This is Hybrid role (3 days in office /2 days remote)

About your Team:

The Enterprise Architecture organization is looking for a Data Engineer to join the team and help build the next generation of data infrastructure and AI-enabled workflows. In this role, you will be responsible for designing, building, and maintaining scalable data pipelines, data lake platforms, and analytics solutions that support enterprise-wide AI initiatives and advanced analytics capabilities. You will partner closely with internal development teams and IT leadership to architect data solutions that meet diverse use-cases across the organization. This role offers the opportunity to work with cutting-edge data technologies, AI knowledge bases, and cloud-native data platforms as we scale our data operations. Your work will focus on delivering robust, well-documented data solutions and establishing best practices for data engineering across the enterprise.

 What will be your responsibilities within IBKR: 

· Design, build, and maintain scalable data crawlers and ETL/ELT pipelines to ingest data from various sources including enterprise collaboration tools, web applications, and internal databases

· Develop and manage data lake platform infrastructure including S3-based storage, Iceberg tables, AWS Glue data catalog, and cloud data warehouse solutions for analytics workloads

· Build and optimize real-time streaming data pipelines using Kafka for event-driven analytics and data processing

· Create and maintain data transformation pipelines to clean, curate, and prepare data for analytics and AI/ML applications, supporting multiple data formats including structured, semi-structured, and unstructured data (text, images, audio, video)

· Develop Python-based applications for data ingestion, processing, and integration supporting Gen AI RAG workflows and knowledge base systems

· Collaborate with internal development teams, data scientists, and stakeholders to understand requirements, architect appropriate data solutions, and create comprehensive technical documentation

· Monitor, troubleshoot, and optimize data pipelines for performance, reliability, and data quality

· Write clean, maintainable, well-tested code following software engineering and data engineering best practices

· Create comprehensive technical documentation for data pipelines, architectures, and platform capabilities

 What required skill’s you need:

· 6+ years of hands-on data engineering experience with modern data stack technologies

· Strong experience with AWS cloud services, particularly: S3, AWS Glue, Athena, EMR, Lambda

· Proficiency in Python for data processing, ETL, and application development

· Experience with PySpark on EMR for large-scale data processing

· Strong SQL skills for data analysis and transformation

· Experience building and maintaining ETL/ELT pipelines at scale

· Experience with Kafka for streaming data pipelines and real-time data processing

· Knowledge of data lake architectures and modern table formats (e.g., Iceberg)

· Experience with CI/CD practices using Git, version control systems, and containerization (Docker)

· Understanding of data modeling, data warehousing concepts, and analytics best practices

· Exceptional problem-solving and analytical skills

· Excellent collaboration and communication (verbal and written) skills

· Self-motivated with ability to work independently and manage multiple priorities

· Willingness and enthusiasm to learn AI/ML technologies, stay current with emerging data engineering trends

 To be successful in this position, you will have the following:

• Self-motivated and able to handle tasks with minimal supervision.
• Superb analytical and problem-solving skills.
• Excellent collaboration and communication (Verbal and written) skills.
• Outstanding organizational and time management skills.

Company Benefits & Perks

About the Role

As a seasoned Infrastructure Engineer, you will design, manage, and scale our high-performance computing environments. This role bridges the gap between traditional system
administration and modern platform engineering, focusing on reliability, automation, and the stringent security requirements of the financial services industry. You will be responsible for a
hybrid ecosystem that spans AWS cloud and on-premise systems, ensuring 99.99% uptime for mission-critical services and transactions.

What You’ll Do

• Linux Systems Engineering: Design and manage high-performance Linux environments including Ubuntu, RHEL, or Amazon Linux. Focus on tuning for low-  latency financial applications and system-level hardening
• Infrastructure as Code (IaC): Architect and maintain scalable cloud infrastructure using Terraform and Ansible, treating infrastructure as a software project with version control
  and peer reviews
• Hybrid Networking: Manage connectivity between cloud environments and on-premise systems, focusing on secure VPC design, VPNs, and routing
• On-Premise Management: Manage physical switches, routers, and firewalls, with an understanding of multicast, VLANs, and interface aggregation
• CI/CD & Release Engineering: Build and optimize deployment pipelines to ensure system updates, patches, and application code are deployed safely and frequently
• Observability & Reliability: Implement comprehensive monitoring (using Prometheus, Loki, and Grafana) to track system SLIs/SLOs and implement automated alerting or self-
  healing scripts
• Container Platform Management: Support and scale Docker / Podman environments, focusing on pod networking and container runtimes
• Infrastructure Security: Implement "shift-left" security, including OS-level hardening (SELinux, AppArmor), automated vulnerability scanning, and IAM policy refinement

What You’ll Need

• Education: Bachelor’s degree in Computer Science, Engineering, IT, or a related field
• Systems Expertise: 3+ years of experience in Linux Administration or Infrastructure Engineering
• System Internals: Deep knowledge of system performance profiling (e.g., top, iostat, strace) and comfort with Linux system fundamentals (i.e. Systemd, LVM, and Cron)
• Automation Proficiency: Strong proficiency in Ansible and Terraform for infrastructure and system automation. Bash and/or Python experience for custom tooling as required
• Cloud & Networking Fundamentals: Hands-on experience with AWS Networking fundamentals (VPCs, Routing Tables, and Nat Gateways). Solid understanding of TCP/IP, DNS, and routing protocols like BGP or OSPF
• Container Runtime: Experience with container runtimes in a Production environment (Docker / Podman, Docker Compose). Kubernetes experience is a plus
• Problem Solving: Ability to perform root-cause analysis on complex distributed systems
  
  Applicants must be authorized to work for any employer in the U.S. DriveWealth is unable to sponsor an employment Visa at this time.

Special Knowledge (Nice to Have, But Not Required)

• Compliance Knowledge: Experience working within regulated environments such as SOC2, or FINRA
• High-Availability Architecture: Experience building multi-region, failover-capable architectures for mission-critical financial transactions
• SDLC Architecture: Architecting deployment pipelines using GitHub actions, familiarity with AWS Secrets Manager for managing sensitive secrets, and other DevOps toolchain
  services
• Fintech Protocols: Basic understanding of financial messaging or low-latency requirements, such as FIX protocol
• Security & Application Tuning: Experience with WAF, DDoS mitigation strategies, and tuning edge application services such as HAProxy
• Certifications: CompTIA Linux+, RHCSA/RHCE, or AWS SysOps Administrator

What We're Looking For

As a Machine Learning Solutions Engineer, you will operate at the intersection of machine learning, distributed systems, and cloud infrastructure.
You will partner with customers to design and deploy end-to-end AI systems, spanning:

• Model development and training
• GPU infrastructure and cluster design
• Distributed inference and production deployment

This role goes beyond traditional ML solutions engineering—you will act as a technical architect, helping customers make critical decisions across compute, orchestration, and system design.

The role can be based out of our New York City or San Francisco office, with an in-office requirement of at least 2-3 days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this role at this time. The annual base pay range for this role is $150,000 - $195,000, in addition to a variable pay component and meaningful equity. 

What You’ll Do

Customer Architecture & Technical Leadership

• Partner with customers to understand ML workloads, infrastructure constraints, and scaling requirements
  
  
• Architect end-to-end solutions across:
  
  
• Data pipelines (CPU → GPU workflows)
  
  
• Distributed training (multi-node, multi-GPU)
  
  
• High-throughput inference systems
  
  
• Translate business goals (latency, cost, throughput) into technical system design decisions
  
  

GPU & Infrastructure Design

• Design and optimize workloads across GPU clusters (H100, H200, B200, etc.)
  
  
• Advise on:
  
  
• Training vs inference cluster design
  
  
• Interconnect choices (Ethernet vs Infiniband / RDMA vs Roce)
  
  
• Storage strategies (local NVMe vs networked / object storage)
  
  
• Model and optimize for:
  
  
• Tokens/sec, tokens/$
  
  
• Throughput vs latency tradeoffs
  
  
• GPU utilization and scheduling efficiency
  
  

Kubernetes & Platform Systems

• Design and support deployments on Kubernetes (EKS, GKE, on-prem clusters)
  
  
• Work with:
  
  
• GPU scheduling (time-slicing, MIG, bin-packing)
  
  
• Autoscaling and workload orchestration
  
  
• Helm-based deployments and multi-tenant environments
  
  
• Help customers balance:
  
  
• Raw Kubernetes flexibility vs platform abstraction (Lightning)
  
  

Demos, POCs, and Execution

• Build and deliver technical demos and POCs that showcase:
  
  
• Distributed training workflows
  
  
• Scalable inference endpoints
  
  
• End-to-end ML pipelines on Lightning AI
  
  
• Scope and lead POCs aligned to customer success metrics (latency, cost, reliability)
  
  

Cross-Functional Impact

• Act as the bridge between customers, product, and engineering
  
  
• Provide feedback on:
  
  
• Platform gaps in infrastructure, orchestration, and performance
  
  
• Emerging patterns in GPU usage and distributed systems
  
  
• Influence roadmap across ML workflows and infrastructure capabilities
  
  

Enablement & Thought Leadership

• Create technical content
• Architecture guides (e.g., high-throughput LLM inference systems)
• Best practices for GPU utilization and scaling
• Educate customers on modern AI infrastructure patterns

What You’ll Need

ML + Systems Expertise

• 3–6+ years experience in:
  
  
• Machine Learning / AI Engineering
  
  
• Solutions Engineering / Sales Engineering / ML Consulting
  
  
• Strong understanding of:
  
  
• Training vs inference workloads
  
  
• Model optimization (quantization, batching, caching, etc.)
  
  

GPU & Distributed Systems

• Experience working with:
  
  
• GPU clusters (NVIDIA stack preferred)
  
  
• Distributed training or inference systems
  
  
• Familiarity with:
  
  
• NCCL, CUDA, or GPU performance profiling
  
  
• Networking concepts (RDMA, Roce, Infiniband, high-throughput systems)
  
  

Kubernetes & Cloud Platforms

• Hands-on experience with:
  
  
• Kubernetes (EKS, GKE, or on-prem)
• Slurm 
• Containerization (Docker)
  
  
• Exposure to:
  
  
• GPU scheduling in Kubernetes environments
  
  
• Multi-tenant or production ML deployments
  
  

Programming & Tooling

• Strong Python skills (PyTorch preferred)
  
  
• Experience building:
  
  
• ML pipelines
  
  
• APIs or inference services
  
  
• Familiarity with Lightning AI, PyTorch Lightning, or similar frameworks is a plus
  
  

Customer-Facing Excellence

• • Ability to:
    
    
    • Explain complex infrastructure and ML tradeoffs clearly
      
      
    • Run technical discovery and uncover quantifiable success metrics
      
      
  • Experience working cross-functionally with:
    
    
    • Sales, product, and engineering teams

Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. 

Our research spans:

• Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. 
• Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science
• Imaging foundation models trained across the world's largest microscopy datasets
• Reasoning and agentic systems that connect frontier LLMs with biological foundation models
• Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights
• Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled

Join our Team!

As an ML Engineer, you'll join some of the strongest infrastructure engineers in AI, building the systems that connect everything together. The infrastructure problems you solve directly determine what science becomes possible. 

What You'll Do

• Work with high-dimensional scientific data formats and contribute to backend compatibility, format evaluation, and I/O performance benchmarking at petabyte scale.
• Define and shape the engineering patterns your team and collaborating researchers will build on for years; the abstractions you write today become the foundation others depend on at scale.
• Work at the intersection of AI systems and biological discovery, where the infrastructure problems you solve directly determine what science becomes possible.
• Deploy models to production and manage artifact tracking across models and datasets.
• Design and optimize GPU-native data loading pipelines for large-scale multi-dimensional tensor workloads, including profiling and resolving hardware utilization bottlenecks across multi-backend systems.
• Work on simplification and improvement of codebase abstractions to accelerate research momentum.
• Build and maintain primitives for pre-training infrastructure that ensure the reliability and continuity of large-scale training runs.
• Help cultivate best practices in MLOps, and think about the full ML lifecycle, including data, fine-tuning, deployment, reliability and monitoring.
• Possesses the ability to execute complex modifications to the research pipeline, such as fast data loading and distributed training.
• Handle DevOps responsibilities, focused on making all engineers and researchers more productive. This includes tasks like cluster monitoring, unit testing and integration testing of research codebase, and continuous integration.
• Collaborate with partner researchers and engineers to deploy our technology within external infrastructure.

What You'll Bring

• Hands-on experience with PyTorch, including custom training loops, distributed training, or low-level performance work.
• Familiarity with GPU-native data I/O tools and large-scale tensor formats (e.g. Zarr, HDF5, TensorStore, or similar).
• Experience with distributed computing frameworks such as Apache Spark, Dask, or Ray.
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
• Experience building or working with AI agent frameworks is a plus.
• A track record of building systems that other engineers and researchers depend on. Not just running experiments, but shipping infrastructure that scales.

Compensation

The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is $150,000 to $350,000+ annually. Compensation ranges will vary based on job-related skills, level of experience, and knowledge. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.

Benefits for the Whole You 

We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. 

• Provides a generous employer match on employee 401(k) contributions to support planning for the future.
• Paid time off to volunteer at an organization of your choice. 
• Funding for select family-forming benefits. 
• Relocation support for employees who need assistance moving

Please note that applying to this opportunity does not guarantee that we will be in touch with you regarding our opportunities. Our recruiting team will contact you if your experience aligns with the skills we seek for future open positions. We will keep your interest on file, contact you as opportunities arise, and send you information about the exciting work we are doing at Biohub. You can opt out at any time! 

#LI-Hybrid

What We're Looking For

We’re looking for a Backend Engineer to help develop and scale the Lightning AI platform, spanning APIs, infrastructure, billing, security, and integrations. In this role, you’ll take ownership of key features and drive them end-to-end, working closely with engineering, product, and design to ship high-quality, iterative improvements. This is an opportunity to build systems that support real-world machine learning workloads at scale.

This role is based in one of our hubs (Seattle, NYC, SF, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

• Write readable/testable/efficient code in Go (Golang).
• Build deep expertise in our technology stack to deliver new features, improve system stability, and increase overall performance.
• Partner with engineering and product leaders on developing the Lightning product while using your experience to set the technical direction for large projects.
• Evaluate, strengthen, and document technical architecture, tools, and processes.
• Maintain software quality, implement automation, drive continuous delivery, and reduce time to production while proactively reducing technical debt.
• Mentor and coach engineers on system design, operating in high uncertainty, and problem-solving to create a supportive, inclusive environment where each engineer can grow.

What You’ll Need

• Extensive experience writing efficient, maintainable code in Go. Familiarity with best practices in testing, readability, and optimization is essential.
• Broad knowledge of backend and frontend systems, with experience building and scaling APIs, CLI tools, billing systems, and security protocols. Exposure to frontend frameworks is a plus.
• Experience with cloud platforms like AWS, GCP, or Azure and designing systems that are reliable, performant, and scalable. Familiarity with containerization (Docker, Kubernetes) is a strong advantage.
• Proven ability to take ownership of key features and drive end-to-end development
• Commitment to software quality, test automation, and continuous delivery. Experience proactively managing technical debt and speeding up time to production.
• Hands-on experience as a backend or product engineer in a SaaS technology company
• Communication and collaboration with engineers, product managers, and designers
• Ability to operate in high uncertainty and rapidly changing environments

Compensation

 What You’ll Be Part Of

At iSpot.tv, we deal with BIG data, operating in a high-scale AWS environment with thousands of servers processing massive streams of media metadata. As a Senior SDE, you are a foundational pillar of our engineering team. You don't just write code; you own entire domains, drive scalable solutions, and act as a "go-to" expert.

We are currently looking for an AI-native engineer—someone who views AI not as a novelty, but as a core component of their development lifecycle—to help lead our mission-critical data evolution, including our strategic migration from Redshift to Snowflake.

 Your Impact

1. Technical Excellence & Domain Ownership

• Coding & Debugging: You will design domains with testability and multiple teams in mind, creating extensible and shareable codebases. You are expected to provide prescriptive code reviews that suggest more acceptable code patterns and contribute to company-wide style guidelines.
• System Modernization: You will lead efforts to upgrade legacy systems, refactoring technical debt into scalable, modern architectures, including x-region database migrations and moving to EKS.
• Quality & Release: You will maintain a high standard of quality, setting the example for the team. This involves developing the architecture for our automation systems and expertly debugging complex issues within the CI/CD pipeline. You will be responsible for implementing secure deployment strategies, especially for large-scale, high-risk projects.

