, Germany - Reports to: Infrastructure Engineering Lead - Employment type: Permanent - Workplace model: Hybrid - Employment is subject to applicable security screening (incl. SUPO) WHY THIS ROLE MATTERS: As a Senior / Staff Platform Engineer, you’ll own and evolve the foundations that all services rely on, leading the design and operation of a secure, scalable Kubernetes platform across cloud and on-prem environments so product teams can ship faster with less friction and stronger reliability at scale. WHO WE ARE ICEYE delivers space-based intelligence, surveillance, and reconnaissance (ISR) capabilities to governments and allied nations. This includes sovereign and turnkey ISR missions leveraging ICEYE’s world-leading synthetic aperture radar (SAR) satellite technology, as well as access to data from the world’s largest SAR satellite constellation. These capabilities enable partners to detect and respond to critical changes anywhere on Earth with unprecedented speed and accuracy, day or night and in any weather, supported by ultra high-resolution imagery and high-frequency revisits. As a trusted partner for defense, intelligence, security, and maritime domain awareness, ICEYE’s near real-time data creates a tactical advantage for mission-critical operations. Designed for dual use, the platform also serves civil protection and commercial users for natural-catastrophe intelligence, insurance, maritime monitoring including oil-spill detection, and finance, contributing to global security and community resilience. ICEYE is headquartered in Finland and operates globally across Europe, North America, the Middle East, and Asia-Pacific. We have more than 900 employees, united by a shared vision: improving life on Earth by becoming the global source of truth in Earth Observation. YOUR DAY-TO-DAY RESPONSIBILITIES - Design, operate, and continuously improve a secure, scalable, and resilient Kubernetes platform across cloud and on-prem environments - Build and maintain standardized platform capabilities such as ingress, service mesh, secrets management, and lifecycle automation - Develop reusable infrastructure patterns and Terraform modules for AWS and on-prem platforms to enable fast, auditable provisioning - Strengthen observability through clear metrics, logs, traces, dashboards, and actionable alerting that support effective operational decisions - Reduce platform friction for product teams by providing architectural guidance, platform standards, and hands-on enablement - Automate platform lifecycle management including bootstrap, upgrades, scaling, and operational maintenance to reduce manual effort and risk - Drive technical direction and sound architectural choices across platform engineering with pragmatic trade-offs between reliability, security, speed, and maintainability - Help raise engineering maturity by mentoring others and shaping shared engineering standards across teams WHAT WE’RE LOOKING FOR MUST HAVES: - 8+ years of experience in Platform Engineering, SRE, DevOps, or infrastructure roles operating production-critical services at scale - Deep hands-on expertise with Kubernetes, including cluster architecture, upgrades, control plane operations, networking, ingress, storage, security, and lifecycle management - Strong understanding of AWS fundamentals, including networking, IAM, compute, storage, and security patterns - Strong experience with Terraform and infrastructure as code, including reusable modules, abstractions, and scalable provisioning patterns - Strong practical observability experience, including SLO and SLI design, instrumentation, dashboarding, alert strategy, and production performance analysis - Proficiency in at least one backend language such as Python or Go for automation, tooling, and internal platform capabilities - Experience providing technical leadership through platform standards, architectural guidance, and hands-on enablement - Ability to operate effectively in complex environments and make pragmatic technical decisions across reliability, security, speed, and maintainability NICE TO HAVES: - Experience with Rancher, Istio, External Secrets, Vault, and software supply-chain hardening practices - Experience operating Kubernetes in restricted, disconnected, or air-gapped environments - Experience with hybrid platforms spanning AWS and on-prem environments such as vSphere or VxRail APPLICATION PROCESS - Talent Attraction Introduction - Hiring Manager Alignment - Task Assignment - Technical Interview - Director Interview WORKING AT ICEYE At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win. HOW WE WORK (OUR VALUES) Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way. - Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the why behind decisions. - See the big picture: Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others. - Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions. - Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift. - Have fun: What we do matters and it should be enjoyable. Celebrate progress, take pride in results, and share the wins. BENEFITS Our benefits are designed to support your health and wellbeing, at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process. OUR COMMITMENT TO DIVERSITY, EQUITY, AND INCLUSION We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table. We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us and we will do our best to help. Apply now to start your ICEYE journey and help us continue to make the impossible possible together. Read more about ICEYE and working with us at iceye.com http://iceye.com.

