Location: Remote - United States
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit
www.redditinc.com
.
This role is fully remote. Reddit has a flexible first workforce.
The Site Experience SRE team sits at the intersection of infrastructure, product engineering, and user experience - ensuring that every interaction across web, mobile, APIs, feeds, media delivery, and real time systems is fast, reliable, and resilient.
We are looking for a Senior Staff Site Reliability Engineer to lead reliability engineering initiatives for critical user facing systems at internet scale. In this role, you will partner with engineering leadership to identify foundational operational challenges, define comprehensive long-term strategies to address them, and lead complex engineering programs that turn those strategies into durable improvements across Reddit.
This is a deeply technical leadership role for someone who can anticipate systemic reliability challenges, shape long-term engineering strategy, and mobilize teams across the organization to deliver lasting change at internet scale.
What you’ll do:
Advance Reddit’s Reliability Strategy
Build an understanding of reliability across Reddit’s systems, teams, and practices. Partner with engineering leadership to evolve our long-term strategy and drive the next stage of how Reddit builds and operates reliable services.
Apply Deep Expertise at Global Scale
Bring firsthand insight in operating the world’s largest platforms, and adapt and extend them to solve Reddit’s unique technical and business challenges.
Lead Reliability Engineering for User Experience
Lead complex, cross-organizational programs advancing reliability, scale, and performance for critical user-facing systems across APIs, content delivery, feeds, search, messaging, and real-time experiences.
Shape the Future of Reliability
Guide the team’s long-term roadmap, setting direction and aligning investments across domains to build resilience, unlock scale, and enable innovation.
Build Strategic Partnerships
Own and grow cross-functional partnerships across product and infrastructure engineering, aligning teams on shared reliability priorities and shaping the investments that keep Reddit resilient as it scales.
Influence Engineering Standards
Define and champion best practices around reliability engineering, SLIs/SLOs, capacity management, release engineering, and operational maturity across the company.
Elevate the Team
Develop engineers at every level through technical leadership, mentorship, and shared learning. Strengthen the team’s engineering judgment, reliability expertise, and ability to deliver with confidence.
What We’re Looking For
10+
years of experience in Site Reliability Engineering, Infrastructure Engineering, or related roles operating best-in-class large-scale distributed systems.
Expertise leading complex, cross-organizational engineering programs from design through launch.
Experience evolving company-wide reliability strategy and guiding long-term roadmaps and investments across technical domains.
Proven ability to build sustained partnerships with engineering leadership, product, and infrastructure teams to align technical and business priorities.
Deep knowledge of reliable and resilient systems designs, with experience adapting them to organizational needs and driving adoption.
Expertise diagnosing complex failures across applications, infrastructure, and networking, and improving observability to expose systemic risks.
Strong software engineering fundamentals and operational judgment, with a record of developing engineers at every level and raising engineering standards across teams.
Nice to Have
Experience with Kubernetes, containers, cloud infrastructure, and modern deployment platforms.
Familiarity with technologies such as Prometheus, Grafana, OpenTelemetry, Envoy, Kafka, ClickHouse, Cassandra, Redis, or similar distributed infrastructure technologies.
Experience with CDN optimization, edge reliability, traffic engineering, or global infrastructure.
Contributions to open source software or participation in technical communities.
Experience leading large scale incident response and operational transformation initiatives.
Benefits:
Comprehensive Healthcare Benefits and Income Replacement Programs
401k with Employer Match
Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Paid Volunteer Time Off
Generous Paid Parental Leave
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit
https://www.redditinc.com/careers/
.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
The base salary range for this position is:
$232,500
—
$325,500 USD
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our
Candidate Privacy Policy for Potential Employees and Contractors
.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
Location: Al Jubail, Saudi Arabia
Eram Talent is hiring for a Mechanical Manitenance Engineer - HVAC with core experience in Petrochemical Plants. The candidate would be responsible for maintaining the reliability, availability, and performance of HVAC and Mechanical Refrigeration Units (MRUs) serving critical petrochemical facilities. Leads preventive and predictive maintenance programs, troubleshooting activities, root cause investigations, reliability improvement initiatives, and spare parts optimization to ensure safe and uninterrupted operation.