2. AI-Driven Productivity & Innovation

• AI-First Mindset: You are expected to be "AI-native." You will actively explore and learn about AI technologies that enhance the efficiency of the entire team’s work.
• Leading Adoption: You don't just use AI; you "create space" for teammates to improve their AI tooling through pairing, providing demos, and writing documentation.
• Creative Problem Solving: You are a pioneer in critical technologies, bringing creative solutions to complex, large-scale projects and ensuring your contributions can be extended far into the future.

3. Operational Excellence & Data Strategy

• Data-Driven RCA: You will propose and implement viable domain measurement solutions. You’ll play a lead role in researching external solutions and leading root cause analysis (RCA) for complex, multi-domain incidents.
• Operational Efficiency & Toil Reduction: You are expected to proactively improve the current state of operations by identifying and reducing toil. You will apply a "Platform Engineering" mindset to automate repetitive manual tasks, ensuring the team remains focused on high-value engineering.
• Scalability & Influence: You will build internal networks to improve organizational speed and the quality of technology solutions, removing obstacles for the team as they arise. You are the "go-to" person for the team, identifying trends and introducing broad solutions to address systemic issues.
• Cost-Conscious Engineering: You will drive a mature cost-optimization strategy, ensuring that architectural decisions and cloud resource utilization are both performant and cost-efficient. You are expected to balance technical excellence with business value, treating cost-consciousness as a core pillar of system reliability.

4. Leadership & Collaboration

• Strategic Alignment: You routinely work cross-functionally to align partners and stakeholders with the project vision and strategy.
• Mentorship: You mentor less experienced team members, ensuring your communication promotes clarity and inspires action. You onboard and coach other engineers in adopting an AI-first mindset, focusing on low-risk strategies.
• Conflict Resolution: You are adept at handling personal conflicts within the team and navigating ambiguity to reach strategic milestones.

 What You Bring

• Experience: Significant experience developing software for shareable features across multiple engineering projects. Experience leading small-to-mid-sized technical initiatives is required.
• Architectural Leadership: Proven ability to make high-level architectural decisions, including redesigning legacy services to ensure they are highly reliable and operable. You follow industry best practices for high-availability API design and the streamlining of complex database operations.
• Platform Engineering: Hands-on experience with Platform Engineering principles, focusing on internal developer experience, infrastructure abstraction, and building self-service capabilities for engineering teams.
• Cloud Native: Expert knowledge of AWS (S3, Lambda, EC2, IAM).
• Tech Required: Java, Spring Boot, MySQL, RabbitMQ (or similar message broker), Kubernetes/EKS, Docker, CI/CD pipelines.
• Tech Preferred: Redshift, Helm, Terraform, Gradle, Groovy.
  • Bonus: Proven experience or a deep architectural understanding of migrating data workloads from Redshift to Snowflake.
• AI Native: Experience using AI coding assistants and LLMs to accelerate development (e.g., Kiro, Gemini, Copilot, Cursor, or similar).
• Soft Skills: Strong communication skills with the ability to tailor messaging to different audiences (from junior devs to senior leadership). Excellent problem-solving and analytical skills.

 Preferred Qualifications

• Experience in Ad-Tech or high-throughput "Big Data" processing environments.
• Experience with Infrastructure as Code (Terraform) and CI/CD concepts (CircleCI).

A track record of identifying trends in incidents and introducing broad solutions to address them.

Target cash compensation range: $136,100 - $170,000 USD Annually

We are committed to providing competitive, market-informed compensation. The cash compensation above includes base salary, variable commission for employees in eligible roles, and annual bonus targets for eligible roles. In addition to cash compensation, all full time iSpotters are eligible to participate in iSpot’s equity plan to receive stock options. Non-exempt roles will also be eligible for (pre-approved) overtime pay. Individual compensation packages are influenced by different factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons.

For more information on total rewards package, go HERE

Hybrid & Flexible Workplace Policy

iSpot supports a hybrid and flexible workplace. Depending on location and work responsibilities, employees may be designated as full-time or part-time office-based or a fully remote employee. A hybrid work schedule indicates that you work in the office some days and work from home other days. The best hybrid workplaces allow for flexibility while also encouraging consistency. 

Those local or living in surrounding areas to one of our offices (Bellevue, WA or New York, NY) will work a hybrid schedule, coming into their local office 1-3 days a week. While those in a role, not office-based and located further away from our offices, will work a fully remote schedule. If you have questions regarding exact details of our hybrid & flexible workplace policy, please let your recruiter know and they will discuss with you further.

#LI-Hybrid

What You’ll Be Part Of

At iSpot.tv, we process massive streams of media metadata in a high-scale AWS environment. As an SDE II, you have moved past foundational learning and are now a competent, independent contributor. You are responsible for delivering high-quality features that power our industry-leading measurement and attribution products.

We are looking for an AI-native engineer—someone who instinctively uses AI to move faster and write better code. You will be a key player in our modern engineering culture, helping us maintain our "source-of-truth" data foundation while supporting major initiatives like our strategic migration to Snowflake.

Your Impact

1. Technical Excellence & Domain Ownership

• Coding & Debugging: You are competent in programming and debugging across multiple components and environments. You will independently own and deliver features, writing high-quality code that includes monitoring, metrics, and logging as standard practice.
• Testing & Quality: You author and own the testing plan for your features, considering product requirements and edge cases. You’ll perform various test types (unit, component, integration, E2E) and are developing the skills to identify patterns in test results to differentiate between application bugs and environment issues.
• Code Reviews: You actively participate in code reviews, following team guidelines and best practices to ensure the collective codebase remains healthy and maintainable.

2. AI-Driven Productivity & Efficiency

• AI-First Workflow: You independently use AI tools (e.g., Cursor, Copilot, Gemini) to improve the speed and quality of your tasks. This includes using AI for code understanding, self-code reviews, and ramping up quickly in new domains or languages.
• Critical Evaluation: You don't blindly copy-paste. You critically evaluate AI-generated output to ensure its correctness, security, and alignment with iSpot standards before relying on it.
• Continuous Improvement: You identify enhancements or efficiencies in your work assignments, using AI to automate repetitive tasks so you can focus on solving complex logic.

3. Operational Excellence & Data Strategy

• Incident Management: You participate in the on-call rotation and will contribute to defining on-call expectations. You are responsible for promptly investigating test failures and production alerts. You are also developing the ability to perform Root Cause Analysis (RCA) in common areas (code, technology, and incidents) with limited guidance.
• Scalability: You will build internal networks to improve organizational speed and improve the quality of technology solutions, removing obstacles for the team as they arise.
• Data Migration Support: You will support the senior team in our Redshift to Snowflake evolution by assisting with data validation, schema updates, and performance monitoring.

4. Collaboration & Growth

• Independence: You complete most assignments independently with little to no supervision, knowing exactly when and how to escalate issues to your manager or senior leads.
• Team Contribution: You help onboard and train new team members and are proactive in building trust through excellent follow-through and integrity.
• Communication: You communicate clearly and concisely, sharing opportunities to improve deliverables or work processes with the broader team.

What You Bring

• Experience: Significant experience (typically 2–5 years) developing software features for business or technology solutions.
• Java Proficiency: Strong experience with Java and Spring Boot in a microservices environment.
• Cloud Foundation: Solid understanding of AWS (S3, Lambda, EC2) and containerization (Docker).
• Tech Required: Java, Spring Boot, MySQL, Git, and familiarity with CI/CD pipelines.
• Tech Preferred: Experience with message brokers (RabbitMQ/SQS), Kubernetes (EKS), Docker, and SQL optimization.
• AI Native: Demonstrated ability to use LLMs and AI coding assistants to accelerate your development lifecycle.
• Mindset: A results-oriented drive to meet high standards and a "persistent/tenacious" approach to solving technical hurdles.
• Soft Skills: Strong communication skills with the ability to tailor messaging to different audiences (from junior devs to senior leadership). Excellent problem-solving and analytical skills.

Preferred Qualifications

Experience in Ad-Tech or high-throughput "Big Data" processing environments.

Target cash compensation range: $104,700 - 120,000 USD Annually

We are committed to providing competitive, market-informed compensation. The cash compensation above includes base salary, variable commission for employees in eligible roles, and annual bonus targets for eligible roles. In addition to cash compensation, all full time iSpotters are eligible to participate in iSpot’s equity plan to receive stock options. Non-exempt roles will also be eligible for (pre-approved) overtime pay. Individual compensation packages are influenced by different factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons.

For more information on total rewards package, go HERE

Hybrid & Flexible Workplace Policy

iSpot supports a hybrid and flexible workplace. Depending on location and work responsibilities, employees may be designated as full-time or part-time office-based or a fully remote employee. A hybrid work schedule indicates that you work in the office some days and work from home other days. The best hybrid workplaces allow for flexibility while also encouraging consistency. 

Those local or living in surrounding areas to one of our offices (Bellevue, WA or New York, NY) will work a hybrid schedule, coming into their local office 1-3 days a week. While those in a role, not office-based and located further away from our offices, will work a fully remote schedule. If you have questions regarding exact details of our hybrid & flexible workplace policy, please let your recruiter know and they will discuss with you further.

#LI-Remote

About the Role

iCapital is looking for a Software Developer in Test to work on the iCapital platform. In this role, you’ll bring practical knowledge of agile development methodologies and engineering best practices. As a Software Developer in Test (SDET), you’ll work closely with the Development and Testing team. The ideal candidate would be a combination of a hands on developer who has some managerial experience, and who can understand existing automation test frameworks and has an ability to enhance and implement the same and should also be able to work with other engineers and product managers to support feature-based testing.

Responsibilities

• Build and implementation of robust automated test suites.
• Integration of automated test suites with the current build and deployment processes.
• Maintenance of automated tests to accommodate changes in system design and architecture.
• Integration of Automation framework with existing tools (JIRA).
• Create/Manage/Utilize Defect workflows with automated test execution.
• Design and publish meaningful metric to support automation test creation and execution.
• Build and implementation of performance test suites.
• Perform all types of testing – Functional. API, Automation, Performance and Load

Qualifications

• 8+ years of experience with QA engineering delivery experience
• 4+ years of delivery within Agile SDLC/teams ideally with CICD
• Programming experience in Java with focus on behavior driven development (BDD) and test-driven development (TDD) and design patterns, ideally within continuous integration (CICD)
• Experience with Java microservices and REST APIs and exposure to React front end
• Agile development approach
• Technologies: Java, JavaScript, IntelliJ/Eclipse
• CICD: Maven, Sonar, Git, Teamcity/Jenkins, Docker
• AI Integration experience preferred
• Exposure to banking and/or finance environments preferred
• Testing: Junit, Playwright, Protractor, JMeter or similar

The base salary range for this role is $110,000 to $145,000 depending on level.  iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO).  

We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday. Every department has different needs, and some positions will be designated in-office jobs, based on their function.

For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us  Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/ 

iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. 

Who You Are:

Working as part of the derivatives engineering team, you are an expert on data pipelining and API development. You have knowledge surrounding common derivatives pricing frameworks and inputs for different tradable assets, and how these inputs are derived. You also have experience with working with various backend technologies and have a detailed working knowledge of core software engineering concepts, such as garbage collection, asynchronous processing, and data structures. You have experience in using mathematical and financial libraries (i.e. SciPy, NumPy, QuantLib) in software engineering applications. You are also familiar with building deployment processes for applications, including unit testing, integration testing, and deployment to a cloud provider (EC2, Kubernetes). You have a curiosity for learning new technologies and expanding your expertise across business lines and technology stacks.

As a team member, you will also work on production support issues and be involved in improvements on CI/CD automation and DevOps. 

Knowledge of the following is an advantage:

• Python, Go, Java
• Derivatives Pricing Models (SABR, SVI)
• Kafka, AWS SQS, or MQ
• Relational and non-relational Databases (Postgres, SQL Server, Databricks)
• Time series databases
• Spark
• FastAPI, Pydantic
• Jenkins
• AWS
• Caching Strategies and Implementations
• In-Memory Data Management
• Experience with Docker

What You’ll Do:

• Work closely with the Derivatives trading desk in optimizing their trading and risk management tools, as well as building reusable derivatives pricing libraries and algorithms
• Embrace and champion the thoughtful adoption of AI to improve team performance and business outcomes.
• Leverage AI tools (e.g., generative AI, automation platforms, data copilots) to improve productivity, decision-making, and output quality in your day-to-day work.

What We’re Looking For: 

• 6+ years of professional experience working in software development
• Experience with building data pipelines, APIs, and reporting tools
• Experience in Financial Technology
• Strong knowledge of data structures, their implementations, and optimization techniques
• University degree in computer science, physics, engineering, or equivalent programming experience

Bonus Points: 

• Experience with LLM Finetuning and RAG Optimization
• Full lifecycle development of a commercial system, including: requirements definition, agile planning, releasing, and production support
• Experience in quantitative trading

What We Offer:

• Competitive base salary and discretionary bonus
• Hybrid/Flexible Working Arrangements 
• Flexible Time Off (paid)
• 3% 401(k) company contribution
• Company-paid health and protective benefits for employees, partners, and other dependents
• Generous paid Parental Leave
• Competitive family planning benefits for US employees 
• Opportunities to learn about the Crypto industry
• Smart, entrepreneurial, and fun colleagues
• Free daily snacks and weekly breakfasts/lunches 
• Employee Resource Groups
• Free coaching and counseling sessions through Headspace

Apply now and join us on our mission to engineer a new economic paradigm.

About Parloa

Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience, one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like Booking.com, HealthEquity, Allianz, SAP, BarmeniaGothaer, and TUI already deploying Parloa at scale.

About the role:

As a Forward Deployed Engineer, DevOps, your mission is to build and scale the dedicated infrastructure that powers our custom agent integrations for our most important customers. You will be the key technical cornerstone of our team, empowering our customer-facing Forward Deployed Engineers to build, deploy, and manage bespoke client solutions with speed and confidence. By creating a robust, automated, and self-service platform, you will directly enable the rapid delivery of high-quality, reliable custom services. 

Areas of ownership:

• Design, build, and maintain the cloud infrastructure specifically for hosting custom services developed by the Agent Integration Engineering team.
• Create flexible and reusable CI/CD pipeline templates that the integration team can easily adopt to automate the deployment of their services.
• Champion Infrastructure as Code to create standardized, yet customizable, service environments, ensuring consistency and rapid provisioning for new integrations.
• Manage a Kubernetes-based environment tailored for hosting a multitude of diverse integration services, focusing on security, isolation, and resource management.
• Implement robust monitoring and observability solutions to provide the integration team with deep visibility into the performance and health of their specific services.
• Serve as the primary DevOps partner for the Forward Deployed Engineering team, understanding their workflow, anticipating their needs, and removing infrastructure-related obstacles.
• Develop automation scripts (Python, Go, Bash) to streamline the entire lifecycle of custom integration services, from creation to decommissioning.
• Support and modernize legacy Azure infrastructure, helping transition workloads to a standardized, Kubernetes-based platform aligned with Parloa’s Engineering practices.

Who you are:

• 5+ years of professional experience in DevOps, infrastructure engineering, or a similar role.
• A strong customer-first mindset, viewing the Forward Deployed Engineering team as your primary customer.
• Proficiency in at least one scripting or programming language like Python, Go, or Bash.
• Hands-on expertise with a major cloud provider (AWS, GCP, or Azure).
• Advanced knowledge of containerization and orchestration, specifically Kubernetes, Helm, and Docker.
• Proven experience creating flexible CI pipelines with tools like Jenkins, GitHub Actions, or GitLab CI, and CD/GitOps workflows with tools like Argo CD.
• A strong background in Infrastructure as Code (Terraform is highly preferred).
• Experience building self-service tools and platforms that empower specific development teams.

Our recruiting process:

TA Screen → Hiring Manager Call → Technical Interview → Bar Raiser

Salary ranges includes OTE

Why Parloa?