Location: Switzerland Workplace: Remote About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. Who We're Looking For A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. Experience We Find Useful You don't need all of this. But you need enough to make a case. - Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM. - Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding. - High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs. - Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections. - Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups. - Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production. - Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems. - Professional fluency in English (written and spoken) is required, as you will be collaborating daily with our US-based leadership and engineering teams. Who Thrives Here - You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations. - You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem. - You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. What Working Here Is Like We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. Location & Employment - Location: remote within Switzerland - Employment type: Full-time, permanent employment - Hiring model: Employment via Employer of Record (EOR) Candidates must already have the legal right to work in Switzerland, as visa sponsorship is not available for this role. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: UK Workplace: Remote About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. Who We're Looking For A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. Experience We Find Useful You don't need all of this. But you need enough to make a case. - Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM. - Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding. - High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs. - Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections. - Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups. - Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production. - Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems. Who Thrives Here - You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations. - You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem. - You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. What Working Here Is Like We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. The base salary range for this full-time position is £140,000 – £200,000. In addition to base pay, total compensation includes equity and benefits. Within the range, individual pay is determined by work location, level, and additional factors, including competencies, experience, and business needs. The base pay range is subject to change and may be modified in the future. Candidates must already have the legal right to work in the United Kingdom, as visa sponsorship is not available for this role. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: Mountain View, California, USA Workplace: Hybrid About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. Who We're Looking For A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. Experience We Find Useful You don't need all of this. But you need enough to make a case. - Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM. - Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding. - High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs. - Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections. - Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups. - Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production. - Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems. Who Thrives Here - You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations. - You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem. - You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. What Working Here Is Like We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. We believe in the power of in-person collaboration to solve the hardest problems and foster a strong team culture. We offer relocation assistance and look forward to you joining us in our Mountain View office. The base salary range for this full-time position is $270,000 - $430,000+ bonus + equity + benefits. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: Remote, Canada; Remote, United Kingdom; Remote, US GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. As a Staff Backend Engineer in the Developer Experience group, you’ll work cross-functionally to help us identify and improve the engineering experience across GitLab’s internal engineering teams. We’re at a pivotal time in transforming our testing approach and development experience to enable engineers to deliver high-quality code efficiently and with confidence. Developer Experience currently has six, globally distributed teams of Backend Engineers and Software Engineers in Test. This role will work across the entire group to help us identify and remove the biggest points of friction that affect development at GitLab. Expect to split your time between hands-on coding in Ruby and Go, designing scalable solutions and helping every team deliver.  