Location: Stockholm
ABOUT US:
AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL.
Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.
Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.
We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation.
Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
THE ROLE:
We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform.
Specifically, you’ll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter.
You’ll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You’ll own durability and cost at petabyte scale, from streaming and batch replication between origins to garbage collection over billions of objects. You’ll work across the stack, from local disk and page cache to distributed blob storage and garbage collection, and you’ll help shape what storage becomes next as we push storage closer to workloads.
WHAT YOU’LL WORK ON:
- Build P2P sharing of data across workers within a single datacenter to dramatically reduce ingress
- Replicate data across multiple blob storage providers
- Automate garbage collection across hundreds of petabytes of data
- Deploy colocated storage clusters to datacenters to accelerate high-throughput customer workloads
YOU MAY BE A FIT IF:
- You have 5+ years of experience writing high-quality production code
- You’ve built high-performance distributed storage or caching systems at a large scale (the more challenges you’ve worked through, the better)
- You have strong cloud skills, including deep familiarity with object storage (S3 or similar), CDNs, and their consistency, throughput, and cost characteristics
- You have strong knowledge of low-level operating system foundations (Linux kernel, file systems, page cache, containers, etc.)
- You’re willing to step into the thick of it with our on-call rotation and respond to production incidents
NICE-TO-HAVE:
- Experience with replication, content addressing, and consistency models in multi-region or multi-cloud systems
- Experience operating storage systems at scale (petabyte-scale datasets, high-throughput read/write paths, large-scale garbage collection or data migration)
- Experience with data engineering at petabyte scale
- Prior experience with Rust
Location: London, United Kingdom - Deliveroo
Our Global Structure
Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team.
About the Role
Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day.
From real-time logistics to resilient infrastructure and marketplace optimisation, we design, build and operate technology that powers Deliveroo’s growth at scale.
In November 2023 we launched our non-food retail offering, Deliveroo ‘Shopping’, where we work with large and small merchants. We oversee all operations within the grocery and retail ecosystem, ensuring stores are equipped to receive and efficiently process orders. Our solutions empower stores to manage orders seamlessly through multiple channels, including our in-house app, API integration, and devices pre-installed with our software. Additionally, we provide tools to maintain and update product catalogs, ensuring accurate inventory for consumers. The technology we’ve developed enables our partners to pick the correct items swiftly while keeping inventory data current, optimizing both efficiency and accuracy.
We’re looking for a
Staff Software Engineer
to join our
London, UK - Hybrid (3 days from the office)
team. In this role, you’ll help us define technical solutions for critical business problems and lead the technical direction for complex, high-scale systems.
Get to know our
Engineering
team — what drives us, how we work, and what you can expect.
What You’ll Be Doing
You’ll be joining a high-impact engineering group focused on solving unstructured and ambiguous challenges. You will act as a technical authority, aligning non-adjacent teams to deliver results that move the needle for the entire organisation.
Here’s what your day-to-day might look like:
Drive Technical Excellence:
Improve code structure and architecture across your team’s remit, developing, releasing and running large-scale web applications whilst transitioning our monolithic codebase to a microservice-based architecture
Lead Project Planning:
Foresee dependencies and risks, partnering closely with Product and Design to ensure smooth delivery of complex features, whilst defining the backend architecture and tech stack for a product area
Optimise Operations:
Improve performance, reliability, scalability and security for our backend systems
Collaborate & Influence:
Build relationships across global engineering teams to identify collaboration opportunities and influence the wider technical roadmap.
Mentor & Hire:
Support the personal growth of your colleagues through technical guidance and take an active role in conducting engineering interviews to scale our team.
What You’ll Need to Thrive
Our ideal candidate will bring strong expertise in some of these areas and curiosity to grow in others:
Proficiency in using AI coding tools
(e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software
Strong Engineering Principles:
Deep pride in writing readable, well-designed, and well-tested software.
Backend Expertise:
Significant experience building web-based applications (we use Go, Ruby/Rails, Python, Scala, and Rust).
Data Proficiency:
Practical experience with relational databases (PostgreSQL, MySQL) and "NoSQL" backends like Redis, DynamoDB, or ElasticSearch.
Systems at Scale:
Proven ability to manage web architecture at scale (handling 20krpm and above).
Technical Leadership:
Experience breaking down large pieces of work and guiding implementation choices for a team of engineers.
Why Join Us?
At Deliveroo, you’ll do work that matters—solving real-world problems in a three-sided marketplace that’s constantly evolving. We’re food lovers, problem solvers, community organisers, proud parents, and more, brought together by a shared drive to make things better. Working here you can expect to:
🔧
Solve meaningful problems at real scale
Work on a complex, always-on marketplace that impacts millions every day.
🌱
See your impact, fast
Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment.
🧠
Grow through challenge and ownership
Take on big, ambiguous problems and accelerate your career with strong support.
🌎
A culture built for builders
High standards, collaboration, flexible working and continuous learning.
💰
Share in the success you help create
Competitive salary and equity options, so you’re rewarded for the impact you make.
Diversity, Equity and Inclusion
At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We’re committed to fostering an environment where everyone can do their best work and feel they belong.
We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief.
If you have a disability or long-term health condition and need support to apply for one of our roles, or require any reasonable adjustments during the recruitment process, you’ll have the opportunity to let us know once you’ve submitted your application. We’ll share details on how to request support so we can ensure you have a fair and equitable experience.
If you’re excited about making a real impact in a fast-moving marketplace and growing your career alongside ambitious, supportive teams, we’d love to hear from you!
Beware of recruitment scams: DASH Brands will never ask you to pay money or share sensitive financial information during hiring — learn more about DASH Brands' legitimate recruiting process at
careersatdoordash.com/recruitment-scam-awareness
.