Key Responsibilities
· Extensive experience in maintaining, troubleshooting, and optimizing HVAC, chiller, and industrial refrigeration systems in petrochemical and process plant environments.
· Hands-on expertise with Mechanical Refrigeration Units (MRUs), centrifugal, screw, and reciprocating chillers, AHUs, package units, ventilation systems, compressors, condensers, evaporators, pumps, and refrigeration control systems.
· Diagnose and resolve mechanical, electrical, instrumentation, refrigeration, and control-related failures to ensure maximum equipment availability and reliability.
· Analyze operating parameters including temperature, pressure, flow, superheat, subcooling, and compressor performance to identify system abnormalities and implement corrective actions.
· Perform equipment performance evaluations, condition assessments, and reliability improvements to minimize downtime and optimize energy efficiency.
· Proficient in interpreting HVAC/refrigeration schematics, P&IDs, electrical drawings, and OEM technical documentation.
· Experienced in Building Management System (BMS) and HVAC control systems, including monitoring equipment performance, troubleshooting control logic, analyzing alarms, optimizing system operation, and integrating HVAC assets with centralized monitoring and control platforms.
Perform RCI investigations for critical and repetitive equipment failures.
Implement corrective and preventive actions to improve equipment reliability.
Preventive & Predictive Maintenance
Develop and optimize preventive maintenance programs based on equipment criticality and reliability data.
Ensure timely completion of maintenance plans and work orders.
Spare Parts Management
Review and optimize HVAC spare parts inventory.
Identify critical and insurance spare parts requirements.
Establish minimum and maximum inventory levels based on risk and lead times.
Coordinate with procurement and warehouse teams to ensure spare availability.
Support obsolescence management and spare part standardization initiatives.
Safety & Compliance
Requirements
Ensure compliance with company safety regulations and engineering standards.
Participate in PSSR, risk assessments, and incident investigations when required.
Support process safety requirements related to HVAC systems serving critical occupied buildings.
Requirements
Minimum of 10 years experience in petrochemical, refinery, oil & gas
Bachelor Degree in Engineering
HVAC, Chillers & Industrial Refrigeration Systems Maintenance & Troubleshooting
MRU Operation and Maintenance
Reliability Engineering
Preventive & Predictive Maintenance
RCI
Spare Parts Optimization
Building Management Systems (BMS)
Location: Doha, Qatar
We are looking to hire a highly skilled Implementation Testing Engineer to join our dynamic team at ProgressSoft Qatar, based in Doha. The ideal candidate will play a crucial role in ensuring the successful implementation and testing of our software solutions. The candidate should have a strong background in both implementation and testing methodologies to guarantee the delivery of high-quality products to our clients.
Responsibilities:
Participate in project planning and provide input on testing requirements, risks, and timelines.
Create and maintain test documentation, including test plans, test cases, and test reports.
Develop and maintain a strong understanding of the software product and its functionality. This includes full Awareness and understanding of the Software Product, Customization, and Integration according to the final signed and baselined scope with the Customer.
Collaborate with project stakeholders, including developers, implementation team, project managers, and business analysts, to identify and document test cases.
Develop and execute test plans and test cases to ensure software products meet the requirements and needs of end-users.
Execute functional, integration and regression test cases; track and report defects; and work with development teams to ensure their timely resolution.
Conduct end-to-end testing for Customer Software/Solution submitted to the Customer based on project signed scope and Customer profile.
Conduct full setup certification and assurance of readiness before the Customer’s team engages in the solution testing and acceptance. This is not limited to the final approved and agreed-on test cases, as it shall cover all exceptional test cases that are identified with the project team and PO/BA and PM during the requirements detailing workshop with the Customer.
Manage the entire testing phase with the Customer’s SIT and UAT team members, attend to queries and clarifications during the testing phase, report and track on Customer’s reported issues, bugs, or CRs and align it with PO (Bugs and Findings), SID team (Issues and Setup Failures) and PM (CRs).
Ensure proper tracking and reporting on daily/weekly status during the testing phase, this includes SIT, UAT, NFT, and others. Reporting shall be aligned with the PM and PO for reflecting it in the weekly reporting by the PM to the Customer which includes:
Monitor, assist, and support Customers during test case execution, defects and reported items tracking and internal reporting and follow up with the Development team.