We’re at the beginning of a new era in customer experience, one where AI doesn’t just respond, but understands, reasons, and takes action. We’re building agentic AI that enterprises trust with their most important customer moments: complex questions, high volumes, real stakes. When millions of people reach out to a brand, those interactions aren’t just support tickets; they’re defining experiences. We’re here to raise the standard: making every conversation seamless, intelligent, and genuinely helpful. If you care about shaping how businesses and customers connect at scale—and want your work to matter in real, everyday moments—this is where you do it.

At Parloa, ownership isn’t a buzzword; it means being accountable for outcomes, not just tasks. We operate in a category that’s evolving fast, where the bar is high, and the problems are complex. We hire people who think in solutions, communicate with clarity, and follow through. People who are comfortable making decisions, taking responsibility, and raising the standard for themselves and those around them.

We’ve grown beyond the earliest startup phase, but we’ve kept the intensity: fast execution, direct feedback, and a strong expectation to contribute meaningfully from day one.

Backed by leading global investors like General Catalyst, EQT Ventures, and Altimeter Capital, we’re scaling with a clear ambition: to become the global category leader in enterprise-grade conversational AI.

About Parloa

Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience, one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like Booking.com, HealthEquity, Allianz, SAP, BarmeniaGothaer, and TUI already deploying Parloa at scale. 

About the role:

As a Senior/Lead Forward Deployed Engineer (SFDE) at Parloa, you’ll be on the front lines of enterprise AI adoption - delivering cutting-edge technology into some of the most complex environments in the world. Your mission: lead end-to-end deployment projects from an engineering perspective - not just implementing what exists, but engineering what’s required to make it succeed at enterprise scale.

FDEs are our in-field product engineers. You will build what doesn’t yet exist, adapt architecture to enterprise realities, and engineer integrations across systems and APIs to make deployments successful. Your work is hands-on and code-first - you’ll be building, debugging, and engineering solutions directly in the field. What you ship not only makes deployments succeed, it also defines how customers experience Parloa and shapes what our product becomes.

This is not about maintenance. This is about engineering what makes it work in production, under real-world enterprise constraints, at speed and scale

Areas of ownership:

• Own deployment engineering projects: Lead the technical execution (incl. product engineering) of Parloa’s deployments inside large, complex enterprise environments
• Design for scale and resilience: Architect deployment solutions that meet enterprise-grade requirements for performance, reliability, and security
• Engineer solutions where none exist: Build custom extensions, integrations, and configurations to close product gaps and meet enterprise requirements
• Work across systems & stacks: Operate at the intersection of backend engineering, DevOps, and data engineering to ensure seamless delivery
• Partner with enterprise teams: Collaborate directly with customer engineering organizations to overcome constraints and deliver measurable outcomes
• Guide and mentor others: Collaborate with and provide technical guidance to more junior in-field engineers
• Influence at senior levels: Engage with enterprise architects and senior technical stakeholders, discussing solutions and architectures in depth to ensure alignment and credibility
• Debug under pressure: Rapidly unblock issues in mission-critical environments and ensure customer success.
• Shape the product: Act as the feedback loop between the field and our core engineering teams - turning deployment learnings into platform evolution
• Deliver long-term impact: Work closely with Deployment Strategists to ensure scalable architectures and durable customer value

Our Technology Stack: Python,TypeScript, Node.js, OpenAI, Microsoft Azure, Kubernetes, Docker, Terraform, MongoDB, MySQL, Redis, Kafka, MCP

Who you are:

• 7+ years of professional experience in software engineering, systems integration, DevOps, or data engineering roles with direct customer impact
• Proven track record of leading deep technical deployments and integrations in large-scale enterprise environments
• Strong technical depth across backend engineering, infrastructure-as-code, Kubernetes/cloud platforms, APIs, and databases - with proven experience in systems design and the ability to go hands-on in production systems
• Ability to operate independently in ambiguous, high-responsibility settings, especially when deploying live to enterprise systems
• A builder’s mindset with bias for action, creativity under pressure, and an obsession with making things work in the real world
• Degree in Computer Science, Engineering, or related technical field
• Strong plus: Experience building or integrating AI/LLM-powered systems (e.g., embedding agent workflows, vector databases, prompt orchestration)

Our recruiting process:

TA Screen → Hiring Manager Call → Technical Interview → Bar Raiser

Salary ranges include OTE

Why Parloa?

We’re at the beginning of a new era in customer experience, one where AI doesn’t just respond, but understands, reasons, and takes action. We’re building agentic AI that enterprises trust with their most important customer moments: complex questions, high volumes, real stakes. When millions of people reach out to a brand, those interactions aren’t just support tickets; they’re defining experiences. We’re here to raise the standard: making every conversation seamless, intelligent, and genuinely helpful. If you care about shaping how businesses and customers connect at scale—and want your work to matter in real, everyday moments—this is where you do it.

At Parloa, ownership isn’t a buzzword; it means being accountable for outcomes, not just tasks. We operate in a category that’s evolving fast, where the bar is high, and the problems are complex. We hire people who think in solutions, communicate with clarity, and follow through. People who are comfortable making decisions, taking responsibility, and raising the standard for themselves and those around them.

We’ve grown beyond the earliest startup phase, but we’ve kept the intensity: fast execution, direct feedback, and a strong expectation to contribute meaningfully from day one.

Backed by leading global investors like General Catalyst, EQT Ventures, and Altimeter Capital, we’re scaling with a clear ambition: to become the global category leader in enterprise-grade conversational AI.

Hi, we're Oscar. We're hiring an Applied AI Engineer to join our AI team.

Oscar is the first health insurance company built around a full stack technology platform and a focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the role

Join Oscar’s AI team to build and launch transformative AI-powered products that redefine the healthcare experience for millions. As an Applied AI Engineer, you’ll take end-to-end ownership of high-impact projects—conceiving, prototyping, and deploying generative AI solutions that solve real-world problems across the healthcare ecosystem.You’ll work alongside a world-class team of engineers and data scientists, rapidly iterating on ideas and shipping production-ready applications that drive measurable business and user outcomes. You’ll have the autonomy to identify opportunities, experiment with the latest AI models and techniques, and deliver solutions that streamline operations, improve patient experiences, and move the needle for Oscar and our members.

You will report to the Sr. Director, AI.

Work Location: This position is based in our New York City office, requiring a hybrid work schedule with 3 days of in-office work per week. Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid

Pay Transparency: The base pay for this role is: $180,504 - $236,911 per year. You are also eligible for employee benefits, participation in Oscar’s unlimited vacation program, company equity grants, and annual performance bonuses.

Responsibilities

• Lead the design, development, and deployment of AI-driven products and features, from zero-to-one prototypes to robust production systems.
• Collaborate cross-functionally with product, design, and business teams to deeply understand user needs and deliver solutions that move key metrics.
• Rapidly experiment with new models, techniques, and tools (including LLMs, RAG, and agentic workflows), iterating based on data and user feedback.
• Build and scale full-stack applications and intelligent agents that automate complex healthcare workflows and deliver seamless user experiences.
• Stay on the cutting edge of the AI ecosystem, evaluating and integrating emerging technologies to keep Oscar at the forefront of healthcare innovation.
• Contribute to Oscar’s AI strategy and technical vision, helping shape the future of healthcare through technology.
• Other duties as assigned

Qualifications

• 7+ years of professional experience in software engineering, data science, or a related field, with a track record of impactful accomplishments
• Strong Python programming skills
• Experience solving complex, ambiguous problems 
• Experience designing and analyzing experiments or evaluations
• Experience or an interest in prototyping full-stack applications

Bonus Points

• Experience with the healthcare industry. Familiarity with claims or clinical data.
• Degree in math, statistics, data science, or engineering.
• Our ideal candidate is a data scientist with an engineering background, an engineer with a data science background, or a founder-type who combines product thinking, rapid prototyping, and hands-on coding to deliver real-world impact.
• Experience with NLP, neural networks, transformers, and modern AI frameworks.
• Knowledge of containerization and deployment tools (e.g., Docker, Kubernetes) or full-stack development (e.g., React, Golang).
• Experimental mindset: comfort with testing hypotheses and iterating on failures.

Location: Hybrid (Local to NYC area)

About the team

The Platform team at Capital Rx is made up of a set of passionate, motivated, and driven individuals who are not only experts in technologies but are great problems solvers and brings high energy and inspiration every day. The team always works a sense of ownership and urgency delivering highest quality of work ensuring seamless operations and fostering collaboration across the software engineering department. We own the architecture, framework & standards, infrastructure and CI/CD pipelines which development teams utilize to deliver code to Captial Rx’s Judi® platform. The team is also responsible for the production environment which requires knowledge with monitoring, alerting and on-call practices. The Platform team performs many functions whether that is tactical operations, providing general solutions for the enterprise or giving guidance or recommendations for individual product teams.

Position Summary:

We are a rapidly growing late-stage health tech company helping millions of lives through our innovative product Judi. We’re seeking a highly skilled and experienced Senior Platform Developer II to join our platform team. This pivotal role will be instrumental in building, scaling, and maintain the robust and secure infrastructure that powers our mission-critical platform.

You will be a force multiplier, enabling our development teams to deliver features faster and more reliably. You will champion infrastructure-as-code principles, contribute code to platform scalability, drive automation across the entire software development lifecycle, and ensure our platform meets the highest standards of scalability, performance, and security.

Position Responsibilities:

• Architect, implement, and maintain highly available, scalable, and secure platform & infrastructure
• Develop and maintain robust automation pipelines for continuous delivery (CI/CD), and infrastructure provisioning tools like GoCD, Harness, and Terraform
• Write clean, efficient, and well-tested Python code for automation, tooling and service development.
• Manage and optimize relational or in-memory databases, including PostgreSQL, Redshift and Redis, ensuring high performance, reliability, and data integrity.
• Administer and finetune container orchestration platforms such EKS and ECS.
• Implement and manage serverless architectures leveraging AWS Lambda for various platform functionalities.
• Collaborate closely with development teams to ensure infrastructure aligns with application requirements and best practices.
• Lead efforts in defining and enforcing security best practices across the platform, including adherence to HIPAA standards, FISMA, SOC II, and FedRAMP compliance standards.
• Monitor systems performance, identify bottlenecks, and implement proactive solutions to ensure optimal operation and scalability.
• Participate in on-call rotations to provide operational support and incident response.
• Champion Agile/Scrum methodologies, actively participating in sprint planning, stand-ups, and retrospectives.
• Mentor junior developers and contribute to a culture of technical excellence and continuous improvement.
• Evaluate and recommend new technologies and tools to enhance platform capabilities and efficiency.
• Develop internal tooling and automation scripts using Python and work with SQL to support operational workflows.
• Implement observability (monitoring/logging/alerting) best practices for highly available SaaS services.
• Responsible for adherence to the Capital Rx Code of Conduct including reporting of noncompliance.

Requirements

• 8+ years of experience as a Platform Engineer, DevOps Engineer, or Site Reliability Engineer.
• Deep expertise in AWS infrastructure and services including but not limited to EC2, Lambda, ECS, EKS, RDS, S3, VPC, CloudWatch, SQS, SNS, IAM, Kinesis
• Excellent proficiency with Terraform, Python, SQL, and automation tooling.
• Extensive experience with Docker and container orchestration (Kubernetes/EKS).
• Solid understanding and hands-on experience with SQL, database administration (PostgreSQL preferred), and performance tuning
• Experience with CI/CD systems (e.g., GoCD, GitHub Actions, Harness).
• Proven experience in automating Observability & Monitoring (Grafana, Kibana, Prometheus), standardizing incident response for alerts to maintain SLAs and SLOs
• Hands-on experience in environments compliant with FISMA, SOC 2, and/or FedRAMP.
• Background in building highly scalable, performant SaaS platforms.
• Excellent communication, collaboration and problem-solving skills.
• Ability to work effectively with cross-functional teams, including developers, IT security & compliance, product manager, and scrum masters.
• Strong experience in production on call rotations and responding to alerts.

This position description is designed to be flexible, allowing management the opportunity to assign or reassign duties and responsibilities as needed to best meet organizational goals.

Location: Preferably Hybrid (Local to NYC area) or Remote (For Non-Local)

About the team

The Platform team at Capital Rx is made up of a set of passionate, motivated, and driven individuals who are not only experts in technologies but are great problems solvers and brings high energy and inspiration every day. The team always works a sense of ownership and urgency delivering highest quality of work ensuring seamless operations and fostering collaboration across the software engineering department. We own the architecture, framework & standards, infrastructure and CI/CD pipelines which development teams utilize to deliver code to Captial Rx’s Judi® platform. The team is also responsible for the production environment which requires knowledge with monitoring, alerting and on-call practices. The Platform team performs many functions whether that is tactical operations, providing general solutions for the enterprise or giving guidance or recommendations for individual product teams.

Position Summary:

We are a rapidly growing late-stage health tech company helping millions of lives through our innovative product Judi. We’re seeking a highly skilled and experienced Platform Developer to join our platform team. This pivotal role will be instrumental in building, scaling, and maintain the robust and secure infrastructure that powers our mission-critical platform.

You will be a force multiplier, enabling our development teams to deliver features faster and more reliably. You will champion infrastructure-as-code principles, contribute code to platform scalability, drive automation across the entire software development lifecycle, and ensure our platform meets the highest standards of scalability, performance, and security.

Position Responsibilities:

• Develop and support highly available, scalable, and secure platform & infrastructure
• Develop and maintain robust automation pipelines for continuous delivery (CI/CD), and infrastructure provisioning tools like GoCD, Harness, and Terraform
• Write clean, efficient, and well-tested Python code for automation, tooling and service development.
• Manage and optimize relational or in-memory databases, including PostgreSQL, Redshift and Redis, ensuring high performance, reliability, and data integrity.
• Administer and finetune container orchestration platforms such EKS and ECS.
• Implement and manage serverless architectures leveraging AWS Lambda for various platform functionalities.
• Collaborate closely with development teams to ensure infrastructure aligns with application requirements and best practices.
• Contribute to defining and enforcing security best practices across the platform, including adherence to HIPAA standards, FISMA, SOC II, and FedRAMP compliance standards.
• Monitor systems performance, identify bottlenecks, and implement proactive solutions to ensure optimal operation and scalability.
• Participate in on-call rotations to provide operational support and incident response.
• Adopt Agile/Scrum methodologies, actively participating in sprint planning, stand-ups, and retrospectives.
• Evaluate and recommend new technologies and tools to enhance platform capabilities and efficiency.
• Develop internal tooling and automation scripts using Python and work with SQL to support operational workflows.
• Implement observability (monitoring/logging/alerting) best practices for highly available SaaS services.

Requirements

• 5+ years of experience as a Platform Engineer, DevOps Engineer, or Site Reliability Engineer.
• Strong expertise in AWS infrastructure and services including but not limited to EC2, Lambda, ECS, EKS, RDS, S3, VPC, CloudWatch, SQS, SNS, IAM, Kinesis
• Excellent proficiency with Terraform, Python, SQL, and automation tooling.
• Extensive experience with Docker and container orchestration (Kubernetes/EKS).
• Solid understanding and hands-on experience with SQL, database administration (PostgreSQL preferred), and performance tuning
• Experience with CI/CD systems (e.g., GoCD, GitHub Actions, Harness).
• Proven experience in automating Observability & Monitoring (Grafana, Kibana, Prometheus), standardizing incident response for alerts to maintain SLAs and SLOs
• Hands-on experience in environments compliant with FISMA, SOC 2, and/or FedRAMP.
• Background in building highly scalable, performant SaaS platforms.
• Excellent communication, collaboration and problem-solving skills.
• Ability to work effectively with cross-functional teams, including developers, IT security & compliance, product manager, and scrum masters.
• Strong experience in production on call rotations and responding to alerts.

This position description is designed to be flexible, allowing management the opportunity to assign or reassign duties and responsibilities as needed to best meet organizational goals.

About the Role

The Onsite Customer Growth team develops features that help Attentive’s customers grow through personalized experiences built directly on their websites. We focus on increasing list growth through investments in creative capabilities, experimentation, and AI-driven optimization. Our team builds the systems and product experiences that power onsite engagement for millions of users and help brands convert more visitors into subscribers and customers.

We’re looking for a Senior Software Engineer to help lead the design and development of the products and platform capabilities behind Attentive’s onsite growth experiences. This role can be oriented toward backend or full-stack engineering, depending on your strengths, but in either case you’ll be expected to own meaningful technical decisions, build scalable systems, and collaborate closely with product, design, data, and AI partners to deliver high-impact customer outcomes.