Synthesia is looking for a Staff Research Scientist Interactive Avatars to lead research on multimodal diffusion models for natural real-time avatar interactions.
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Location: New York City, NY; San Francisco, CA; Seattle, WA
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
As a member of the GTM team at Anthropic, you will be a Staff Forward Deployed Engineer (FDE) who embeds directly with our most strategic customers and leads the technical direction of their AI adoption. Customers bring you in to lead, not only to implement: you decide what should be built, and then make sure it gets built well. You will work with customer teams to ship advanced AI applications that solve real world business problems, and guide the architecture and advisory work that surrounds those builds across an account.
Working closely with our Research, Product, and Engineering teams, you'll combine engineering expertise, an understanding of frontier AI applications, and customer-facing skills to understand customer workflows and develop innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.
You will sit at the frontier of enterprise AI deployments and help shape our forward-deployed motion as it scales. We expect Staff FDEs to set direction under ambiguity and represent Anthropic at the highest level in customer environments. In this role, you guide architecture and build initiatives across workstreams, working directly with senior technical and business stakeholders and owning outcomes that span an account's roadmap.
You don't need to have shipped agents to production. You do need deep experience building and operating production systems, hands-on time with agents, and the judgment to lead architecture and advisory work with enterprise customers.
Responsibilities
Own technical strategy for a key account or vertical, in partnership with account and product teams.
Guide technical architecture and design decisions across multiple concurrent workstreams.
Lead discovery and advisory engagements independently, shaping scope and technical strategy before a build starts.
Lead engagements delivered with partners, setting the architecture and the quality bar for work you don't build yourself.
Review designs and unblock other FDEs on hard technical calls.
Represent Anthropic to senior technical and business stakeholders, including VPs and C-level, to align on strategy and de-risk delivery.
Own your engagements end to end: scope the work, sequence it, unblock it, anticipate security and procurement gates, and deliver production systems the customer can operate.
Work within customer systems to build production applications and agent components with Claude, and hand over systems the customer can run.
Identify and codify repeatable deployment patterns and contribute insights back to our Product and Engineering teams.
Build long term relationships with customers and proactively identify new opportunities for AI deployment throughout the lifecycle of an engagement.
Travel frequently (25%) to customer sites to build in person with customers.
Be a champion for Anthropic's mission in the field.
You May Be a Good Fit If You Have
Deep system design and problem decomposition skills: you can walk into a discovery conversation with only a business problem and leave with a defensible technical strategy for a secure, production-ready design inside a complex enterprise environment of legacy systems, with identity and access, and compliance requirements.
Experience in a senior technical, customer facing role such as Forward Deployed Engineer, or as a Tech Lead with consulting or product experience. Former technical founders are also encouraged to apply.
A track record as the person a team turns to on ambiguous technical calls, whether through architecture review, pairing, or informal mentorship.
A track record of directly influencing senior technical and business stakeholders, including VP and C-level, in complex organizations.
Extensive experience building and operating production systems. Hands-on experience with LLMs and agents is expected. Side projects and prototypes count.
Strong programming skills with proficiency in Python (and ideally in one or more additional languages like TypeScript, Java, etc), experience shipping production applications, and everyday use of AI coding tools with the judgment to review and steer.
Experience leading advisory and architecture-review engagements as well as hands-on builds, and running them end to end.
High agency with an ability to navigate ambiguity present in complex organizations, and the learning velocity to pick up new domains and tools fast.
Passion for advancing safe, beneficial AI systems through creative technical applications.
A background in financial services, healthcare/life sciences, or another enterprise vertical are nice to have.
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$280,000
—
$320,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: San Francisco, CA; Seattle, WA
Workplace: Remote
ABOUT DOCKER
Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout.
We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default.
_______________________________________________________________________
Docker is looking for a Staff Software Engineer to set the technical direction for key parts of our AI Developer Tools team. You will work at the intersection of AI, developer experience, and platform engineering, building the AI-powered tools and the platform that let teams across Docker prototype, deploy, and scale their own AI developer tools.
As a Staff Engineer you will own the technical design and delivery for two areas:
AI-Powered Developer Tools. Design and build AI agents and tools that accelerate developer productivity, surface observability insights, and automate operational reviews. You will help teams adopt an AI-native way of working and speed up adoption of tools such as Claude Code and Codex. Examples include AI-powered code review and refactoring assistants, automated test generators and local environment setup tools, deployment pipeline diagnostic agents, and agents that simplify on-call work during incidents.
Self-Service AI Developer Tools Platform. Design and build the platform infrastructure that lets product and platform teams across Docker unblock themselves by prototyping, building, and deploying their own AI developer tools. You will set the patterns and standards that let teams experiment, iterate quickly, and graduate successful prototypes into production-ready services.
You will report to the Senior Manager, AI Developer Tools, and work closely with the team's Principal engineers, engineering leadership, product engineering teams, and platform teams across Docker.
WHAT WOULD MAKE SOMEONE SUCCESSFUL IN THIS ROLE
You are a hands-on technical leader who works well at the intersection of AI, developer experience, and platform engineering. You have shipped production systems built on LLMs and AI agents, and you can explain what worked and what did not. You think in platforms: you design something once so that several teams can move faster. You have clear opinions about what makes a developer tool good, and sound judgment about when to build, when to integrate, and when not to do either. You are comfortable in a fast-moving AI landscape and balance technical quality with shipping iteratively. Before you design, you ask about scale, users, and constraints rather than assuming them. You lead through influence and mentorship, and the engineers around you get better because you are on the team.