You’ll be instrumental in shaping our engineering culture across GitLab. This is a highly visible role with strong company-wide support. You’ll be instrumental in shifting our culture and practices toward a cohesive Developer Experience Platform strategy—backed by buy-in and appetite for change. Some examples of our projects Project Examples In this role, you may lead projects such as: Internal developer platform adoption: Build and evolve platform capabilities that make it easier for engineering teams to create, deploy, operate, and scale services on Kubernetes. Kubernetes-based service onboarding: Define reusable service templates, deployment workflows, configuration patterns, and operational guardrails for teams adopting the platform. Developer workflows and test environments: Build development, CI, and test environments that reflect production Kubernetes behavior — including third-party operators and the custom resources services depend on — sequencing CRD establishment, controller readiness, and dependent workloads so engineers get a working environment rather than a partially reconciled one, across both local and remote clusters. Platform reliability and observability: Partner with infrastructure and service teams to improve rollout safety, troubleshooting, service health, resource management, and operational visibility across Kubernetes workloads. What You'll Do Lead and grow a team responsible for developer tooling and internal platform capabilities used by engineering teams to build and operate services. Set and execute a roadmap for Kubernetes-based developer workflows, balancing developer experience, platform reliability, security, and operational efficiency. Guide the design of reusable onboarding and deployment patterns for services running on Kubernetes, including workloads, networking, configuration and secrets, identity, storage, observability, progressive delivery, and the custom resources and controllers that services depend on. Make environment bring-up and teardown deterministic — resolving readiness and ordering dependencies between CRDs, controllers, and the workloads that rely on them — so engineers get reproducible environments instead of intermittent failures. Partner with infrastructure, security, and application teams to turn Kubernetes capabilities into simple, well-supported workflows rather than requiring every service team to become a Kubernetes expert. Establish engineering standards, documentation, automation, and feedback loops that improve adoption and reduce the time required to bring a service from development to production. Coach engineers through architectural decisions, incident follow-up, and production operations while maintaining a clear focus on sustainable team delivery. Represent the team with technical and organizational stakeholders, communicate tradeoffs clearly, and use adoption and reliability measures to guide prioritization. Take part in on-call or operational support where your team’s ownership model requires it. What You'll Bring Deep experience building developer tooling, DevEx platforms, testing frameworks, or CI/CD systems at scale. Strong hands-on Go experience designing, implementing, testing, and operating production-quality services, command-line tools, automation, or platform tooling. Experience contributing to Ruby-based systems is also valuable for this role. Practical Kubernetes experience building or operating production workloads and platform capabilities, including deployments, services, networking, configuration and secrets, observability, resource management, and troubleshooting. Depth in Kubernetes deployment lifecycle: Helm-based deployment and release management, kubeconfig and multi-cluster context handling including deploying into clusters you don't own, and integrating third-party operators and their custom resources (CloudNativePG, cert-manager and similar) into working environments — including the readiness and ordering problems that come with them: waiting on CRD establishment, controller availability, and custom resources reaching their own definition of ready. Experience authoring a controller or operator is useful but not required. Experience designing scalable solutions that improve engineering productivity, test reliability, development environments, or delivery workflows across multiple teams. Demonstrated ability to provide technical leadership and influence without authority across engineering, infrastructure, security, and product functions. Familiarity with DevOps workflows, CI/CD pipelines, release automation, and production operations. Strong written and verbal communication skills in a remote-first environment. A product mindset with a passion for empowering developers through simple, reliable, and well-documented workflows. Alignment with GitLab values, especially collaboration, iteration, and transparency. The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $131,600 — $282,000 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: Lanham, MD Position Objective: Contributes to the provision of high-quality, cost-effective healthcare as a provider of direct and indirect patient care and by effective of the health care team. Functions as a competent member of the health care team. 1. Clinical Decision Making/Judgment Demonstrates clinical nursing knowledge and skill in the specialization of the unit. Demonstrates the ability to apply the nursing process effectively in the care of culturally diverse patients and families. Demonstrates the ability to utilize all applicable laws, policies, standards, guidelines and evidence-based practice in the provision of patient/family care. Organizes and reprioritizes patient care activities based on subtle and overt and/or environmental changes. Consistently and thoroughly assesses patients to collect data and identify learning needs according to established standards and policies. Utilizes a systematic, continuous and complete analysis of assessment data to develop individualized problem lists for assigned patients. Develops and individualizes a plan of care for each patient in accordance with established standards, appropriate prioritization of problems/needs, and mutually agreed upon goals. Efficiently implements the patients plan of care in accordance with applicable standards, policies, procedures and guidelines. Demonstrates proficiency in medication administration, pain management and other unit or initiative specific skills. Continuously evaluates the effectiveness of the plan(s) of care, making revisions and recommendations based on analysis of patient responses to interventions. 