This hybrid role is based in our New York office, with in-office collaboration Tuesday through Thursday each week.

What You’ll Accomplish

• Design, build, and evolve scalable backend services, APIs, and user-facing product capabilities that power Attentive’s onsite growth products.
• Lead technical design for new features and platform improvements, making thoughtful tradeoffs around reliability, performance, maintainability, and speed of execution.
• Partner closely with product, design, AI, and data teams to develop intelligent, data-driven capabilities that improve performance and user experience for customers and end users.
• Anticipate future product and platform needs, and proactively design solutions that support team growth, product expansion, and increasing scale.
• Improve system observability, resiliency, and performance to ensure our onsite experiences remain fast, reliable, and effective at scale.
• Serve as a technical leader on the team by driving design discussions, raising the engineering bar in code reviews, and mentoring other engineers.
• Contribute to a strong engineering culture through high-quality implementation, pragmatic architecture, and a focus on measurable customer impact.

Your Expertise

• 5+ years of professional software engineering experience, ideally with strong experience building backend systems, product platforms, or customer-facing applications at scale.
• Strong proficiency in at least one modern programming language such as Java, or TypeScript
• Experience designing and operating distributed systems, APIs, and microservices, with a solid understanding of reliability, scalability, and performance.
• For backend candidates: deep experience building service-oriented systems and data-intensive applications.
• For full-stack candidates: strong backend fundamentals plus experience building high-quality frontend applications and collaborating closely on end-user experience.
• Experience with cloud infrastructure and modern developer tooling, such as AWS, Docker, Kubernetes, relational databases, caching systems, queues, or streaming platforms.
• Ability to translate business goals and product ideas into clear technical plans and execute effectively across functions.
• A track record of writing clean, maintainable, well-tested code and holding a high bar for production quality.
• Curiosity, strong collaboration skills, and a passion for building products that drive meaningful customer growth.

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $170,000 - $230,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-AB2

By applying for this position, your data will be processed as per Attentive's Privacy Policy.

About the Role
The Onsite Customer Growth team builds the features that help Attentive’s customers grow directly on their websites. Our mission is to accelerate list growth and improve conversion by delivering creative, high performing onsite experiences powered by strong engineering and intelligent AI driven optimization.

What You’ll Accomplish

• Lead, mentor, and grow a high performing engineering team responsible for building the backend systems powering onsite customer growth products
• Set the technical vision and roadmap for backend services, APIs, and data driven systems that power personalized onsite experiences at scale
• Partner closely with AI, data, and product teams to develop intelligent capabilities that improve performance and user experience
• Ensure the reliability, scalability, and performance of the systems that support customer growth and real time user interactions
• Drive best practices in design discussions, code reviews, architecture decision making, and operational excellence
• Foster a learning oriented team culture that encourages collaboration, curiosity, ownership, and continuous improvement
• Own delivery of key product initiatives, balancing long term platform investments with near term business objectives
• Promote clean, maintainable, well tested code and high engineering standards across the team

Your Expertise

• 7+ years of professional backend software engineering experience, including at least two years managing or leading engineers
• Strong proficiency in one or more modern programming languages such as Java, or Typescript
• Experience designing and operating distributed systems, APIs, and microservice architectures at scale
• Hands on familiarity with cloud platforms such as AWS and containerization technologies such as Docker or Kubernetes
• Deep understanding of databases, messaging systems, or streaming technologies such as PostgreSQL, Redis, or Kafka
• Track record of building reliable, scalable, high throughput systems that support customer facing products
• Demonstrated ability to coach and develop engineers, drive team alignment, and create an inclusive, collaborative engineering environment
• Strong communication and cross functional partnership skills, with the ability to work effectively with AI, data, product, and design teams
• A mindset rooted in ownership, curiosity, and a passion for building meaningful systems that drive measurable customer impact

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $193,000 - $250,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-MN1

By applying for this position, your data will be processed as per Attentive's Privacy Policy.

About the Role

The New York Times is looking for a Software Engineer to join our Scoop Core team. Our mission is to empower product teams with a modern platform that serves as the single source for all content.

Our platform enables teams to manage and evolve content schemas quickly and safely, while also providing the foundation for building user-friendly collaborative editing and publishing tools.

We use GraphQL for Schema Definition and queries, Golang for development and PostgreSQL for data storage. We host our platform services on AWS. We also maintain the existing legacy publishing platforms that are hosted on GCP.

You will report to the Senior Engineering Manager, Scoop Core.

Responsibilities:

• Take on multiple technical tasks not limited to programming, such as working with Cloud services, platforms and APIs
• Research and document proposed solutions
• Write unit tests, integration tests and user documentation
• Assist other teams to onboard to our platform
• Maintain existing legacy systems
• Collaborate and learn through pairing, design reviews, and code reviews
• Collaborate with Product Management and other professionals within your team and across the organization
• Demonstrate support and understanding of our value of journalistic independence and a commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• You have 2+ years of experience building large-scale software applications
• You have experience building backend systems
• You have hands-on unit and integration testing experience
• You have experience communicating updates and resolutions to customers and cross-functional partners

Preferred Qualifications:

#LI-Hybrid

REQ-019826

About the Role

The Reflections team at The New York Times is looking for a Backend Software Engineer. You will be part of a diverse team that includes native mobile engineers, web/backend engineers, QA, product managers, designers and data experts.

The Reflections team focuses on personalizing the Times experience, making it feel "yours." We aim to help users effortlessly discover and regularly engage with the journalism they value most, strengthening. and deepening their relationship with the Times.

This role is hybrid, located at our New York City headquarters, and typically requires coming into the office two days per week.

Responsibilities:

• Collaborate with design, product, web, backend, and native mobile engineers to refine requirements and develop new features across our platform.
  
  
• Design, build, and maintain backend services primarily in Go (Golang), developing scalable REST or GraphQL APIs and writing high-quality, production-ready code following engineering best practices.
  
  
• Develop and improve Go-based services and microservices, integrating with databases, internal systems, and cloud infrastructure.
  
  
• Contribute ideas that help shape the direction of our products and actively participate in solving meaningful technical challenges.
  
  
• Participate in technical discussions and architecture decisions with native mobile, web, and backend engineers, as well as owners of internal and external dependencies.
  
  
• Work across multiple parts of the stack when needed while maintaining a strong focus on backend service development in Go.
  
  
• Provide production support by participating in on-call rotations for the services and systems we build.
  
  
• Contribute to iteration on internal team processes and norms.
  
  
• Demonstrate support and understanding of our value of journalistic independence and a commitment to our mission to seek the truth and help people understand the world.
  
  
• You will report to the Engineering Manager
  
  

Basic Qualifications:

• 3+ years of full-time experience developing backend APIs using Go (Golang), including building REST or GraphQL services in production environments. Experience with additional backend technologies such as TypeScript, Node.js, or Express is a plus.
  
  
• 3+ years of experience working with SQL or NoSQL databases, such as PostgreSQL or DynamoDB, including designing schemas, writing queries, and integrating data storage with backend services.
  
  
• 3+ years of experience building and deploying services on public cloud platforms, such as Google Cloud Platform (GCP) or Amazon Web Services (AWS).
  
  
• Experience working in Agile software development environments, collaborating with cross-functional teams through iterative development, testing, and release cycles.

Preferred Qualifications:

• Familiarity with GraphQL.
  
  
• Familiarity with containers and container orchestration systems like Kubernetes, Docker.
  
  
• Familiarity with CI/CD techniques and tooling (e.g. Jenkins, drone), automated testing and deployments, and other DevOps practices.
  
  
• Understanding of caching and content delivery.
  
  

This role will require limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables. This role also requires availability to our core working hours which are 10am - 6pm ET.

#LI-Hybrid

REQ-019607

About the Role

The New York Times is looking for a Senior Software Engineer, with a focus on ML platform development, to join our Machine Learning & AI team to help solve creative challenges around Machine Learning infrastructure.

Machine Learning (ML) at the New York Times enhances the experience of our 150 million digital readers from around the globe and grows our subscriber base through content recommendations and personalizations.

The Machine Learning & AI team builds and maintains the infrastructure that hosts all of The New York Times real-time ML inference models, including both data and compute. Our partners are Data Scientists that build and deploy their ML models on the ML platform. On the other end, our partners are engineering systems that call these hosted models at scale with low-latency and Service Level Agreements (SLAs) guaranteed by our platform.

This role is a hybrid role, based in New York City. You will report to the Engineering Manager of the Machine Learning Platform team.

Responsibilities:

• You will research, develop, and deploy infrastructure for the Machine Learning Platform that supports large-scale multi-tenant workloads

• You will build a platform to train and test algorithms that provide real-time content recommendations and personalization to our readers

• You will enhance ML platform's CI/CD and integration testing capabilities

• You will build a platform that supports the full Machine Learning workflow; from model training, testing and production deployment at high scale and low latency

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world

Basic Qualifications:

• 5+ years of direct relevant experience in MLOps or DevOps, including experience operating large systems in a production environment

• Experience deploying and monitoring systems using cloud infrastructure (GCP or AWS)

• Experience working with Kubernetes, Docker, and CI/CD (Drone, Argo, Jenkins, etc)

• Experience leading the development of large-scale, data-driven, distributed multi-tenant systems

• Proficiency with at least one high-level programming language like Python or Go

Preferred Qualifications:

• Experience with any of the these technologies: Terraform, Airflow, SQL/BigQuery, BigTable or other NoSQL datastores such as Cassandra, DynamoDB, Redis

• Familiarity with ML tooling such as Triton, TensorFlow, scikit-learn

• Experience building the infrastructure that power real-world machine learning applications like recommendation systems, bandits, etc.

• Experience engaging with partners to understand pain points, observe patterns, and identify opportunities for improvements

This role requires limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

REQ-019502

#LI-hybrid

About the Role

Machine Learning (ML) at the New York Times enhances the experience of our 150 million digital readers from around the globe and grows our subscriber base through content recommendations and personalizations.

The Machine Learning Platform (MLP) team builds and maintains the infrastructure that hosts all of The New York Times real-time ML inference models, including both data and compute. Our partners are Data Scientists that build and deploy their ML models on the ML platform. On the other end, our partners are engineering systems that call these hosted models with low-latency and Service Level Agreements (SLAs) guaranteed by the MLP.

We are looking for a Software Engineer, with a focus on MLOps, to join our Machine Learning Platform team to help solve creative challenges around Machine Learning infrastructure for the New York Times.

This role is a hybrid role, based in New York City. You will report to the Engineering Manager of the Machine Learning Platform team.

Responsibilities:

• You will research, develop, and deploy infrastructure for the Machine Learning Platform at scale

• You will build infrastructure to train and test algorithms that provide real-time content recommendations and personalization

• You will enhance ML platform's CI/CD and integration testing capabilities

• You will promote developer productivity by rolling out capabilities that maximize self-sufficiency and minimize the toil in learning those capabilities in building scalable applications with high speed, quality, and performance

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world

Basic Qualifications:

• 2+ years of direct relevant experience in MLOps or DevOps, including experience operating large systems in a production environment

• Experience deploying and monitoring systems using cloud infrastructure (GCP or AWS)

• Experience working with Kubernetes, Docker, and CI/CD

• Familiarity with at least one high-level programming language like Python or Go

Preferred Qualifications:

• Experience with any of the these technologies: Terraform, Airflow, SQL/BigQuery, Drone, Triton, TensorFlow, scikit-learn, DataDog

• Experience building real-world machine learning applications like recommendation systems, bandits, etc.

• Experience engaging with stakeholders to understand pain points, observe patterns, and identify opportunities for improvements

This role may require limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

REQ-019501

#LI-Hybrid

About the Role

The Quality Engineering team at The New York Times is hiring a QA Engineer. You will work with software engineers, DevOps, product managers, and designers to support quality across our web, mobile, and API platforms.

You will develop automated test frameworks, strengthen CI/CD reliability, and improve release confidence through scalable automation practices.

This role is hybrid and based in New York City, with an expectation of two days per week in the office. You will report to the Senior QA Manager.

Responsibilities:

• Design automated testing frameworks in Python for APIs, web, and mobile applications
• Develop and integrate automated test workflows into CI/CD pipelines
• Improve test reliability, execution speed, and coverage across environments
• Develop scalable test environments using containerization and cloud infrastructure
• Collaborate with engineering, DevOps, and product teams to define test strategies early in the development lifecycle
• Integrate logging, monitoring, and metrics into testing workflows to improve defect detection and release confidence
• Contribute to documentation and standards for automation and TestOps

Basic Qualifications:

• 3 years of experience in test automation, software engineering, or quality engineering
• Proficiency in Python and experience building maintainable automation frameworks
• 3 years of experience with modern test automation tools such as PyTest, Playwright, Selenium, or Appium
• 3 years of experience testing REST, GraphQL, or gRPC APIs
• Hands-on experience integrating automated tests into CI/CD pipelines (e.g., GitHub Actions, Jenkins, GitLab CI)
• 3 years of experience with Docker and familiarity with Kubernetes
• 3 years of experience working in cloud environments (AWS, GCP, or Azure)

Preferred Qualifications:

• Experience with mobile test automation
• Experience with test environment provisioning and infrastructure-as-code
• Familiarity with AI-assisted coding tools (e.g., GitHub Copilot, Cursor, Claude) in software development workflows
• Experience improving observability or quality metrics within engineering teams

#LI-Hybrid

REQ-019672

About the Role:

Machine Learning (ML) at the New York Times enhances the experience of our 150 million digital readers from around the globe and grows our subscriber base through content recommendations and personalizations.

The Machine Learning & AI team builds and maintains the infrastructure that hosts all of The New York Times real-time ML inference models, including both data and compute. Our partners are Data Scientists that build and deploy their ML models on the ML platform. On the other end, our partners are engineering systems that call these hosted models at scale with low-latency and Service Level Agreements guaranteed by our platform.

As an MLOps Engineer you will partner with product, data science and ML platform engineers to build and maintain the infrastructure that powers the machine learning lifecycle. You will automate and refine the training, deployment, monitoring, and management of our ML models.

This role reports to the Senior Engineering Manager of Data Management Infrastructure.

Responsibilities:

• Build and Automate ML Pipelines: by owning robust CI/CD pipelines for automated model training, validation, deployment, and retraining.

• Productionalize Models: Build the process for packaging, containerizing, and deploying ML models as scalable, low-latency, and highly-available services.

• Monitoring and Operations: Implement and manage comprehensive monitoring for production models, tracking system health, data drift, and model performance degradation.

• Tooling and Infrastructure: Manage and evolve our MLOps toolchain, including model registries, feature stores, experiment tracking systems, and model serving platforms.

• Collaboration and Support: Partner with data scientists to understand model requirements and optimize them for production. Support software engineers in integrating with ML services.

• Best Practices and Governance: Champion and enforce MLOps best practices for reproducibility, versioning (data, code, model), testing, and governance.

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• 2+ years of software engineering or DevOps experience with a focus on MLOps, automation, and infrastructure

• 2+ years of experience programming in Python or Go

• Experience building and managing CI/CD pipelines (e.g., Github Actions, Jenkins, GitLab CI)

• Hands-on experience with containerization and orchestration (e.g., Docker, Kubernetes)

• Cloud platform experience (AWS, GCP) and familiarity with infrastructure-as-code (e.g., Terraform, CloudFormation)

Preferred Qualifications:

• Experience with MLOps tools (e.g., MLflow, Kubeflow)

• Experience with the machine learning model lifecycle, from experimentation to production

• Experience with data processing frameworks (e.g., Spark, Dask, or Ray)

• Experience with low-latency no-sql datastores (BigTable, Dynamo, etc)

• Familiarity with monitoring and observability stacks (e.g., Prometheus, Grafana, Datadog, or ELK)

• Knowledge of data engineering pipelines and orchestration tools (e.g., Airflow, Prefect)

REQ-019522

#LI-hybrid

About the Role, Mission or Department Overview

The New AI Products and Platforms mission is a central hub for new, high-ambition AI opportunities and services at The Times. We are hiring a Senior Software Engineer to help build the backend services and infrastructure that will form our internal AI Platform.