RESPONSIBILITIES
Technical Leadership and Architecture
- Set technical direction and own the architecture for AI-powered developer tools and the self-service platform within the team's roadmap
- Turn ambiguous problems into clear requirements, plans, and staged decisions. Ask about scale, users, and constraints before designing, and write down your assumptions
- Establish patterns, standards, and best practices for LLM integration, agent development, and production AI systems that the team and partner teams adopt
- Shape platform capabilities including deployment frameworks (ArgoCD/GitOps), observability integration (Grafana), security controls, and operational tooling for AI developer tools
- Design reliable, scalable infrastructure for hosting AI agents and developer tools
- Recommend AI technology choices, LLM provider strategies, and agent orchestration approaches, and make the trade-offs explicit
- Work with the Senior Manager and the team's Principal engineers to align technical decisions with business goals
Systems Design and Implementation
- Design, build, and operate production AI agents for developer productivity, including code review assistants, test generators, deployment diagnostics, and incident response automation
- Build self-service platform capabilities that reduce time-to-production for new AI tools from weeks to days
- Build systems that speed up adoption of AI-native development tools (Claude Code, Codex) across Docker's engineering organization
- Set and meet reliability, security, and performance standards for AI systems, including SLOs, monitoring, incident response, and cost management
- Design integrations between AI developer tools and existing developer infrastructure such as CI/CD pipelines, observability platforms, and deployment systems
- Take part in the team's on-call rotation and use what you learn to improve alerts, runbooks, and tooling
Strategic Impact and Innovation
- Evaluate emerging AI/LLM technologies, developer tooling trends, and agent frameworks, and recommend what Docker should adopt and what it should not build
- Define how we measure AI tool effectiveness, including adoption, productivity gains, and developer satisfaction
- Improve AI tool performance, cost efficiency, and developer experience through architectural improvements
- Contribute to the technical approach for hardening proven internal tools so other teams across Docker can adopt them
- Lead cross-team technical delivery, surface risks early, and work with Infrastructure, Security, and Data on shared standards
Leadership and Mentorship
- Mentor senior engineers on AI/LLM integration patterns, agent development, and platform engineering practices
- Lead design reviews and raise the quality of design and code reviews across the team
- Create reusable patterns, documentation, and architectural decision records (ADRs) that other engineers build on
- Help the team turn good individual AI-assisted engineering practice into shared workflows and controls
- This role may require participation in an on-call rotation to provide support outside of standard business hours, including evenings, weekends, and holidays, as needed.
QUALIFICATIONS
REQUIRED
- 8+ years of software engineering experience, with demonstrated technical leadership on production systems at scale
- Hands-on production experience building LLM-powered applications, AI agents, or AI-assisted developer tools
- Strong understanding of LLM APIs (OpenAI, Anthropic, and others), prompt engineering, agent orchestration frameworks, and practical uses of AI in software development workflows
- Track record of designing and building scalable distributed systems and developer-facing platforms
- Production experience with cloud-native infrastructure, including Kubernetes, GitOps deployment patterns, observability systems, and CI/CD pipelines
- Proficiency in Go (preferred), Rust, Java, or Python, with strong software engineering fundamentals
- Experience designing developer tools, platform systems, or internal tools that other teams rely on
- Track record of clarifying requirements and constraints with stakeholders before committing to a design
- Track record of leading complex initiatives that crossed team boundaries, and of influencing without direct authority
- Strong product and platform judgment: you weigh business outcomes, developer experience, and technical trade-offs
- Clear written and spoken communication suited to a remote, async-first company
- Track record of mentoring other experienced engineers
- Ownership mentality with a bias for action and iterative delivery in ambiguous, fast-moving environments
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
PREFERRED
- Experience with MCP (Model Context Protocol) or similar AI agent integration standards
- Background in developer productivity, DevOps, SRE, or platform engineering
- Contributions to open source AI tools, developer tooling, or platform engineering projects
- Experience evolving an internal platform or tool into a widely adopted, production-grade service
- Knowledge of security, compliance, and operational practices for production AI systems
- Experience with infrastructure-as-code (Terraform, Pulumi) and major cloud platforms (AWS, GCP, Azure)
WHAT TO EXPECT
FIRST 30 DAYS
- Build context on Docker's current AI and developer tooling landscape, including existing AI experiments, LLM provider relationships, and architecture decisions to date
- Meet the Senior Manager, the team's Principal engineers, engineering leadership, and key stakeholders in product engineering to understand needs, pain points, and constraints
- Review existing AI tool prototypes and internal experiments to learn what is working and what is not
- Get hands-on with the team's services and ship a useful production change
- Shadow on-call and learn the operational profile of the team's services
- Work with the Senior Manager to agree on initial technical priorities
FIRST 90 DAYS
- Lead the technical framing and delivery plan for one significant problem, from requirements through to production
- Document the architecture, technology choices, and integration patterns for that work, including ADRs
- Ship a production AI developer tool that sets patterns the team can reuse (for example an AI-powered code review agent, a deployment diagnostic agent, or an on-call assistant)
- Contribute to the technical foundations of the self-service platform: deployment pipeline, observability integration, security controls, and cost management
- Lead design reviews for your area of the roadmap and begin mentoring other engineers
- Take part in the on-call rotation
FIRST YEAR OUTLOOK
- Be the trusted technical lead for your area of AI Developer Tools, and a sought-after partner for teams across Docker
- Deliver at least one material outcome that spans multiple teams or systems
- Have multiple production AI tools demonstrating value across Docker's engineering organization
- Help build a self-service platform that lets multiple teams build, deploy, and operate their own AI tools with little friction
- Define and instrument how the team measures AI tool adoption, effectiveness, and developer productivity impact
- Grow other senior engineers into broader ownership, and reduce the number of decisions that depend on a small set of people
Docker considers sponsorship on a case-by-case basis based on business needs.