Conduct necessary testing and verification on all resolved bugs prior and approve to submission in the Customer release.
Conduct post-release update deployment and run a sanity check to ensure the setup is ready for the Customer team to resume testing with no new or reopened bugs or issues.
Create and maintain, in coordination with the Implementation team, the Non-functional testing that covers the performance, security, and penetration as well as technical testing (DR Drill, BCT, …etc).
Ensure that all testing activities are performed in accordance with established testing standards, methodologies, and procedures.
Maintain and improve corporate quality controls and testing plans in alignment with the PMO and Group Operations team.
Perform any other duties related to the position as assigned by the concerned management.
Requirements:
3-5 years of experience in software testing, preferably on banking or payment applications.
Strong experience in functional, integration and regression testing of web and back-end systems, covering Requirement Gathering and analysis, Functional Studies, Estimations, Test Design, Test Planning, Quality Reviews, Manual Testing, Automation Testing, API Testing, Defect Management, and Reporting.
Experience in Security Testing tools is a plus.
Knowledge of STLC and Test Process Phases.
Knowledge and Concepts in the Faults and Test Cases and Scenarios Priority.
Good understanding of the end-to-end payment lifecycle.
Knowledge of payment and clearing systems such as cheque clearing, ACH, instant payments, RTGS and GCC cross-border payments, and of ISO 20022 payment messages. Knowledge of SWIFT MT/MX and CBPR+ is a plus.
Experience implementing payments-related projects with banks, financial institutions, and/or payment service providers. Experience in Qatar or other GCC markets is preferred.
Excellent verbal, written, and interpersonal skills in English and Arabic.
Attention to details.
Excellent team player.
Excellent organizational and time management skills.
Sharp analytical, problem-solving, and research skills.
Background in software development is preferred.
Location: United States; Canada; Australia; New Zealand; United Kingdom
About Gramian
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
About the Job
We are seeking experienced Hardware Engineers with strong programming skills and hands-on experience using AI Coding Agents to contribute to specialized AI training projects focused on complex, real-world engineering challenges.
This opportunity is intended for engineers who combine deep technical knowledge with practical implementation experience. You will design, solve, and evaluate engineering problems that require first-principles reasoning, quantitative analysis, simulation, coding, and reproducible technical solutions.
We particularly value engineers who have personally owned substantial technical work, such as bringing hardware systems into production, validating engineering models against physical test data, developing verification frameworks, or diagnosing complex hardware failures.
Practical coding ability and hands-on experience with AI Coding Agents are essential. We are looking for engineers who can independently write and execute code, use AI-assisted coding tools effectively, and validate their technical outputs. Academic qualifications alone are not sufficient without demonstrable engineering and programming capabilities.
Previous experience in AI model training is not required.
LOCATION: Remote – US, Canada, Australia, New Zealand, UK, SEA, and APAC
WORKLOAD: Approximately 15 hours per week.
SCHEDULE: Flexible; choose your working days and hours, including weekends.
COMPENSATION: Output-based, with payment per task that meets project specifications.
PROJECT: AI training focused on real-world hardware engineering problems.
AI CODING AGENT EXPERIENCE: Mandatory.
Key Responsibilities
Create technically rigorous, self-contained hardware engineering problems based on realistic industry and research scenarios.
Develop detailed reference solutions using engineering calculations, simulations, scripts, experimental reasoning, and other appropriate methods.
Design engineering tasks that require quantitative reasoning, technical judgment, and practical problem-solving.
Use programming and engineering software to model, simulate, analyze, and validate hardware systems.
Develop Python scripts and other computational tools to automate engineering calculations and validation workflows.
Evaluate engineering solutions against physical principles, technical specifications, and real-world operating constraints.
Validate engineering models and simulation results against experimental or physical test data.
Develop and apply verification and testing methodologies.
Investigate complex hardware failures, identify root causes, and recommend corrective actions.
Use AI Coding Agents to support engineering workflows, code development, debugging, and technical problem-solving.