This platform will enable teams across the company to build, deploy, and manage applications that use large language models (LLMs) to advance our journalism and our business. You will report to the Director of AI Platforms and work with a team of engineers, designers, product and project managers, data scientists, and newsroom stakeholders to make investments in AI possible across The Times.

This is a hybrid position based in our New York City headquarters. You can typically expect to come into the office two days per week.

Responsibilities:

• Design, build, and maintain scalable and reliable backend services and APIs for a central platform used by teams building AI applications across our journalism and our business.

• Take ownership of core platform components and integrations, including systems for prompt and workflow management, evaluation and tracing, and monitoring for cost, usage, and performance.

• Build and operate vector database and retrieval infrastructure to support search and AI-powered discovery experiences.

• Design and develop retrieval-augmented generation (RAG) pipelines and agentic workflows that connect our content, data, and AI models.

• Build orchestration layers for multi-step AI workflows, managing the coordination of LLM calls, retrieval, and business logic.

• Develop the infrastructure that enables teams to create and manage their AI applications, complete with metadata, observability, and access controls.

• Architect and implement data pipelines and storage solutions to support our AI systems.

• Write high-quality, maintainable, and well-tested code, primarily in backend languages like Python or Go.

• Ensure a high degree of code quality, security, and system observability.

• Collaborate with editorial, product, ML, and data teams to translate requirements into platform capabilities.

• Review code written by other software engineers on the team and provide feedback.

• Contribute to and advocate for robust testing strategies to ensure service reliability.

• Be a mentor to other software engineers to enable their growth.

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• 5+ years of software engineering experience, with a strong focus on backend development.

• 5+ years of experience in one or more backend programming languages such as Python or Go.

• 5+ years of experience designing, building, and operating distributed systems and APIs at scale.

• 1+ years of experience building applications with Large Language Models (LLMs) and familiarity with the surrounding ecosystem (e.g., orchestration, retrieval-augmented generation).

Preferred Qualifications:

This role requires limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

#LI-Hybrid

REQ-019837

Octus is seeking a Principal Data Engineer to roll up their sleeves and build scalable, production-grade data pipelines and infrastructure. You'll be a hands-on technical leader — writing code daily, solving hard engineering problems, and helping elevate the team around you through doing. Spanning Snowflake, Databricks, and AWS, you'll be deeply involved in the day-to-day development of the data platform that powers Octus's products, data, and automation initiatives. The ideal candidate is an expert in Python and SQL who thrives in an execution-focused environment and has deep experience building modern data pipelines and lakehouse solutions.

Responsibilities

• Build and maintain end-to-end data pipelines — from raw ingestion through transformation and delivery — across diverse data sources (APIs, web data, internal feeds, etc.).
• Hands-on development of scalable, production-grade pipelines within Databricks, including Delta Lake table management, Workflows, and cluster optimization.
• Build and maintain data models, schemas, and transformation logic in Snowflake, optimizing for performance and reliability.
• Develop and manage Databricks environments including Unity Catalog, Delta Live Tables, and integration patterns that support both internal data consumers and external sharing use cases.
• Build and manage orchestration workflows using AWS services (MWAA/Airflow, Lambda, ECS, SQS, MSK) and Databricks-native orchestration where appropriate.
• Implement and maintain infrastructure as code (IaC) using Terraform, ensuring reproducibility and compliance with cloud standards.
• Establish and enforce best practices in data modeling, schema design, and ETL/ELT processes for high-volume structured and semi-structured data across Snowflake and Databricks.
• Ensure data quality, lineage, and observability through automated testing, monitoring, and alerting across all pipeline layers.
• Collaborate closely with technology leadership to align data platform development with business strategy and product goals.
• Stay at the forefront of industry trends in data engineering, lakehouse architecture, and cloud-native data platforms.

Requirements

• Strong foundation in software engineering principles, including SOLID design, modularity, and scalability.
• Expert proficiency in Databricks, including Delta Lake, Unity Catalog, Delta Live Tables, MLflow, and Databricks Workflows.
• Deep experience with Snowflake, including data modeling, performance optimization, and integration with upstream/downstream pipeline tooling.
• Expert proficiency in Python for data pipeline and automation development.
• Advanced SQL skills with experience optimizing complex queries and data models at scale.
• Proven experience designing and maintaining cloud-native data pipelines on AWS (e.g., MWAA/Airflow, Lambda, ECS, SQS, Glue, S3, Redshift, etc.).
• Experience implementing and managing Terraform or similar IaC frameworks.
• Strong understanding of lakehouse architecture patterns, data ingestion, transformation, and orchestration, including familiarity with ML/AI pipeline integration patterns.
• Familiarity with CI/CD pipelines, automated testing, and modern DevOps practices.
• 8+ years of experience in data engineering or backend development, with a focus on scalable data solutions.
• Demonstrated experience leading data infrastructure projects end-to-end and mentoring senior engineers.
• Familiarity with containerization (Docker) and workflow orchestration best practices.
• Excellent communication, collaboration, and problem-solving skills.

Nice to Have

• Experience with streaming data technologies (Kafka, Kinesis, Flink).
• Exposure to ML/AI pipeline patterns (feature stores, experiment tracking, model serving) and MLOps tooling, particularly in a cross-functional team environment.
• Experience integrating data quality and observability tools.
• Experience with Databricks as a data sharing and collaboration platform (Delta Sharing, Marketplace).
• Familiarity with Claude Code or similar AI-powered developer tools for accelerating pipeline development and code workflows.

At Octus, we consider a range of factors in connection with compensation decisions, including experience, skills, location, and our business needs and limitations. As a result, compensation may vary within and across similar roles and positions. Please note that the salary range information below is a good faith estimate for this position and actual compensation for any individual may fall outside this range if warranted by the circumstances applicable to that individual. If we identify a role that would be suitable for a broader range of skills and experience such that we would consider hiring at multiple levels then the range listed below may reflect that breadth.

The salary range estimate for this position is $175,000 - $220,000

The actual compensation will be at Octus' sole discretion and will be determined by the aforementioned and other relevant factors.

Octus delivers breaking news and market-moving intelligence through cutting-edge data and technology for hedge funds, investment banks, and law firms- and we’re transforming how professionals access complex and opaque information. As part of our high-performing AI Innovation team, you’ll help design, build, and productionize modern GenAI and LLM-powered systems that support both client-facing features and internal operational efficiency. You’ll work end to end—from shaping ambiguous problems into scalable solutions to deploying reliable AI models in production - collaborating closely with product, engineering, and infrastructure teams. This is a hybrid role based in NYC (3 days in office per week). Curious about what we’re building? Check out our flagship GenAI product, CreditAI here and our AI framework here.

Responsibilities

• Apply strong problem-solving and critical thinking skills to break down complex, ambiguous requirements into clear, implementable technical components and system designs.
• Design, build, and maintain AI-powered and data-driven systems with a focus on modern language and multimodal models, including LLM-driven applications, RAG pipelines, and agentic workflows.
• Evaluate and productionize commercial and open-source LLMs, choosing appropriate models, tools, and techniques for each use case. Develop multi-step agentic workflows that incorporate tools, external data sources, memory, and control logic.
• Manage the orchestration of production LLM workflows and agentic systems, ensuring reliability and efficiency through prompt routing, state management, retries, fallbacks, and error handling. Design, test, and iteratively refine prompts and system instructions using prompt engineering and tuning techniques to improve model reliability, accuracy, and task performance.
• Maintain production-grade code and services with automated monitoring and performance tracking, using metrics and alerts to guide continuous improvements in models, prompts, and pipelines.
• Apply systems thinking to design and optimize AI and LLM systems, balancing quality, scalability, latency, cost, and operational complexity, while implementing efficiency improvements using model selection, prompt design, batching, caching, and retrieval strategies.
• Define and implement evaluation and observability frameworks for AI systems, including automated testing, task-specific benchmarks, regression testing for prompts, human-in-the-loop validation, and performance monitoring.
• Build and integrate AI models into backend systems and APIs to support both real-time and batch inference, ensuring solutions are production-ready, scalable, and efficient.
• Apply NLP and ML techniques to tasks such as information extraction, semantic search and retrieval, text classification, summarization, and reasoning over text and documents.
• Collaborate closely with engineering and infrastructure teams to deploy solutions using containerized and cloud-based environments (e.g., GitHub, Docker, AWS), applying modern deployment and infrastructure practices.
• Collaborate with product managers, business stakeholders, and domain experts to translate complex, ambiguous business problems into actionable technical solutions, and communicate progress, trade-offs, and outcomes to relevant stakeholders.
• Continuously learn and adapt to advancements in NLP and Generative AI to ensure solutions remain innovative and effective.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
• 3+ years of experience as a Data Scientist, Machine Learning Engineer, or applied AI practitioner, with a strong foundation in computer science, algorithms, and software development. 
• Advanced programming skills in Python, with experience building production-grade systems beyond research or experimentation.
• Solid understanding of machine learning and applied AI concepts, with experience taking solutions from prototype to production.
• Hands-on experience designing, building, and deploying LLM-driven or GenAI applications, including familiarity with vector databases, embeddings pipelines, or semantic search systems.
• Practical experience with cloud-based deployments and infrastructure tools (e.g., AWS, Docker, GitHub) and an understanding of modern DevOps practices, containerization, orchestration, caching strategies, and cost-aware design.
• Strong problem-solving skills and systems thinking, with the ability to balance trade-offs across model quality, scalability, inference latency, cost, and operational complexity.
• Ability to interpret and implement research ideas and algorithms, actively contributing to research and development initiatives while translating them into production solutions.
• Excellent communication and collaboration skills, with experience working closely with product managers, engineers, and domain experts to deliver actionable technical solutions.
• Passion for learning and staying current with the rapidly evolving AI/ML landscape, including emerging best practices for GenAI applications.
• Strong ownership and initiative, with the ability to independently drive projects from problem definition to delivery, while being a team player and contributing to the overall success of the data science team.

At Octus, we consider a range of factors in connection with compensation decisions, including experience, skills, location, and our business needs and limitations. As a result, compensation may vary within and across similar roles and positions. Please note that the salary range information below is a good faith estimate for this position and actual compensation for any individual may fall outside this range if warranted by the circumstances applicable to that individual. If we identify a role that would be suitable for a broader range of skills and experience such that we would consider hiring at multiple levels then the range listed below may reflect that breadth.

The salary range estimate for this position is $130,000-$145,000.

The actual compensation will be at Octus’ sole discretion and will be determined by the aforementioned and other relevant factors. This position is eligible for a performance-based annual bonus.

As a DevOps Engineer at Octus, you will play a crucial role in the development, implementation, and maintenance of the cloud infrastructure for our products. This position involves close collaboration with Application Developers, Data Engineers, SRE, Security, and IT professionals to automate and streamline operations and processes. Your contributions will be essential in ensuring the reliability, scalability, and security of our systems and applications.

Core Responsibilities:

• Design, implement, and maintain CI/CD pipelines to automate the build, test, and deployment processes.
• Effectively prioritize workload with a constant focus on increasing developer efficiency.
• Manage and optimize cloud infrastructure to ensure scalability, performance, and cost-effectiveness. Experience with AWS is a plus.
• Work closely with SRE to develop and maintain monitoring and alerting systems to ensure the health and performance of our systems and applications.
• Work closely with Security to implement and enforce security best practices across our infrastructure and applications.
• Collaborate with software developers to optimize application performance and reliability.
• Participate in the planning and execution of disaster recovery and business continuity strategies.
• Effectively communicate with stakeholders to provide updates on project statuses, issues, and recommendations.
• Participate in on-call rotation to provide system support.

Core Requirements:

• At least 5 years of experience in a DevOps role.
• At least 2+ years of experience with Terraform.
• Expert knowledge of cloud concepts and services (EC2, ECS, S3, RDS, A/ELB, EBS, VPC, Route53 or equivalent).
• Expert level knowledge of Linux. Strong scripting skills for automation and tooling.
• Ability to troubleshoot, diagnose, resolve & document RCA of incidents.
• Good knowledge of database configuration, concepts, maintenance, and troubleshooting.
• Thorough understanding of Security principles and experience in designing, implementing, monitoring proper controls.
• Extensive experience with Infrastructure-as-code & configuration management tools (Terraform, SaltStack or equivalent).
• Experience with containerization technologies such as Docker and orchestration tools like Kubernetes, ECS including managing microservices architectures.
• Knowledge of CI/CD tools such as Jenkins, Github Actions or equivalent.
• Experience with monitoring and logging tools such as Datadog, Cloud Watch or equivalent.
• Excellent communication skill, with the ability to effectively collaborate with cross-functional teams.

At Octus, we consider a range of factors in connection with compensation decisions, including experience, skills, location, and our business needs and limitations. As a result, compensation may vary within and across similar roles and positions. Please note that the salary range information below is a good faith estimate for this position and actual compensation for any individual may fall outside this range if warranted by the circumstances applicable to that individual. If we identify a role that would be suitable for a broader range of skills and experience such that we would consider hiring at multiple levels then the range listed below may reflect that breadth.

The salary range estimate for this position is $165,000 - $190,000.

The actual compensation will be at Octus' sole discretion and will be determined by the aforementioned and other relevant factors.

#LI-Hybrid

P15407_3389736

The Opportunity

Auth0’s platform is the front door for thousands of customers and millions of users. On the Platform Engineering team, we build the resilient foundations that enable customers to rely on Auth0 for always-on authentication and authorization services.

As the Senior Manager of Data Streaming Services, you will lead the evolution of our streaming data backbone across a multi-cloud footprint. You will oversee multiple engineering teams dedicated to making data streaming seamless, reliable, and high-performance. This is a "manager of managers" role requiring a blend of strategic foresight, execution rigor, and technical grit. You will set the vision for our streaming services, mentor high-performing teams, and take accountability for our service uptime guarantees.

What you’ll achieve

• Lead a world-class team of teams. Oversee data streaming infrastructure and services that power our global platform across AWS and Azure.
• Own roadmap and execution. Partner with product and stakeholder teams to define the team's strategy and prioritized roadmap.
• Drive engineering excellence. Set high standards of quality, reliability, and operational robustness, championing best practices in software development, from code reviews to observability and incident management.
• Lead an automation-first culture. Reduce operational friction and ensure infrastructure is self-healing and code-defined. Draw efficiency from AI-assisted development.
• Act as a technical leader. Lead response on incidents for services under ownership and help teams navigate complex distributed systems failures.

What you’ll bring

• Proven engineering leadership, building and leading teams of teams. Experience coaching Staff+ engineers and engineering managers.
• Strong technical and architectural acumen. Background in building scalable, distributed systems. Comfortable participating in and guiding technical discussions.
• Strong project management skills. Expertise in creating technical roadmaps, prioritizing effectively in an agile environment, and managing complex project dependencies.
• Collaborative leadership style, adapted to remote ways of working. Excellent written and verbal communication skills to build strong relationships with stakeholders and inspire others.

Bonus Points

• Experience developing data-intensive applications in a modern programming language such as go, node.js, or Java.
• Experience with databases such as PostgreSQL and MongoDB.
• Experience with distributed streaming platforms like Kafka.
• Familiarity with concepts in the IAM (Identity and Access Management) domain.
• Experience with cloud providers (AWS, Azure), container technologies such as Kubernetes and Docker, and observability tools such as Datadog.
• Experience building reliable, high-availability platforms for enterprise SaaS applications.

#LI-Hybrid

P15407_3389736

The Solutions Engineer Team

We believe Solutions Engineers at Okta are involved in all stages of the customer’s digital transformation.  Solutions Engineers are experienced in using presentations, email, phone, and social media to connect with customers virtually and in person. We are looking for great teammates who can build and deliver sales presentations and customized product demonstrations to educate Okta’s Customers (from developers to product managers to C-level executives) on best practices throughout their cloud security technology journey. 

We believe Okta’s Solutions Engineers empathize with Customers and quickly discern their true technical needs by asking detailed, clarifying questions while presenting solutions that specifically address those needs. Okta Solution Engineers have the rare combination of technical acumen and business insight; in a career where you can utilize both. As a Solutions Engineer at Okta, you will further develop each of these skills by advising a diverse set of customers on the value they will gain by using Okta’s Identity Platform.