Compensation & Equity
United States: $170,350 – $275,550 + equity
______________________________________________________________________
POSTING INFORMATION
- Open vacancy: This posting is for an existing open role.
- AI in hiring: Docker may use AI-assisted tools during our recruiting process.
- Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent.
______________________________________________________________________
PERKS & BENEFITS
- Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration.
- Flexibility that fits your life – We trust you to manage your schedule while delivering great work.
- Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break.
- Home office support – Set up your workspace for comfort and success.
- Technology stipend – Equivalent to US$100 net per month to help support your work.
- Learning & development – Annual stipend for conferences, courses, certifications, and continued learning.
- Parental leave – 16 weeks of paid parental leave after six months of employment.
- Equity for all full-time employees – Share in Docker's long-term success as we continue to grow.
- Comprehensive benefits – Medical, retirement, and paid holidays vary by country.
- Docker swag – Because representing the whale never gets old.
Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community.
#LI-REMOTE
Location: United States; Canada
Workplace: OnSite
WHO ARE WE?
Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.
We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.
We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.
We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!
Role Overview
As a Member of Technical Staff in Post-Training Data Infrastructure, you will build and own the pipelines that produce the post-training data for our large language models (LLMs), from SFT and RL data to synthetic and human-annotated data. You will work closely with researchers and annotation teams so they can iterate on data as quickly as they iterate on models.
Key Responsibilities
- Build and maintain data pipelines for SFT, preference, and RL post-training data.
- Own dataset quality, versioning, and reproducibility.
- Turn research data recipes into production-grade, reusable components.
- Scale model inference for data generation and model-based grading.
- Design data formats and schemas that keep post-training datasets consistent and efficient to train on.
- Collaborate with researchers and engineers to make sure data pipelines keep pace with the needs of cutting-edge language models.
Qualifications
- Strong software engineering skills.
- Experience designing and building large-scale data pipelines for machine learning, ideally for LLM post-training.
- Track record of running distributed data processing and model inference at scale.
- Good understanding of post-training methods (e.g., SFT, RLHF, DPO) and how data shapes model behaviour.
- Excellent communication skills.
This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to Cohere, please reach out. We value diverse backgrounds and perspectives at Cohere
FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS:
- A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.
- Full health and dental benefits, including a separate budget for mental health.
- RRSP matching, 401K, Pension Scheme.
- 100% Parental Leave top-up for up to 6 months, for either parent.
- Annual enrichment benefits:
Arts & culture, fitness/wellness, quality time, and a workspace improvement credit.
Education & learning stipend for conferences, courses, and coaching.
- 6 weeks of paid vacation (30 working days!)
- Budget for traveling to other offices if you are remote, plus an annual company offsite.
HOW AND WHERE WE WORK:
- Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon.
- For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.
- For those not near an office: a co-working benefit so you can work alongside others in your city.
- Everyone receives a $500 home office stipend to set up your workspace properly.
If any of the above doesn’t line up exactly with your experience, we still encourage you to apply.
We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs.
We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.
Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.
Location: Europe; New York; Toronto
Workplace: Remote
WHO ARE WE?
Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.
We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.
We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.
We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!
Key Overview:
As a Member of Technical Staff in Post-Training, you will train our large language models (LLMs) with reinforcement learning and develop methods that help them generalize beyond the distribution they were trained on. You will design the training recipes, environments, and evaluations that tell us whether a model has truly learned a skill or has only fitted its training tasks, and turn what works into the recipes behind our production models. You will work closely with the post-training data infrastructure, evaluation, and pre-training teams.
Key Responsibilities
- Design, run, and analyse large-scale RL post-training experiments (e.g., RLHF, RL from verifiable rewards).
- Research and develop methods that improve out-of-distribution generalization, such as reward design, environment and task diversity, curricula, and regularization.
- Build held-out evaluations that measure generalization to unseen tasks, domains, and formats, and that catch reward hacking and benchmark overfitting.
- Diagnose training dynamics and failure modes, including instability, reward over-optimization, and capability regressions.
- Turn successful research into robust, reproducible training recipes for production models.
Qualifications
- Strong research and software engineering skills, with hands-on experience training LLMs.
- Experience applying reinforcement learning to LLMs (e.g., PPO, GRPO, RLHF, RLVR), ideally at scale.
- Track record of work on generalization, robustness, or distribution shift, through publications or shipped models.
- Rigorous experimental practice: clean ablations, careful controls, and sound conclusions from noisy results.
- Experience with distributed training (e.g., JAX, PyTorch, FSDP, Megatron) is a plus.
- Excellent communication skills.
- Deep understanding of data quality principles and best practices: demonstrates willingness to dive deep into data while possessing strong intuition for assessing the quality of datasets and anticipating how different data characteristics will impact model training outcomes.
Working Location
This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.
FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS:
- A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.
- Full health and dental benefits, including a separate budget for mental health.
- RRSP matching, 401K, Pension Scheme.
- 100% Parental Leave top-up for up to 6 months, for either parent.
- Annual enrichment benefits:
Arts & culture, fitness/wellness, quality time, and a workspace improvement credit.
Education & learning stipend for conferences, courses, and coaching.
- 6 weeks of paid vacation (30 working days!)
- Budget for traveling to other offices if you are remote, plus an annual company offsite.
HOW AND WHERE WE WORK:
- Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon.
- For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.
- For those not near an office: a co-working benefit so you can work alongside others in your city.
- Everyone receives a $500 home office stipend to set up your workspace properly.
If any of the above doesn’t line up exactly with your experience, we still encourage you to apply.
We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs.
We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.
Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.