2. Nurse-Patient Family Relationships Demonstrates the ability to assess the patients/familys learning needs, readiness to learn, learning style, and presence of barriers to learning. Demonstrates the ability to develop, implement and evaluate teaching plans for patient populations in unit specialty in accordance with applicable standards. Demonstrates the ability to apply knowledge of growth and development across the life span to the care of patients. Provides direct patient care to patients and families in a culturally, developmentally and ethically appropriate manner. Plans of care address the physical, psychosocial, spiritual and learning needs of the patient/family. 3. Clinical Scholarship Participates in QI, CPI and risk management activities at the unit, department or organizational level. Demonstrates the ability to effectively perform and improve all processes in order to achieve excellence with regard to Luminis Healths quality standards and benchmarks. Supports the use of evidence based guidelines and organizational policies and procedures to promote safe patient care and a safe practice environment. 4. Clinical Leadership Participates in unit shared governance according to departmental standards. Participates in the education and orientation of new staff. Delegates patient care activities as appropriate; evaluates delegated activities for expected patient care outcomes. Employs real time computer documentation when completing patient record. Educational/Experience Requirements: Graduate of an accredited school of nursing Adherence to the credentialing requirements of Luminis Health as stated in the nursing bylaws. Where applicable, completion of a BSN is required within 5 years of date of hire Required License/Certifications: Current licensure as a registered nurse by the Maryland Board of Nursing BLS - American Heart Association Health Provider If serving as a bilingual/multilingual interpreter, certification in Medical Interpretation is required to perform the duties of a qualified interpreter. Additional requirements by department: PALS Requirement: The following department(s) require PALS: Pediatrics Unit, Postanesthesia Care Unit, Endoscopy, Procedural Care Unit, Interventional Radiology. ACLS Requirement: The following department(s) require ACLS: Heart and Vascular Unit, Neuro Care Unit, ICU/IMU, Interventional Radiology, Postanesthesia Care Unit, Progressive Care Unit, Resource Nurses, Emergency Department, Prep, Telemetry, Outpatient Infusion, DRCC Bowie, Observation Unit, Endoscopy, Procedural Care Unit, Cardiac Cath Lab, Flex Nursing Unit, Operating Room (LHDCMC only), Cardiac Cath Lab, Observation Unit, DCMC IP Mental Health, and Edwards Pre-Op and PACU. New Grad and New to Specialty RN’s in ICU must get their ACLS within 6 months Chemotherapy/Immunotherapy Certification requirement: Certification within 6 months of hire if experienced or within 1 year for new graduate nurse The following department(s) require a Chemotherapy/Immunotherapy Certification: Oncology Unit NRP - Neonatal Resuscitation requirement: The following department(s) require NRP - Neonatal Resuscitation: Mother and Baby Unit, Neonatal Intensive Care Unit, Labor and Delivery Unit, and Women's Surgical Unit. BLS requirement: The following department(s) require BLS: Employee Health, Performance Improvement, Special Pathogens Unit, Neuro Care Unit, Pre-Anes Testing, Wound Care Center, Medical Staff Office, Nursing Administration, Nursing Graduate Program, Women's Surgical Unit, Joint and Spine Unit, 4 Medical, IV Therapy, Nursing Quality and Research, HSCRC Nursing Grant, Flex Nursing Unit, ICU, Operating Room, Short Stay Unit, Postanesthesia Care Unit, Progressive Care Unit, 4TH FLOOR, DCH 3 East Med Surg Telemetry, 3 West Oncology, Emergency Room, Oncology Unit, ACE Unit and 2 EAST OBS, Vascular Access Team. Working Conditions, Equipment, Physical Demands: There is a reasonable expectation that employees in this position will be exposed to blood-borne pathogens. Physical Demands - The physical demands and work environment that have been described are representative of those an employee encounters while performing the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions in accordance with the Americans with Disabilities Act. The above job description is an overview of the functions and requirements for this position.  This document is not intended to be an exhaustive list encompassing every duty and requirement of this position; your supervisor may assign other duties as deemed necessary. Pay Range $34 — $54 USD Luminis Health Benefits Overview: •    Medical, Dental, and Vision Insurance •    Retirement Plan (with employer match for employees who work more than 1000 hours in a calendar year) •    Paid Time Off •    Tuition Assistance Benefits •    Employee Referral Bonus Program •    Paid Holidays, Disability, and Life/AD&D for full-time employees •    Wellness Programs •    Employee Assistance Programs and more *Benefit offerings based on employment status Opt-in for text notifications! Luminis Health's two-way SMS texting platform lets you receive notifications and messages from our Talent Acquisition team directly on your phone. To enable this feature, select "yes" when asked to "opt-in to receive text messages" and to "Receive updates from a recruiter about this job via SMS" when completing your application. Once you are opted in, you can easily opt-out at any time. Standard text messaging rates may apply based on the candidate's mobile carrier plan. Luminis Health is not responsible for any charges incurred by the recipient. Candidates are encouraged to review their mobile carrier's plan for applicable text messaging rates and usage charges.