The Solutions Engineer Opportunity

Reporting to the Senior Manager, Solutions Engineers, this Senior Solutions Engineer (Okta) will partner with Commercial Account Executives. As a Senior Solutions Engineer at Okta, you will be the technical lead in all stages of the customer lifecycle. You will focus on delivering customer value by aligning customer requirements to business results enabled by Okta solutions. You will contribute to account and opportunity strategies and, collaboratively, demonstrate the value of Okta solutions through presentations, whiteboard sessions, and proof-of-concept demonstrations.

What You’ll Do

As a Senior Solutions Engineer, you’ll be a strategic technical expert for a customer-facing sales team. You'll use your skills to:

• Work alongside the Corporate/Expansion (employee size 300-1249) sales team as the technical and domain expert of a customer-facing sales team to help Customers understand the value of Okta’s solutions
• Serve as a technical advisor: Partner with the sales team to educate customers on Okta’s identity solutions and demonstrate their value.
• Solve customer challenges: Understand customer needs and provide tailored product demonstrations to show how our solutions can solve their business problems.
• Lead technical engagements: Answer product and technical questions, and plan and deliver complex Proofs of Concept (POCs) by collaborating with other Okta engineering teams.
• Drive product and knowledge growth: Share customer feedback with our product teams to influence future enhancements and contribute to the team's knowledge by sharing best practices and reusable assets.
• Stay ahead of the curve: Keep up with competitive analysis and market differentiation to better position Okta.
• Support company events: Represent Okta at marketing events, including conferences, user groups, and trade shows.

What You’ll Bring

• Experience: 8+ years of experience in pre-sales engineering and solution selling, with a strong background in Enterprise account segments.
• Technical Acumen:
• Deep understanding of identity protocols (e.g., SAML, OIDC, OAuth, FIDO, Passkeys, SCIM, LDAP).
• Working knowledge of cloud platforms like AWS, Azure/Entra, and GCP.
• Experience with REST APIs and SDKs.
• Hands-on experience in one or more of the following: front-end web development, back-end development, scripting (Bash, PowerShell), or DevOps (Docker, Kubernetes).
• Understanding of identity-related cybersecurity topics (e.g., phishing, MFA bypass attacks, privilege escalation).
• Communication & Presentation Skills: The ability to simplify complex technical concepts and deliver compelling presentations to diverse audiences, from developers to C-level executives. You should be skilled at diagramming user journeys and complex architecture.
• Strategic Mindset: Proven skills in territory management, including building pipelines and collaborating with sales counterparts.
• Travel: Ability to travel up to 25% of the time.
• A bachelor's degree in Engineering, Computer Science, MIS, or a comparable field is preferred.

Bonus Skills (Ideally, You Have)

• Experience in the IAM space
• Hands-on knowledge of Identity Governance (IGA) or Privileged Access Management (PAM) solutions.
• Practical experience with Windows Server, Active Directory, LDAP, and Federation services.

You might also have (not mandatory):

• AI & Emerging Tech: Expertise with Agentic AI and LLM-based workflows. You understand the use cases for AI agents, both internal and external, and have familiarity with MCP servers.
• Diagramming experience for user journey flows, complex architecture diagrams, etc.

#LI-Remote

#LI-CM

P10563_3394826

About the role:

We are looking for a Staff Software Engineer to join our team and help us develop the core systems powering our clinical research. You will work closely with a talented product and data science team, stay up-to-date with the latest technologies, and contribute to a fast-paced, innovative environment. The ideal candidate for this role should be able to deliver across the tech stack and is eager to learn and apply new techniques and technologies.

Where you will work:

This role will be based in our New York City office (in the Financial District). You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday.

What you will do:

• Design and build extensible systems that can grow with the business needs
• Collaborate across disciplines to understand our domain and iterate on new ideas
• Lead technical strategy and decision-making
• Protect our users’ privacy and security through secure coding practices

What you will bring to the team:

• 7+ years hands-on work delivering full-stack software
• Excellent communication skills and ability to clearly communicate design rationale and concepts
• Familiarity with Python, React, NodeJS, Docker, and AWS
• Excellent understanding of SQL and data modeling
• Familiarity building scalable data pipelines, query optimization, data modeling, and defining reusable datasets
• Experience working in a team using agile methodologies and fluency with the agile toolkit
• Experience mentoring team members and acting as a technical multiplier
• A willingness to “roll up your sleeves” and do whatever is necessary to ensure company success
• A desire to be a part of a high-performing, mission-driven team that operates with intense urgency, a strong sense of individual accountability, and a commitment to authentic feedback

Technologies we use: 

• Claude Code, Kubernetes, AWS, Airflow, dlt, dbt, Python, TypeScript, React, Go

This is a unique opportunity to join a fast-growing company in a transformative role, helping shape the future of healthcare.

Compensation Transparency:

The target salary range for this position is $240,000 - $285,000. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k), Teladoc Health and more.

The financial industry is growing at a record pace, but our data providers are still stuck in the past — with cumbersome onboarding processes, complicated APIs, slow infrastructure, and expensive licensing costs.

Databento is the next generation market data provider — with the radical idea that you should only pay for the data that you use. We power the world's largest finance and fintech institutions and lower the barrier of entry for small startups, gaining over 4,000 users during our first year of launch. Our team brings former experience at the world's leading quantitative firms, including Two Sigma, Flow Traders, Tower Research, PDT Partners, SIG, and more.

We offer health, dental, disability, and life insurance benefits, as well as 401(k) matching for full-time employees. We accommodate 100% remote work, with teammates living around the globe and paid in their local currency.

Responsibilities

• Systems and network configuration.
• Bare-metal and containerized application deployment.
• Maintaining large storage clusters.
• Instrumenting performance measurement and alerts.
• Improving systems automation and tooling.
• On-call support.
• Coordinating bulk data delivery to customers and vendor partners.
• Occasional physical infrastructure deliveries and systems provisioning.

Required qualifications

• Strong Linux knowledge.
• Experience with systems configuration and provisioning (PXE, Puppet, and Ansible preferred; Terraform).
• Understanding of storage concepts (RAID, LVM, popular filesystems, distributed storage).
• Basic networking (OSI model, IP protocols, switching/routing).
• Ability to code in Python and write shell scripts.
• DevOps/GitOps mindset.
• Prior internship experience or 2+ years in full-time systems engineering or infrastructure roles.
• Bachelor’s degree in Computer Science or a related field.
• Candidates must be authorized to work in the U.S.; H-1B visa sponsorship is not available.

Nice-to-haves

• Experience with distributed storage systems (e.g., Ceph).
• Customer support experience and strong problem-solving abilities.
• Prior experience at a trading or fintech firm, or a strong interest in learning fintech.
• Database administration (MySQL, ClickHouse, Redis).
• Cloud engineering basics (AWS, GCP — compute, storage).
• Virtualization and compute workloads (Proxmox, Docker, Kubernetes, HTCondor).
• Systems and network tuning.
• Monitoring and alerting (Prometheus, Grafana, Alertmanager, Loki).
• Ability to travel to data centers in New Jersey or Boston on short notice (within one week).

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Lyft is looking for software engineers from a scope of disciplines. We are growing our team with people who want to build, improve and incorporate technologies that make the lives of our community more enriched. As an engineer at Lyft, you'll collaborate with teams like product, design, data science, analytics, and operations on code that empower us to iterate quickly, while focusing on delighting our passengers and drivers.

The Rider organization is focused on building a seamless, best-in-class rideshare experience for riders. From the foundational functionality of requesting a ride to the tailored interactions with your flight, we sweat the small stuff to help make Lyft the best transportation solution. As a Senior Software Engineer on the Rider Team, you will work hand in hand with various teams across Lyft, fostering collaboration, and driving innovation to improve riders' experience with rideshare.

Responsibilities:

• Write well-crafted, well-tested, readable, maintainable code
• Participate in code reviews to ensure code quality and distribute knowledge 
• Participate in our teams on-call rotation. Identify, triage, debug and resolve issues/bugs across our various applications and platforms
• Have the ability to explain the various trade offs made in decisions
• Manage project priorities, deadlines, and deliverables.
• Partner with product managers, designers, data scientists and other engineering teams to build complex features and products from idea to positive execution
• Analyze our internal systems and processes and locate areas for improvement/automation
• Share your knowledge by giving brown bags, tech talks, and promoting appropriate tech and engineering best practices
• Provide technical mentorship and feedback to junior engineers
• Help establish roadmap and architecture based on technology and our needs

Experience:

• BS/MS or equivalent in Computer Engineering, Computer Science, or related field or equivalent practical experience
• 5+ years of software engineering industry experience
• Solid knowledge of distributed systems, relational and NoSQL databases
• Experience designing, debugging and running fault-tolerant, highly available, large-scale distributed systems
• Experience working with public cloud platforms (e.g., AWS, GCP, Microsoft Azure, etc.)
• Experience working with kubernetes and container technologies (e.g. Docker, cri-o, etc)
• Ability to work with a low-ego, highly collaborative, and cross-functional team

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the New York City area is $148,000 - $185,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

About the Role

Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand.

Developer Productivity owns the end-to-end experience of how engineers and researchers at Anthropic develop, build, test, and ship code at scale — from the source control and language ecosystems that underpin our monorepo, to the build and CI infrastructure that keeps thousands of daily builds running reliably across multiple cloud providers, to the developer acceleration tooling that deeply integrates Claude into engineering workflows.

Team Matching: Team matching is determined after the interview process based on interview performance, interests, and business priorities. Please note we may also consider you for different Infrastructure teams. 

Responsibilities:

• Own the technical strategy and roadmap for your area, translating team-level goals into concrete execution plans
• Define infrastructure architecture, ensuring the hardest problems get solved — whether by you directly or by working through others
• Design and build scalable, reliable distributed infrastructure and shared libraries that support high-volume workloads across all engineering teams
• Own and evolve build environments, package management, and dependency systems to enable fast, reproducible builds
• Define and implement language ecosystem standards, tooling, and frameworks that drive developer productivity across research and production workloads

You may be a good fit if you:

• Have deep experience with build systems, CI/CD pipelines, and/or developer tooling in a large monorepo environment
• Have strong proficiency in Python, Rust and/or Go
• Are obsessed with developer productivity and reducing friction in the software development lifecycle
• Have experience with container orchestration and infrastructure at scale
• Have excellent communication skills and enjoy supporting internal partners to improve their development experience
• Are excited about designing foundational systems and are comfortable working independently on ambiguous, high-impact technical challenges

Strong candidates may have:

• 15+ years (not including internships or co-ops) of experience in a Software Engineer role, building and operating large-scale developer infrastructure
• 3+ years (not including internships or co-ops) of experience leading large scale complex projects or teams as a tech lead
• Experience with CI orchestration tools (Buildkite, Jenkins, GitHub Actions, or similar) and merge queue management at scale
• Experience building or operating remote build execution systems (Bazel Remote Execution API, BuildBarn, BuildBuddy, or similar)
• Experience with Nix/NixOS/Docker and managing large image / package sets at scale
• Experience building CLI tools, developer-facing services, and GitHub API and automation workflows

Deadline to apply: None. Applications will be reviewed on a rolling basis.

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

The responsibilities of our Platform team include building and maintaining all backend services, including, but not limited to, payments, analytics, subscriptions, new products, text to speech, and external APIs.

This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, is passionate about making product decisions, and has experience building great user experiences that delight users.

We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount. 

Our interview process involves several technical interviews and we aim to complete them within 1 week. 

What You’ll Do

• Design, develop, and maintain robust APIs including public TTS API, internal APIs like Payment, Subscription, Auth and Consumption Tracking, ensuring they meet business and scalability requirements
• Oversee the full backend API landscape, enhancing and optimizing for performance and maintainability
• Collaborate on B2B solutions, focusing on customization and integration needs for enterprise clients
• Work closely with cross-functional teams to align backend architecture with overall product strategy and user experience

An Ideal Candidate Should Have

• Proven experience in backend development: TS/Node (required)
• Direct experience with GCP and knowledge of AWS, Azure, or other cloud providers
• Efficiency in ideation and implementation, prioritizing tasks based on urgency and impact
• Preferred: Experience with Docker and containerized deployments
• Preferred: Proficiency in deploying high availability applications on Kubernetes

What We Offer

• A dynamic environment where your contributions shape the company and its products
• A team that values innovation, intuition, and drive
• Autonomy, fostering focus and creativity
• The opportunity to have a significant impact in a revolutionary industry
• Competitive compensation, a welcoming atmosphere, and a commitment to an exceptional asynchronous work culture
• The privilege of working on a product that changes lives, particularly for those with learning differences like dyslexia, ADD, and more
• An active role at the intersection of artificial intelligence and audio – a rapidly evolving tech domain

The United States Based Salary range for this role is: 140,000-200,000 USD/Year + Bonus + Stock depending on experience

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.

What You’ll Do

• Be scrappy to find new sources of audio data and bring it into our ingestion pipeline
• Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.
• Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.
• Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team’s dataset roadmap to power Speechify’s next-generation consumer and enterprise products.

An Ideal Candidate Should Have

• BS/MS/PhD in Computer Science or a related field.
• 5+ years of industry experience in software development.
• Proficiency with bash/Python scripting in Linux environments
• Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)
• Experience with web crawlers, large-scale data processing workflows is a plus
• Ability to handle multiple tasks and adapt to changing priorities.
• Strong communication skills, both written and verbal.

What we offer

• A fast-growing environment where you can help shape the company and product.
• An entrepreneurial-minded team that supports risk, intuition, and hustle.
• A hands-off management approach so you can focus and do your best work.
• An opportunity to make a big impact in a transformative industry.
• Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
• Opportunity to work on a life-changing product that millions of people use.
• Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
• Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.

Compensation: The United States base salary range for this full-time position is $140,000-$200,000 + bonus + equity depending on experience

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

What You’ll Do:

CoreWeave is seeking a highly skilled and motivated Systems Kernel Engineer to join our HAVOCK Team, reporting into the Manager of Systems Engineering. In this role, you will be a key contributor to the stability, performance, and evolution of CoreWeave’s Linux based infrastructure. As a kernel generalist, you will be responsible for debugging kernel-level issues, analyzing and fixing crashes, panics, dumps, and upstreaming fixes and features that improves the performance and reliability of our stack.

This position is ideal for someone who thrives in low-level systems engineering, and understands how modern workloads stress kernels, and is excited to work across a diverse hardware/software ecosystem including CPUs, GPUs, DPUs, networking, and storage.

Kernel Hardware - Acceleration - Virtualization - Operating Systems - Containerization - Kubelet

Our Team’s Stack:

• Python, Go, bash/sh, C
• Prometheus, Victoria Metrics, Grafana
• Linux Kernel (custom build), Ubuntu
• Intel/AMD/ARM CPUs, Nvidia GPUs, DPUs, Infiniband and Ethernet NICs
• Docker, kubernetes (k8s), KubeVirt, containerd, kubelet

Focus Areas:

• Kernel Debugging – Analyze kernel crashes, oopses, panics, and dumps to identify root causes and propose fixes.
• Upstream Contributions – Develop patches for the Linux kernel and upstream them where applicable (networking, storage, virtualization, GPU/DPU enablement).
• Stack-Wide Support – Ensure kernel support and stability across:
• Virtualization (KubeVirt, QEMU, vFIO)
• Container runtimes (containerd, nydus, kubelet)
• HPC/AI workloads (CUDA, GPUDirect, RoCE/InfiniBand)
• Kernel-Hardware Enablement – Support new hardware bring-up across Intel, AMD, ARM CPUs, NVIDIA GPUs, DPUs, and NICs.
• Performance & Stability – Tune kernel subsystems for latency, throughput, and scalability in distributed HPC/AI clusters.

About the role:

• Triage and fix kernel crashes and performance regressions.
• Develop, test, and upstream kernel patches relevant to CoreWeave’s hardware/software environment.
• Collaborate with hardware vendors and the Linux community on feature enablement.
• Implement diagnostics and tooling for kernel-level observability.
• Work closely with HPC and Fleet teams to ensure kernel readiness for production workloads.
• Provide kernel-level expertise during incident response and root-cause investigations.

Who You Are:

• 5+ years of professional experience in Linux kernel engineering or systems-level development.
• Deep understanding of kernel internals (memory management, scheduling, networking, storage, drivers).
• Experience debugging kernel crashes, dumps, and panics using tools like crash, gdb, kdump.
• Strong C programming skills with the ability to write maintainable and upstream-quality code.
• Experience working with kernel modules, drivers, and subsystems.
• Strong problem-solving abilities with a “full-stack” systems perspective.