Location: San Francisco, CA | New York City, NY | Seattle, WA
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
As of May 2026, Claude authored
more than 80% of the code we merge
. In September 2026, we merged more than
30,000 changes per day
. Writing a change is fast now, and the hard part is knowing what is correct and safe to ship. Platform Acceleration builds the internal tools that close that gap for Anthropic's product engineers, who own the Claude API, our SDKs, and the rest of the Claude Platform. We work like a small product team whose customers are other Anthropic engineers.
We're looking for Staff+ engineers with a strong background in backend or infrastructure who care about developer experience and have built tools other engineers rely on. We prefer candidates who can work from our San Francisco office, and we'll also consider candidates based in Seattle.
What you'll do
Design, build, and operate the tools that help product teams ship faster
Own the technical strategy and roadmap for your area, and make sure its hardest problems get solved, by you or through others
Define what it means to trust a change, especially changes written by Claude, and build the tooling that holds the bar throughout the software development lifecycle
Build agents that take on repetitive engineering work, such as diagnosing failures, fixing broken tests, and running migrations
Embed with partner teams to find their biggest sources of friction, validate a solution with them, and turn the fix into a product other teams can adopt
Move between building new tools and improving the shared systems that teams already depend on, as priorities shift
You might be a good fit if you:
Experience building and operating backend services or infrastructure in production, in Go, Python, Rust, or TypeScript
Deep experience with developer tooling, CI/CD, test infrastructure, or deployment systems
Experience leading large, complex technical projects across teams, from an ambiguous problem to a solution developers adopt
Clear written and verbal communication, with experience supporting internal partner teams
Interest in Anthropic's mission of building safe, beneficial AI
Preferred qualifications:
Experience at a startup or on a similarly small team, taking a product from zero to one and talking directly to your users
Substantial experience with agents that do engineering or other technical work
Experience building widely adopted CLI tools, developer-facing services, GitHub automation, or open source developer tools
Experience measuring developer productivity and using the data to decide what to build
A point of view on how software engineering changes as agents write more of the code
Deadline to apply:
None. Applications will be reviewed on a rolling basis.
Location Preference:
Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of team.
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$405,000
—
$485,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Shield AI is looking for a Staff IT Systems Engineer to lead regional ICT operations, infrastructure, cloud services, security controls, and compliance.
Location: Mexico; Serbia; Brazil; Hungary; Ecuador; South Africa
About Paired
Paired is a global staffing and recruiting agency that specializes in pairing remote work with top-tier talent!
We are dedicated to connecting talented individuals with remarkable companies in need of their skills. Our goal is to create fulfilling job opportunities for professionals around the world.
About our Client
Our client runs a fast-growing education and software business, and across their channels, his team and him, have built a platform of more than 1.5 million followers.
His job is to be the face of their content and to think about where the company goes next. That takes about forty hours a week of creating, plus long uninterrupted blocks for strategy. It leaves very little room for anything else.
Which is the problem. Projects need chasing. Follow-ups need sending. Hiring needs running. Reports need collecting. None of that happens on its own, and when he tries to do it, the content and the strategy suffer.
That is what this role is for. You'll protect his time, remove operational drag, and make sure the company actually executes.
The Role
A lot of roles with this title are a dead end: no access to the founder's inbox, no seat in the meetings, just a pile of disconnected projects nobody else wanted. If that is your experience of these jobs, he understands the scepticism.
This is not that. You will see his calendar, his inbox, his meetings, and his numbers. You will watch decisions get made in real time and understand why they went the way they did. Done properly, it is the fastest and most complete training in how to run a company that exists, which is why it comes with a defined path to
Chief of Staff over twelve to eighteen months.
The trade is simple, and he would rather be blunt about it. You get total context. In exchange, you do the work he genuinely does not want to do: the chasing, the reminding, the coordinating, the collecting, the repetitive things that protect my creative bandwidth.
If that trade sounds good to you, keep reading. If you want the access without the admin, this is not your role.
What You'll Own
Calendar, first and above everything else
Protect deep work blocks, batch meetings, enforce priorities
Turn a chaotic week into an intentional one that matches company goals
Gate my time, never my people. You are not a human shield and you will never intercept someone who should be talking to me directly
The follow-up engine
Action items, owners, due dates, reminders, escalation
Nothing dies in Slack, WhatsApp or email because somebody got busy
Draft messages, emails and internal updates so I can approve them fast
Project management and accountability across the company
Build and run the company operating system, whether that lives in Trello, Asana or Notion
Every project carries an owner, a deadline, a next action and a definition of done
Hold department leaders to what they committed to, including when that means a difficult conversation
Hiring operations
Run hiring end to end for key roles: an Organic Content Director, a Senior DR Copywriter, an Instagram Copywriter and others
Pipeline, scheduling, scorecards, assignments, Loom reviews, references
Keep it moving fast without dragging me into logistics
Content operations oversight
You will not create content. You will make sure it ships
Track weekly output, deadlines and approvals across YouTube, Instagram and email so I am not chasing anyone
Metrics and reporting
Collect and analyse the monthly P&L, maintain KPI dashboards, run the weekly reporting rhythm
Review payroll, which means you will know what everyone earns, and come back with specific recommendations on raises, comp structure, inefficiency and where we are carrying people we should not be
Projects that do not fit anywhere else
Sometimes real-world and operational, such as managing the build-out of a home studio in Puerto Rico
Sometimes unglamorous. A real example: three or four hours going line by line through my AMEX statement to find software we are overpaying for, then contacting each vendor to cancel. The right answer is to do it once, then automate it, delegate it or own it monthly
AI across the workflow
Using ChatGPT instead of Google is the floor, not the bar
You should be good enough that you are advising other department leaders on how to use AI in their own work
How you will be trained
Nobody performs on day one in this role, and I do not expect you to. Context is the whole job, and context takes time to build.