Preferred:

• Contributions to the Linux kernel or related open-source projects.
• Familiarity with virtualization (KVM, QEMU, VFIO) and container runtimes.
• Networking stack expertise (InfiniBand, RoCE, TCP/IP performance tuning).
• GPU/DPU bring-up and driver experience.
• Experience in HPC or large-scale distributed systems.
• Familiarity with QA/QE best practices
• Experience working in Cloud environments
• Experience as a software engineer writing large-scale applications
• Experience with machine learning is a huge bonus

The base salary range for this role is $165,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). 

What You’ll Do
Our Solutions Architecture team at Weights & Biases is a unique hybrid organization, combining the deep technical skills of Site Reliability Engineering with the consultative expertise of Solutions Architecture. We focus on ensuring customers can successfully deploy and operate W&B across cloud and on-prem environments while delivering a best-in-class experience that accelerates ML adoption at scale.

About the Role
As a Solutions Architect, you will be responsible for managing complex customer deployments across AWS, GCP, Azure, and on-prem environments. You’ll partner directly with customer engineering teams to provision and monitor services, debug and resolve infrastructure issues, and ensure performance and scalability using SRE best practices. This role blends hands-on technical problem-solving with customer-facing engagement, including technical discussions, demos, workshops, and enablement content creation. You’ll work closely with Sales Engineering, Field Engineering, Support, and Product to drive adoption and influence our product roadmap based on customer feedback.

Who You Are

• Proven track record of systematically diagnosing and resolving infrastructure issues
• Experience in a customer-facing technical role
• Expertise in Docker, Kubernetes, Helm charts, networking, and cloud-managed services (e.g., MySQL, Object Stores)
• Strong fundamentals in Infrastructure as Code (IaC), preferably Terraform
• Proficiency with at least one cloud platform (AWS, GCP, Azure); experience across multiple platforms is a plus
• Strong Linux/Unix command line experience
• Basic proficiency in Python and familiarity with ML workflows or tools

Preferred

• Deep proficiency in Kubernetes design patterns, including Operators
• Familiarity with data engineering and MLOps tooling
• Experience as an educator or facilitator for technical training sessions, workshops, or demos
• SaaS, web service, or distributed systems operations experience

Wondering if you’re a good fit?
We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• You love diving into infrastructure problems and solving them systematically
• You’re curious about how to scale complex ML systems in production environments
• You’re an expert in building and running containerized, distributed systems

Why Us?
We work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The base salary ranges for this role is $180,000 to $200,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

About the Role:

SysEng HAVOCK (Hardware - Acceleration - Virtualization - Operating Systems - Containerization - Kernel)

CoreWeave is looking for a Senior Systems Engineer who is ready to evolve beyond traditional DevOps. You will start by stabilizing and scaling our Linux OS and Kernel build pipelines. Once the foundation is set, you will lead the transition to AI-native infrastructure, building "smart" workflows that don't just report errors, but understand and fix them.

You are a Systems Engineer at heart, but you are ready to apply LLMs, RAG, and predictive modeling to solve infrastructure challenges at scale.

Our Team’s Stack:

• Languages: Python, Go, bash/sh
• Observability: Prometheus, Victoria Metrics, Grafana
• OS & Kernel: Linux Kernel (custom build), Ubuntu
• Hardware: Intel/AMD/ARM CPUs, Nvidia GPUs, DPUs, Infiniband and Ethernet NICs
• Containerization: Docker, Kubernetes (k8s), KubeVirt, containerd, kubelet

Responsibilities:

• Pipeline Architecture: Design, maintain, and automate reproducible OS image build pipelines for our massive fleet of GPU-accelerated servers.
• Kernel Distribution: Collaborate with kernel engineers to package, validate, and distribute custom Linux builds across Intel, AMD, and ARM architectures.
• Dependency Management: Build tooling to manage dependencies, versioning, and release workflows, ensuring hermetic builds.
• Telemetry & Metrics: Standardize the collection of build metrics to create a baseline for future AI modeling.
• "Smart" CI/CD & Auto-Remediation: Architect AI agents that ingest and analyze build logs in real-time. Develop systems that auto-triage errors, categorize failure patterns, and generate context-aware fix suggestions for engineering teams.
• Predictive Regression Modeling: Design ML workflows that utilize historical performance data to detect kernel and OS regressions (latency, throughput, stability) in staging environments before they impact production.
• Dynamic Kernel Tuning: Implement closed-loop feedback systems that analyze real-time system metrics and automatically suggest or apply sysctl parameter optimizations for specific customer workloads.
• Next-Gen ChatOps: Engineer LLM-driven interfaces for Slack/internal tools, enabling stakeholders to query build statuses, request log summaries, or provision resources using natural language commands.

Requirements:

• 4+ years of professional experience in Linux Systems Engineering, Release Engineering, or DevOps.
• Deep knowledge of Linux internals (boot process, kernel modules, networking stack).
• Experience with package management (Debian/Ubuntu) and build systems.
• Strong proficiency in Python (essential for the AI integration aspects of this role).
• Demonstrable experience integrating API-based AI models (OpenAI, Anthropic, or local open-source models) into software workflows.
• Understanding of RAG (Retrieval-Augmented Generation) architectures for querying technical documentation or logs.
• Experience building event-driven automation (e.g., using webhooks to trigger analysis agents).
• Familiarity with data structures required for vector search or time-series analysis.
• Bachelor’s degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field.

Nice-to-haves:

• Experience with Kubeflow or MLFlow.
• Background in High-Performance Computing (HPC).
• Experience fine-tuning small language models (SLMs) for code or log analysis tasks.

The base salary range for this role is $153,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

What You’ll Do:

The Applications Engineering team in the Data Infrastructure organization builds AI-native analytics platforms and first-party applications that embed governed data directly into operational workflows. The team develops CoreWeave’s internal data-native software products, transforming data into operational capability through intelligent interfaces, automation, and decision systems. This includes AI-native analytics platforms (e.g., UNION) and mission-critical applications such as capacity planning and scenario modeling. These systems encode CoreWeave’s differentiated operating knowledge into software, enabling scalable, data-driven decision-making across the business.

About the role:

As a Senior Software Engineer, you will design and build production-grade, full-stack applications that make data accessible, actionable, and embedded within CoreWeave’s core workflows. You will develop AI-enabled user experiences, scalable backend services, and intuitive interfaces that abstract away the complexity of underlying data systems. Day-to-day, you’ll work across the stack - from React-based frontends to backend services running on Kubernetes - while integrating AI/LLM capabilities into real-world applications. This role offers high visibility and the opportunity to directly influence how data is consumed and operationalized across the company.

Who You Are: 

• 7+ years of experience building production-grade software applications, including both backend services and modern web frontends
• Strong proficiency in backend programming languages (Python, Go, Java, C#) and frontend programming languages (JavaScript, TypeScript)
• Strong experience building modern frontend applications using frameworks such as React and Next.js
• Hands-on experience with containerization and deployment tooling (e.g., Docker, Helm)
• Experience building and operating APIs and services (e.g., REST, gRPC) with a focus on performance and reliability
• Experience developing and deploying AI/ML/LLM-powered applications in production environments
• Familiarity with data platforms and tools (e.g., Spark, Kafka, or similar systems) and integrating them into application workflows
• Experience implementing software development best practices, including CI/CD, automated testing, observability, and secure application design
• Ability to take ownership of complex systems end-to-end, from design through deployment and iteration

Preferred: 

• Experience building AI-native applications such as text-to-SQL interfaces, copilots, or automated insight-generation systems
• Experience designing and building scalable, distributed systems deployed in cloud-native environments (e.g., Kubernetes)
• Familiarity with real-time data processing or streaming architectures
• Experience building internal platforms or tools that enable self-service analytics or decision-making 

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk. 

• You love building user-facing applications that turn complex data into intuitive experiences
• You’re curious about applying AI to real-world problems, not just prototypes
• You’re an expert in designing and shipping systems that are both scalable and usable

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!  

The base salary range for this role is $165,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

What You’ll Do:

We are seeking a Senior Platform Engineer to join our Kubernetes Infrastructure team. This role involves administering our critical multi-tenant Kubernetes platforms and collaborating with development teams to establish proper deployment architectures. The ideal candidate will have a strong background in resilient kubernetes application architecture and deployment.

About the role:

• Champion reliability initiatives for Kubernetes application deployments: Advocate for best practices to ensure high availability, scalability, and resilience of applications in Kubernetes, focusing on robust testing, secure pipelines, and efficient resource use.
• Administer multi-tenant Kubernetes platforms: Manage complex multi-tenant Kubernetes clusters, configuring access, quotas, and security for isolation and optimal resource allocation while upholding SLAs.
• Perform lifecycle and day 2 operations on clusters: Execute Kubernetes cluster lifecycle, including provisioning, patching, monitoring, backup, disaster recovery, and troubleshooting.
• Deep dive into reliability issues: Conduct in-depth analysis and root cause identification for complex reliability incidents in Kubernetes, utilizing advanced debugging and monitoring tools to propose preventative measures.
• Perform on-call duties: Respond to critical alerts and incidents outside business hours, providing timely resolution to minimize disruptions, collaborating with teams, and communicating clearly.

Who You Are:

• Bachelor's in CS, Engineering, or related field, or equivalent experience preferred.
• CKA or similar certifications is highly desired.
• 5+ years administering multi-tenant SAAS Kubernetes (EKS, AKS, GKS).
• Strong Gitops/Devops with Argocd or similar helm chart management.
• Proven Docker and containerization experience.
• Strong Linux OS experience.
• Proficient in Go.
• Excellent problem-solving, debugging, and analytical skills.
• Strong communication and collaboration.

Preferred:

• Master's degree in Computer Science, Engineering, or a related field.
• Experience with performance profiling and optimization of distributed systems.
• Knowledge of network protocols and distributed consensus algorithms.

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!  

The base salary range for this role is $165,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). 

What You’ll Do:

The Customer Experience (CX) Organization at CoreWeave is dedicated to ensuring every client running AI workloads at scale has a seamless, reliable, and high-performance experience. This team supports the infrastructure that powers the AI revolution—working across data centers, hardware systems, and customer workloads to maintain the integrity of our cloud platform. The CX organization aligns closely with the internal and customer engineering teams, offering valuable insights from the field and having the chance to contribute to the CoreWeave product roadmap and development. 

About the role:

As the Infrastructure Operations Program Manager, you will be responsible for operationalizing and scaling CoreWeave’s bare-metal support program globally, initially focusing on the team’s data program. You will lead a pivotal function, serving as the liaison between clients, internal teams, and external vendors to ensure effective data analysis and reporting. You will drive data-first management of client relationships and enable cross-functional partnerships to improve new and existing operational processes and tools.

In this role, you will:

• Own and evolve data processes and tooling across all support workflows, including break/fix, incident response, maintenance, RMA, and customer escalations.
• Drive operational insights through data, improving how we collect, structure, and analyze information to surface trends, enforce accountability, reduce repeat issues, and proactively report on program performance.
• Partner cross-functionally with engineering, operations, vendors, and customers to align on data definitions, reporting standards, and workflow instrumentation.
• Partner with data teams to build and maintain scalable data models and reporting layers, working with both structured and unstructured data to create reliable tables, views, and dashboards.
• Transform ad hoc processes into standardized workflows, enabling consistent tracking and measurement across regions, vendors, and customers.
• Develop and operationalize key metrics and dashboards, including backlog, SLA adherence, resolution time, vendor performance, and overall program health.
• Enable a metrics-driven operating model, helping the organization transition toward data-informed decision-making, faster time-to-resolution, and improved customer experience.
• Continuously identify gaps and opportunities in tooling, reporting, and workflows, and lead initiatives to improve operational efficiency and visibility.
• Fill additional scope of operational program management as the team’s needs shift and evolve.

Who You Are

• 3+ years of program or operations management experience in cloud infrastructure, datacenter operations, or high-performance computing environments.
• Strong ability to bridge operations and data, with hands-on experience in support environments, data analysis, reporting, and visualization across multiple systems and sources.
• Experience working with support or service delivery environments (e.g., ticketing systems, incident management, escalation workflows).
• Proficiency in working with structured and unstructured data, including building datasets, defining metrics, and ensuring data quality and consistency.
• Demonstrated ability to design and implement scalable processes and workflows, turning ambiguity into repeatable, measurable systems.
• Familiarity with cloud computing concepts, containerization, and/or infrastructure hardware environments.
• Working knowledge of hardware troubleshooting and datacenter operations is a strong plus.
• Excellent communication and stakeholder management skills, with the ability to work effectively across technical and non-technical teams, including external partners.
• Proven problem-solving mindset, with the ability to operate effectively in fast-paced, evolving environments.
• Experience creating clear, customer-facing reports and documentation that translate operational data into actionable insights.
• Applicants must have work authorization that does not require sponsorship now or in the future.

Wondering if you’re a good fit? We believe in investing in our people and value candidates who bring unique backgrounds—even if you don’t check every box. Here are a few qualities we’ve found make someone successful on our team. If some of this describes you, we’d love to talk.

• You’re curious about Kubernetes, Docker, and containerized infrastructure
  
  
• You have strong problem-solving skills with a proactive and analytical mindset.
  
  
• You have excellent communication skills and a demonstrated ability to work collaboratively in a fast-paced environment.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
  
  
• Act Like an Owner
  
  
• Empower Employees
  
  
• Deliver Best-in-Class Client Experiences
  
  
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! 

The base salary range for this role is $122,000 to $179,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). 

What you'll do:

CoreWeave is seeking a highly skilled and motivated HPC Performance Engineer to join our HAVOCK Team, reporting into the Manager of Systems Engineering. In this role, you will play a crucial part in the design, development, and optimization of our bare-metal systems from POST through joining a Kubernetes cluster. The team’s primary responsibilities include maintaining a custom Linux kernel, various OS images (Ubuntu-based), the virtualization stack (kubevirt/qemu/vfio), and the container/pod runtime stack (containerd/nydus/kubelet). You will collaborate closely with cross-functional teams, up stack engineering teams, and stakeholders to ensure our low-level software stack is performant in the context of hardware updates; and providing data, metrics, dashboards, and analysis to substantiate performance assertions.

Kernel Hardware - Acceleration - Virtualization - Operating Systems - Containerization - Kubelet

Our Team’s Stack:

• Python, Go, bash/sh, C
• Prometheus, Victoria Metrics, Grafana
• Linux Kernel (custom build), Ubuntu
• Intel/AMD/ARM CPUs, Nvidia GPUs, DPUs, Infiniband and Ethernet NICs
• Docker, kubernetes (k8s), KubeVirt, containerd, kubelet

About the role:

• Develop and maintain tools for establishing systems performance baselines 
• Develop and maintain performance regression analysis testing automation
• Design and maintain performance regression test pipelines for HPC workloads
• Debug and Tune fabric-level performance to ensure low-latency high throughput configurations
• Development of telemetry for performance analysis across distributed clusters of servers
• Triage and fix performance issues in Linux
• Collect data, produce metrics and visualizations that communicate performance information compared to benchmarks; this data should lead to appropriate business decisions and toward greater automation that improves customer experience in relation to performance
• Define Linux and OS requirements, specifications, and system architecture in relation to systems performance, in collaboration with cross-functional teams. Along with these responsibilities there will also be cross team collaboration to triage and resolve bottlenecks

Who you are:

• 5+ years of professional experience in Systems/HPC Performance Engineering, Benchmarking, and/or Validation.
• Strong experience with MPI workloads and distributed system performance analysis
• Familiarity with RoCE, InfiniBand, and GPUDirect/Data Direct I/O, NUMA, etc in HPC workloads
• Hands-on use of public HPC benchmarks (HPCC, HPL, OSU, MLPerf-HPC, STREAM, IO500)
• Extensive, deep experience in Linux internals
• Fluency with a programming language geared toward automation (Python preferred, but others possible)
• Experience writing robust, testable code
• Experience diagnosing and fixing systems performance issues
• Experiencing with implementing automation testing
• Ability to effectively prioritize and communicate proposed features and fixes in a remote-employee environment
• Strong passion for automation, with a commitment to automating processes comprehensively
• Excellent documentation skills and attention to detail
• Strong analytical and problem-solving abilities

Preferred:

• Familiarity with QA/QE best practices
• Familiarity with Golang
• Opinions about software version control and team collaboration 
• Experience working in Cloud environments
• Experience as a software engineer writing large-scale applications
• Experience in open-source community software development
• Experience with machine learning is a huge bonus

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!  