Weeks 1 to 4, shadowing.
You sit in on everything: calendar, meetings, comms, priorities. You build your own model of how I think, what I care about and how I decide. You start taking small things off my plate immediately, mostly scheduling, notes and action items.
Days 30 to 60, execution and systems.
You take over the follow-up engine and the task system. You run a short structured weekly planning session with me. You start managing hiring operations and cross-functional projects, and you begin enforcing owners and due dates.
Days 60 to 90, Office of the CEO.
You run the operating cadence: reporting, follow-ups, meeting prep. You own major initiatives. You are my execution arm while I focus on content and strategy.
Months 3 to 18, Chief of Staff track.
As trust and competence compound, the work shifts from execution toward leverage: planning rhythms, decision memos, cross-functional problem solving, running high-priority initiatives. This is performance-based, not automatic.
Requirements
Who this is for
You are an operator. You like execution, structure, and turning mess into order
You have extreme ownership. You anticipate rather than wait
You can make good calls without asking me for permission every day
You are comfortable in the background while I am the one on camera
You are discreet, because you will see everything
You write clearly and in detail
You enjoy running a tight system and holding people to it
Who this is not for
You want a strategy-only role where you bounce ideas around without touching admin or follow-up
You need constant direction, reassurance or step-by-step instruction. You are here to protect my time, not to collect free mentorship from me
You avoid conflict and cannot hold someone accountable when they are late or underperforming
You are uncomfortable with high access and high confidentiality
Unglamorous tasks offend you
Tools
Google Workspace, Slack, Trello or Asana, Calendly, Zoom, Loom.
Benefits
Remote work
Flexible hours
USD compensation around $3k-5k/month (negotiable but dependable on seniority)
Fast-track to Chief of Staff
What success looks like
Twenty or more hours a week of my time handed back within 60 to 90 days
He stops doing project management, follow-ups, appointment setting, internal chasing and hiring logistics
The weekly operating rhythm runs without me pushing it
Projects move faster, with fewer dropped balls
The company gets calmer and more accountable, not more chaotic
Location: Remote - Canada
What We’re Building
Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023!
If you want to see what we’ve been up to, please check out these
blog posts
and Honeycomb.io
press releases
.
Who We Are
We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live
our values
every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers.
How We Work
We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote
About the problem space
AI has changed what's possible in go-to-market, support, and business operations. The constraint is no longer "can we build it" — it's "can we deploy it into a real workflow, prove it made things better, and keep it working."
Most companies are stuck at the demo stage: a lot of clever prompting, very little that runs reliably on Tuesday morning without someone watching it. This role exists to get us past that, everywhere outside of engineering.
Little more about the team:
You'll sit on the Data team, which is where this work belongs. Our team already operates at the seam between the business and its systems — we partner daily with RevOps, Customer Success, Sales, and Product, and we own the data infrastructure these workflows depend on. AI-in-the-business is a data problem with a model attached, and you'll have the pipelines, the warehouse, and the domain relationships already in place.
What you'll do
You are a senior individual contributor. Your job is to take business workflows that are slow, manual, or inconsistent, and make them fast, automated, and measurably better — then do it again, and leave behind enough shared scaffolding that the third one is easier than the first.
Ship automated workflows end to end
Partner with department leaders to identify the highest-leverage workflows in their orgs, and go deep enough on how the work actually happens to know where a model helps and where it doesn't.
Define success before you build: cycle time, quality, cost, risk. Instrument it. Report on it honestly, including when the answer is "this didn't work."
Deliver working systems, not prototypes, with evaluation harnesses, human-in-the-loop review where the stakes call for it, and ongoing monitoring.
Iterate on adoption the way a product manager would: user research, documentation, and a real plan for getting people to use the thing.
Build the shared substrate as you go
Establish patterns for model access, orchestration and agents, prompt and tool management, evaluation, logging, and cost control — derived from what real workflows needed, not designed in advance.
Build on the Data team's existing infrastructure rather than standing up parallel systems.
Co-own shared components with your counterpart in Engineering; identify dependencies early and bring them into partner roadmaps collaboratively.
Make the company fluent
Create templates, playbooks, and golden paths: prompt patterns, agent patterns, safety checklists, evaluation patterns.
Run office hours, demos, and community-of-practice sessions that make adoption feel accessible rather than intimidating.
Develop enablement material for distinct audiences — GTM, operations, leadership — from fundamentals through advanced workflows.
Help people build judgment about AI: when to use it, when not to, and how to tell whether it worked.
Keep it safe and governable
Partner with Security, IT, and Legal on access control, data handling, vendor risk, and policy — so that employees have a clear, fast, safe path to experiment.
Work with the Data team to apply our data classification standards to AI use cases: what data can be used for retrieval and context, and what audit trails are required when sensitive data flows through LLM pipelines.
What you'll bring
Deep experience shipping systems into real business workflows — you've owned something end to end, in production, that non-technical people depended on daily.
Hands-on fluency with modern AI stacks: LLMs, retrieval, tool use and agents, evaluation, guardrails — plus the pragmatism to keep things shippable.
The ability to learn someone else's job well enough to improve it. This role lives or dies on understanding how support, sales, or finance actually work.
A track record of leading cross-functional initiatives without formal authority, bringing clarity, momentum, and crisp decision-making.
Comfort navigating security, privacy, and compliance tradeoffs in real organizations: data classification, retention, access controls, vendor risk.
Strong teaching instincts — you explain complex things simply, write clear docs, and meet people where they are.
Demonstrated ability to stay current as the landscape shifts, and to change your mind in public when the evidence does.
Nice to have
SQL fluency and comfort in a modern data stack (dbt, a cloud warehouse, BI tooling).
Experience with workflow automation or enterprise systems: case management, ticketing, CRM, knowledge bases.
Familiarity with observability practices for AI systems: monitoring, quality signals, evaluation pipelines, cost and latency analysis.
Change management experience across a distributed, multi-function company.
Interest in external evangelism — writing, speaking, podcasts, peer groups.
Base Salary based on level of experience
$310,000
—
$360,000 CAD
What you'll get when you join the Hive:
A stake in our success - generous equity with employee-friendly stock program
It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience
Time to recharge with unlimited PTO
A distributed-first mindset and culture (really!)
Home office, co-working, and internet stipend
Full benefits coverage for employees, with additional coverage available for dependents
Up to 16 weeks of paid parental leave, regardless of path to parenthood
Annual development allowance
And much more...
Please note we cannot currently sponsor or support visa transfers at this time.
Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work.
Phishing and Recruitment Scam Warning:
We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you:
All communications will come from an
@honeycomb.io
email address
We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses—
never personal accounts like Gmail or Yahoo
.
Our recruiting process will
never
ask you to provide financial or sensitive personal information, including but not limited to:
Social security or tax identification numbers
Credit card numbers
Bank account information
Diversity & Accommodations:
We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams.
We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know.
As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback.
Privacy Notice:
If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes.
For more information regarding our privacy practices please see the
Honeycomb Privacy Notice
.
If you do not want us to retain your information, or want us to update it, please contact
privacy@honeycomb.io
. Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.
Location: Remote - United States
What We’re Building
Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023!
If you want to see what we’ve been up to, please check out these
blog posts
and Honeycomb.io
press releases
.
Who We Are
We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live
our values
every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers.
How We Work
We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote
About the problem space
AI has changed what's possible in go-to-market, support, and business operations. The constraint is no longer "can we build it" — it's "can we deploy it into a real workflow, prove it made things better, and keep it working."
Most companies are stuck at the demo stage: a lot of clever prompting, very little that runs reliably on Tuesday morning without someone watching it. This role exists to get us past that, everywhere outside of engineering.
Little more about the team:
You'll sit on the Data team, which is where this work belongs. Our team already operates at the seam between the business and its systems — we partner daily with RevOps, Customer Success, Sales, and Product, and we own the data infrastructure these workflows depend on. AI-in-the-business is a data problem with a model attached, and you'll have the pipelines, the warehouse, and the domain relationships already in place.
What you'll do
You are a senior individual contributor. Your job is to take business workflows that are slow, manual, or inconsistent, and make them fast, automated, and measurably better — then do it again, and leave behind enough shared scaffolding that the third one is easier than the first.
Ship automated workflows end to end
Partner with department leaders to identify the highest-leverage workflows in their orgs, and go deep enough on how the work actually happens to know where a model helps and where it doesn't.
Define success before you build: cycle time, quality, cost, risk. Instrument it. Report on it honestly, including when the answer is "this didn't work."
Deliver working systems, not prototypes, with evaluation harnesses, human-in-the-loop review where the stakes call for it, and ongoing monitoring.
Iterate on adoption the way a product manager would: user research, documentation, and a real plan for getting people to use the thing.
Build the shared substrate as you go
Establish patterns for model access, orchestration and agents, prompt and tool management, evaluation, logging, and cost control — derived from what real workflows needed, not designed in advance.
Build on the Data team's existing infrastructure rather than standing up parallel systems.
Co-own shared components with your counterpart in Engineering; identify dependencies early and bring them into partner roadmaps collaboratively.
Make the company fluent
Create templates, playbooks, and golden paths: prompt patterns, agent patterns, safety checklists, evaluation patterns.
Run office hours, demos, and community-of-practice sessions that make adoption feel accessible rather than intimidating.
Develop enablement material for distinct audiences — GTM, operations, leadership — from fundamentals through advanced workflows.
Help people build judgment about AI: when to use it, when not to, and how to tell whether it worked.
Keep it safe and governable
Partner with Security, IT, and Legal on access control, data handling, vendor risk, and policy — so that employees have a clear, fast, safe path to experiment.
Work with the Data team to apply our data classification standards to AI use cases: what data can be used for retrieval and context, and what audit trails are required when sensitive data flows through LLM pipelines.
What you'll bring
Deep experience shipping systems into real business workflows — you've owned something end to end, in production, that non-technical people depended on daily.
Hands-on fluency with modern AI stacks: LLMs, retrieval, tool use and agents, evaluation, guardrails — plus the pragmatism to keep things shippable.
The ability to learn someone else's job well enough to improve it. This role lives or dies on understanding how support, sales, or finance actually work.
A track record of leading cross-functional initiatives without formal authority, bringing clarity, momentum, and crisp decision-making.
Comfort navigating security, privacy, and compliance tradeoffs in real organizations: data classification, retention, access controls, vendor risk.
Strong teaching instincts — you explain complex things simply, write clear docs, and meet people where they are.
Demonstrated ability to stay current as the landscape shifts, and to change your mind in public when the evidence does.
Nice to have
SQL fluency and comfort in a modern data stack (dbt, a cloud warehouse, BI tooling).
Experience with workflow automation or enterprise systems: case management, ticketing, CRM, knowledge bases.
Familiarity with observability practices for AI systems: monitoring, quality signals, evaluation pipelines, cost and latency analysis.
Change management experience across a distributed, multi-function company.
Interest in external evangelism — writing, speaking, podcasts, peer groups.