The base salary range for this role is $165,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). 

Please note that this is a 24/7/365 team. You will be asked to select and rank your preferred shift(s) below.

What You’ll Do:

The Customer Experience (CX) Organization at CoreWeave is dedicated to ensuring every client running AI workloads at scale has a seamless, reliable, and high-performance experience. This team supports the infrastructure that powers the AI revolution—working across data centers, hardware systems, and customer workloads to maintain the integrity of our cloud platform. The CX organization aligns closely with the internal and customer engineering teams, offering valuable insights from the field and having the chance to contribute to the CoreWeave product roadmap and development. 

About the Role

As a Bare Metal Support Engineer, you will be responsible for supporting, operating, and maintaining CoreWeave’s extensive GPU fleet across our growing data centers in the U.S., Europe, and beyond. You will work closely with customers, data center technicians, and engineering teams to ensure the reliability, performance, and scalability of our infrastructure. 

In this role, you will: 

• Provide high-level support for customers utilizing bare-metal GPU fleets on CoreWeave Cloud.
  
  
• Diagnose, triage, and investigate reported customer issues and high-priority incidents, identifying root causes and escalating when necessary.
  
  
• Develop a deep understanding of customer workloads and use cases to provide tailored technical support.
  
  
• Coordinate remote troubleshooting and hardware interventions with Data Center Technicians.
  
  
• Create and maintain internal documentation, including troubleshooting guides, best practices, and knowledge base articles.
  
  
• Participate in an on-call rotation to support production clusters and ensure operational reliability.
  
  
• Collaborate with engineering teams to improve hardware reliability, software stability, and system performance.
  
  
• Implement automation and scripting to streamline support workflows and reduce manual interventions.
  
  
• Perform in-depth log analysis and debugging across multiple layers of the stack (firmware, drivers, hardware).
  
  
• Provide feedback to internal teams on common support issues to drive continuous improvements.
  
  
• Work with networking teams to troubleshoot connectivity issues affecting customer workloads.
  
  
• Support supercomputing infrastructure running GPU workloads at scale.
  
  
• Drive operational excellence by refining internal processes and support methodologies.
  
  

Who You Are:

• Experience in data centers, GPU clusters, server deployments, system administration, or hardware troubleshooting.
  
  
• Demonstrated experience driving resolutions and continuous improvements across cross-functional environments and teams within a data center environment.
  
  
• Intermediate knowledge of Linux (Ubuntu, CentOS, or similar), including command-line proficiency.
  
  
• Experience with NVIDIA GPUs, SuperMicro systems, Dell systems, high-performance computing (HPC), and large-scale data center environments.
  
  
• Experience in networking fundamentals (TCP/IP, VLANs, DNS, DHCP) and troubleshooting tools.
  
  
• Hands-on experience with firmware updates, BIOS configurations, and driver management.
  
  
• Experience analyzing system logs and debugging issues across firmware, drivers, and hardware layers.
  
  
• Experience working with Jira, Confluence, Notion, or other issue-tracking and documentation platforms.
  
  
• Experience in scripting and automation (Python, Bash, Ansible, or similar).
  
  

Wondering if you’re a good fit? We believe in investing in our people and value candidates who bring unique backgrounds—even if you don’t check every box. Here are a few qualities we’ve found make someone successful on our team. If some of this describes you, we’d love to talk.

• You’re curious about Kubernetes, Docker, and containerized infrastructure
  
  
• You have strong problem-solving skills with a proactive and analytical mindset.
  
  
• You have excellent communication skills and a demonstrated ability to work collaboratively in a fast-paced environment.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
  
  
• Act Like an Owner
  
  
• Empower Employees
  
  
• Deliver Best-in-Class Client Experiences
  
  
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!  

The base salary range for this role is $83,000 to $132,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

What You’ll Do
The Field Engineering team at Weights & Biases plays a vital role in ensuring customer success and adoption of our platform. As part of this team, we partner with Sales, Support, Product, and Engineering to lead technical success after the sales process. We work closely with some of the most advanced AI teams in the world, helping them build, optimize, and scale their ML and GenAI workflows across industries such as computer vision, robotics, natural language processing, and large language models (LLMs).

About the Role

We’re hiring a Post-Sales AI Solutions Engineer (AISE), Scale Customer Success to help customers successfully implement and scale AI/ML workflows and GenAI/agentic applications on Weights & Biases. You will design and deliver technical enablement and adoption programs that reach many customers at once, create reusable assets that improve self-serve success, and use product signals and feedback loops to continuously improve outcomes.

Key Responsibilities 

1. Run 1-to-many onboarding and enablement programs
   Own and deliver scalable onboarding and adoption motions (webinars, cohort sessions, group training, and office hours) that help customers get to value quickly and consistently.
2. Build reusable technical assets that drive self-serve success
   Create and maintain playbooks, reference architectures, templates, sample code/notebooks, and troubleshooting guides that standardize best practices and reduce repeated 1:1 work.
3. Operate the scaled motion using signals and feedback loops
   Use product usage signals and customer patterns to segment and trigger the right interventions, track program impact (activation, time-to-first-value, feature adoption), and feed recurring insights back to Support, Product, and Field Engineering to continuously improve the scaled journey.

Who You Are

• 3–5 years of relevant experience in a similar role
• Strong programming proficiency in Python
• Experience with deep learning frameworks (TensorFlow/Keras, PyTorch Lightning) and tools (e.g., Streamlit, LangChain)
• Familiarity with cloud platforms (AWS, GCP, Azure)
• Excellent communication and presentation skills, both written and verbal
• Organized and outcomes-driven: you can run programs, measure impact, and iterate.

Preferred

• Experience with GenAI and LLMs
• Proficiency with HuggingFace, Fastai, scikit-learn, XGBoost, LightGBM, or Ray
• Experience with hyperparameter optimization solutions
• Background in data engineering, MLOps, or LLMOps, with tools such as Docker and Kubernetes
• Familiarity with data pipeline tools

Wondering if you’re a good fit?
We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• You love collaborating with top AI teams to solve real-world ML and GenAI challenges
• You’re curious about how to optimize AI workflows at scale
• You’re an expert in Python and ML tooling, with a passion for enabling customer success

Why Us?
We work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The base salary range for this role is $139,000 to $204,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

The Security Incident Response Team (SIRT) plays a vital role in keeping Datadog safe from cybersecurity threats, defending the organization against threat actors, and maintaining the trust of our customers by ensuring their data remains protected. In this role, you will work closely with teams across Datadog to identify, triage, and respond to a wide range of threats, ensuring that we can contain any incidents as quickly as possible. You will also contribute to the tools and systems that make us more effective in our mission, and help ensure we have cross-functional learning from incidents to improve our defensive posture going forward.

At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

What You’ll Do:

• Partner with our Cyber Threat Intelligence and Detection Engineering teams to identify threats to Datadog and ensure we have appropriate, accurate, high-signal detections for those threats.

• Triage escalated alerts to determine whether a security incident is occurring or may occur imminently.

• Respond to security incidents, whether as an incident commander or as an incident responder

• Make us more efficient through building tools and automations that eliminate repetitive processes

• Help us improve our overall security posture through post-incident reviews, tabletop and purple team exercises, and process/runbook improvements.

• Participate in a light on-call rotation.

Who You Are:

• You have at least 5 years of experience in security incident response, threat hunting, security operations, cloud security, or other operational security domains.

• You’ve worked with at least one public cloud platform (AWS, GCP, or Azure) and cloud-native technologies like Kubernetes, Docker, or Terraform.

• You have a strong understanding of cloud-native threat actor TTPs and corresponding defensive controls and actively stay up to date with the threat landscape from various blogs, whitepapers, and conference talks.

• You’ve used a wide range of technologies and datasets to detect threats in cloud and enterprise environments

• You have experience building and supporting tools for incident response and forensic use cases using Python, Go, or similar programming languages.

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth:

• Generous and competitive benefits package

• New hire stock equity (RSUs) and employee stock purchase plan

• Continuous career development and pathing opportunities

• Employee-focused best in class onboarding

• Internal mentor and cross-departmental buddy program

• Friendly and inclusive workplace culture

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

We are Datadog's in-house product experts. The technical solutions team enables Datadog's worldwide growth by educating potential clients and ensuring that existing customers are happy and successful. A Technical Account Manager (TAM) will continue to provide hands-on technical services to our largest customers by supporting, adopting and providing guidance over the comprehensive suite of products and features available at Datadog. A TAM is held in high regard as an expert and trusted advisor for how IT Operations translates to business value.

At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

What You’ll Do:

• Advise on technical support and product adoption for customers in line with pre-sales, post-sales and the renewal processes
• Analyze customer’s IT Operations environment on a regular basis and provide recommendations that will maximize Datadog’s value.
• Be the customer’s advocate by knowing their goals and use cases then suggesting process changes, product adoption, configuration and additional features to meet their requirements
• Participate and prepare for Monthly and Quarterly Business Reviews with customers
• Collaborate with Datadog’s product management, engineering and technical services teams to help identify new features and products
• Continuously evolve best practice to technical product adoption and customer success

Who You Are:

• Someone with a solid technical grounding and hands-on experience of IT Operations
• Confident in your hands on experience AWS, Azure or GCP
• Comfortable scripting languages like Python, Javascript, Ruby, Perl, Go, PHP, or Chef/Puppet etc.
• Skilled in using CI/CD tools e.g. Jenkins, Gitlab etc.
• Knowledgeable about Containerization tools e.g. Docker, Kubernetes or Rancher etc.
• Able to sit up to 4 hours, traveling to and from client sites 
• Able to travel via auto, train or air up to 30% of the time
• Previous experience working as a TAM supporting mid-market and/or Enterprise customers in the cloud space
• Experienced using Datadog and/or other cloud monitoring tools
• Fluent in written and spoken English and French

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth:

• Best-in-breed onboarding
• Generous global benefits
• Intra-departmental mentor and buddy program for in-house networking
• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• An inclusive company culture, able to join our Community Guilds and Inclusion Talks

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

#LI-Hybrid

Datadog’s Implementation Services team helps customers implement and deploy Datadog quickly. Our team of architects leads the discovery, design, build, and launch of the Datadog platform to help customers accelerate time to value and get the most out of their investment. As a member of our team, you will be responsible for developing the technical roadmap for a customer’s implementation, and leading them through it every step of the way.   

At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

What You’ll Do:

• Design and guide execution of Datadog implementations, including gathering requirements, building technical architecture, and supporting deployment and launch
• Guide customer onboarding through co-development working sessions and assist when they run into roadblocks
• Write automation and design architecture for deployment templates 
• Manage the operation of implementation projects 
• Collaborate with other teams, including Customer Success, Technical Account Management, and Sales to deliver an exceptional onboarding experience

Who You Are:

• Experience designing and delivering technical solutions for DevOps Monitoring or architecture systems
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and compute technologies (EC2, serverless, VMware, VMs, Docker, Kubernetes).
• Experience with Config Management, IAC and CI/CD tools, including Ansible, Puppet, Terraform, Chef, Jenkins, Circle CI, GitHub Actions, Azure Pipelines, etc…
• Experience programming/scripting with any of the following: Java, Python, Ruby, Go, Node.JS, PHP, and .NET etc
• Background in security operations, including SOC management, SIEM tooling (e.g. Splunk Professional Services), and designing or supporting zero-trust networking architectures
• Successful track record with 5+ years experience as an Architect or Consultant in a professional services team
• Able to sit up to 4 hours, traveling to and from client sites 
• Able to travel via auto, train or air up to 30% of the time

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth:

• Best-in-breed onboarding
• Generous global benefits
• Intra-departmental mentor and buddy program for in-house networking
• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• An inclusive company culture, able to join our Community Guilds and Inclusion Talks

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

#LI-Hybrid

We are Datadog's in-house product experts. The Technical Solutions team enables Datadog’s worldwide growth by educating potential clients and ensuring that existing customers are happy and successful. As a Technical Account Manager 2 (TAM 2), you’ll serve as a trusted advisor to our strategic customers, accelerating their adoption of the Datadog platform and enabling long-term success. TAM 2s bring deep technical expertise, refined customer skills, and consultative insight into how monitoring, observability, and DevOps practices translate to business value.

At Datadog, we place value in our office culture—the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

What You’ll Do:

• Act as a technical advisor to 3 primary enterprise accounts, ensuring successful product adoption and effective usage of the Datadog platform.
• Lead enablement and adoption sessions across core product areas tailored to your customer’s architecture and business needs.
• Analyze customers’ IT Operations environments and workflows to recommend configuration, product usage, and performance improvements.
• Deliver technical business reviews, health checks, and account maturity assessments, contributing to customer QBRs with impactful recommendations.
• Escalate product issues appropriately and advocate for your customers’ needs with Datadog’s Product and Engineering teams.
• Create executive-level summaries and insights that tie platform usage to business outcomes.
• Participate in internal TAM strategy sessions and contribute to team learning through feature presentations, case studies, or best-practice sharing

Who You Are:

• You have 2+ years of experience in a technical customer-facing role (TAM, Solutions Architect, SRE, DevOps Engineer, or similar) within the cloud or observability space.
• You’re confident with at least two public cloud platforms (e.g. AWS, Azure, GCP) and have hands-on experience with infrastructure or application monitoring.
• You’re familiar with scripting or automation tools (e.g. Python, Bash, Terraform, Chef/Puppet).
• You have working knowledge of CI/CD pipelines and containerization tools (e.g. Jenkins, GitLab, Docker, Kubernetes).
• You excel at communicating technical concepts to both technical and non-technical stakeholders, and can adapt your style for individual contributors or exec audiences.
• You’re able to work with minimal guidance on customer enablement, issue triage, and product adoption strategies.
• You are comfortable traveling up to 25–30% of the time as needed (via auto, air, or train).
• Previous experience using Datadog or other cloud monitoring tools is a strong plus

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth:

• Best-in-breed onboarding program
• Generous global benefits package
• Intra-departmental mentor and buddy program for in-house networking
• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• An inclusive company culture, including Community Guilds and Inclusion Talks

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

#LI-Hybrid

About us:

• We are a multinational company with offices in the US (New York and Los Angeles), Germany (Berlin), and the UK (London)
• We provide a flexible work culture that offers the opportunity to collaborate and connect in person at our offices as well as accommodating work from home
• We are deeply committed to ensuring diversity, equity and inclusion at all levels of our organization and fostering a community where everyone’s voice, perspective and experience is respected and heard.
• We believe a strong team is made by investing in employees through mentorship, workshops and enrichment opportunities

Benefits:

• Not located in Berlin? No worries, we offer extensive relocation support including allowances, one way flights, temporary accommodation and, by partnering with Expath, on the ground support on arrival
• Interested in a gym membership, photography course or book? We have a Creativity and Wellness benefit!
• Employee Equity Plan
• Generous professional development allowance
• Flexible vacation and public holiday policy where you can take up to 35 days of PTO annually
• We offer free German courses at beginning, intermediate and advanced
• Various snacks, goodies, and 2 free lunches weekly when at the office

Diversity, Equity and Inclusion at SoundCloud

SoundCloud is for everyone. Diversity and open expression are fundamental to our organization; they help us lead what’s next in music by understanding and empowering our creators and fans, no matter their identity. We acknowledge the challenges in the music industry, and strive to influence an inclusive culture where everyone can contribute respectfully and thrive, especially the historically marginalized communities that many of our creators, fans and SoundClouders identify with. We are dedicated to creating an inclusive environment at SoundCloud for everyone, regardless of gender identity, sexual orientation, race, ethnicity, migration background, national origin, age, disability status, or care-giver status.

At SoundCloud you can find your community or elevate your allyship by joining a Diversity Resource Group. Diversity Resource Groups are employee-organized groups focused on supporting and promoting the interests of a particular underrepresented community in order to build a more inclusive culture at SoundCloud. Anyone can join, whether you share the identity or strive to be an ally.