Base Salary based on level of experience
$225,000
—
$265,000 USD
What you'll get when you join the Hive:
A stake in our success - generous equity with employee-friendly stock program
It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience
Time to recharge with unlimited PTO
A distributed-first mindset and culture (really!)
Home office, co-working, and internet stipend
Full benefits coverage for employees, with additional coverage available for dependents
Up to 16 weeks of paid parental leave, regardless of path to parenthood
Annual development allowance
And much more...
Please note we cannot currently sponsor or support visa transfers at this time.
Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work.
Phishing and Recruitment Scam Warning:
We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you:
All communications will come from an
@honeycomb.io
email address
We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses—
never personal accounts like Gmail or Yahoo
.
Our recruiting process will
never
ask you to provide financial or sensitive personal information, including but not limited to:
Social security or tax identification numbers
Credit card numbers
Bank account information
Diversity & Accommodations:
We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams.
We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know.
As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback.
Privacy Notice:
If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes.
For more information regarding our privacy practices please see the
Honeycomb Privacy Notice
.
If you do not want us to retain your information, or want us to update it, please contact
privacy@honeycomb.io
. Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.
Location: New York City, New York
What you’ll be part of
Garner is on a mission to transform the U.S. healthcare system — and we’re the only proven player doing exactly that. We partner with employers to redesign how healthcare works: applying 550+ proprietary clinical metrics across 80+ specialties to a dataset of 320M+ patients to identify the best-performing doctors, then using compelling incentives to steer members to the care that helps them get healthier, faster.
The result is a rare “win win” — better care and lower costs for both members and employers. In just five years, our work has helped over 2.5 million people access higher-quality care and saved $1B in healthcare costs. We recently raised our Series E and have doubled five years running. If you've ever wanted your work to solve a problem that touches every person in this country, this is the opportunity to do exactly that. You'd be joining a team fundamentally reimagining healthcare in the U.S. — and using AI to scale that impact further and faster than anyone else can.
Who we want
This is a role for someone who wants to sit close to the decisions, deliver real impact, and be pushed to be the best version of themselves. As Chief of Staff, you will report to the CRO and act as their extension across the Revenue organization. You will run the operating rhythm that keeps a fast-growing revenue team aligned, make sure the commitments made in leadership rooms turn into finished work, and take on the projects that do not have an obvious owner. The role is hands-on: you will chase deliverables, build the tracker, prepare the deck, and follow the thread until it is closed. In return you get a front-row seat to how a revenue organization is run at scale and a direct line to the people running it.
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'll do
Run the CRO's weekly operating cadence: track commitments and deliverables across the Revenue leadership team, follow up on what is late, and make sure nothing falls through
Act as the CRO's extension in tracking Revenue projects and KPIs, surfacing risks early and staying on them until they are resolved
Own the Revenue OKR process end to end: planning, tracking, and execution across every Revenue team, and reporting progress to the CRO and the executive team
Coordinate budget and headcount requests for the Revenue organization, from business case through approval with Finance and People
Lead cross-functional projects on the CRO's behalf, coordinating with Product, Marketing, Finance, People, and Legal, and manage them through to completion
Work directly with the CRO on high-visibility initiatives for the business
What we're looking for
4+ years of experience in a strategic problem-solving role; prior experience in management consulting, investment banking, or an early-stage startup environment
A strong ability to break down unstructured problems into their component parts, recommend solutions, and work with cross-functional stakeholders to implement them
A combination of high ownership mentality and detail orientation that has resulted in a track record of delivering operational initiatives
Strong analytical skills and the ability to synthesize insights from complex data
Interest and/or experience working in healthcare, with a mission to improve the U.S. healthcare system
A desire to do work that matters, and to be held to a high standard while doing it. You're energized by a mission with measurable outcomes, not just good intentions
This is a unique opportunity to join a fast-growing company in a transformative role, helping shape the future of healthcare.
What you'll get here:
You’ll work on problems that matter, at a company working to change healthcare at scale. You’ll work at the intersection of AI and systemic healthcare reform, where the problems we solve are as interesting and compelling as the mission.
At Garner, you’ll take on real, ambitious problems with real ownership and autonomy, alongside exceptional, principles-based people who genuinely want you to win. It’s demanding by design. You’ll be challenged to stretch beyond what you thought possible and receive consistent coaching to help you grow and do the best work of your career. This isn't the right fit for everyone, and that's intentional. The people here are driven by what's at stake for real people, and that's what gives our intensity its purpose.
Compensation Transparency:
The target salary range for this position is $215,000 - $250,000. 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) with company match, flexible spending accounts, Teladoc Health and more.
Fraud and Security Notice:
Please be aware of recent job scam attempts. Our recruiters use
getgarner.com
and
garnerhealth.com
email domains exclusively. If you have been contacted by someone claiming to be a Garner recruiter or a hiring manager from a different domain about a potential job, please report it to law enforcement
here
and to
candidateprotection@garnerhealth.com
.
Equal Employment Opportunity:
Garner Health is proud to be an Equal Employment Opportunity employer and values diversity in the workplace. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.
Garner Health is committed to providing accommodations for qualified individuals with disabilities in our recruiting process. If you need assistance or an accommodation due to a disability, you may contact us at
talent@garnerhealth.com
.
We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief
New York City, NY; San Francisco, CA; Seattle, WA
УдалённоSan Francisco, CA; Seattle, WA
ОфисUnited States; Canada
УдалённоEurope; New York; Toronto
We prefer candidates who can work from our San Francisco office, and we'll also consider candidates based in Seattle; Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of team
УдалённоMexico; Serbia; Brazil; Hungary; Ecuador; South Africa
УдалённоleadRemote - Canada
УдалённоleadRemote - United States
New York City, New York
United States - Remote
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