Document methodologies, assumptions, calculations, and reference solutions to ensure results are reproducible and independently verifiable.
Requirements
Bachelor's, Master's, or PhD degree in Electrical Engineering, Mechanical Engineering, Mechatronics, Aerospace Engineering, Systems Engineering, Applied Physics, or a closely related discipline.
Significant professional or research experience in hardware engineering, product development, systems integration, testing, validation, reliability, or failure analysis.
Demonstrated ownership of substantial engineering work, such as:
Taking a hardware product or subsystem into production.
Validating engineering models against physical testing.
Developing engineering test or verification systems.
Diagnosing and resolving complex hardware failures.
Mandatory hands-on experience working with AI Coding Agents.
Strong practical programming skills and the ability to independently write, understand, debug, and execute code.
Experience using programming languages or engineering tools relevant to hardware development and analysis.
Ability to connect first-principles engineering knowledge with practical design and operational constraints.
Strong quantitative, analytical, and technical reasoning skills.
Ability to produce clear, technically accurate, and independently verifiable engineering solutions.
Strong written and spoken English communication skills.
Location: Singapore; Malaysia; Philippines; Indonesia; Thailand; Vietnam
About Gramian
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
About the Job
We are seeking experienced Hardware Engineers with strong programming skills and hands-on experience using AI Coding Agents to contribute to specialized AI training projects focused on complex, real-world engineering challenges.
This opportunity is intended for engineers who combine deep technical knowledge with practical implementation experience. You will design, solve, and evaluate engineering problems that require first-principles reasoning, quantitative analysis, simulation, coding, and reproducible technical solutions.
We particularly value engineers who have personally owned substantial technical work, such as bringing hardware systems into production, validating engineering models against physical test data, developing verification frameworks, or diagnosing complex hardware failures.
Practical coding ability and hands-on experience with AI Coding Agents are essential. We are looking for engineers who can independently write and execute code, use AI-assisted coding tools effectively, and validate their technical outputs. Academic qualifications alone are not sufficient without demonstrable engineering and programming capabilities.
Previous experience in AI model training is not required.
LOCATION: Remote – US, Canada, Australia, New Zealand, UK, SEA, and APAC
WORKLOAD: Approximately 15 hours per week.
SCHEDULE: Flexible; choose your working days and hours, including weekends.
COMPENSATION: Output-based, with payment per task that meets project specifications.
PROJECT: AI training focused on real-world hardware engineering problems.
AI CODING AGENT EXPERIENCE: Mandatory.
Key Responsibilities
Create technically rigorous, self-contained hardware engineering problems based on realistic industry and research scenarios.
Develop detailed reference solutions using engineering calculations, simulations, scripts, experimental reasoning, and other appropriate methods.
Design engineering tasks that require quantitative reasoning, technical judgment, and practical problem-solving.
Use programming and engineering software to model, simulate, analyze, and validate hardware systems.
Develop Python scripts and other computational tools to automate engineering calculations and validation workflows.
Evaluate engineering solutions against physical principles, technical specifications, and real-world operating constraints.
Validate engineering models and simulation results against experimental or physical test data.
Develop and apply verification and testing methodologies.
Investigate complex hardware failures, identify root causes, and recommend corrective actions.
Use AI Coding Agents to support engineering workflows, code development, debugging, and technical problem-solving.
Document methodologies, assumptions, calculations, and reference solutions to ensure results are reproducible and independently verifiable.
Requirements
Bachelor's, Master's, or PhD degree in Electrical Engineering, Mechanical Engineering, Mechatronics, Aerospace Engineering, Systems Engineering, Applied Physics, or a closely related discipline.
Significant professional or research experience in hardware engineering, product development, systems integration, testing, validation, reliability, or failure analysis.
Demonstrated ownership of substantial engineering work, such as:
Taking a hardware product or subsystem into production.
Validating engineering models against physical testing.
Developing engineering test or verification systems.
Diagnosing and resolving complex hardware failures.
Mandatory hands-on experience working with AI Coding Agents.
Strong practical programming skills and the ability to independently write, understand, debug, and execute code.
Experience using programming languages or engineering tools relevant to hardware development and analysis.
Ability to connect first-principles engineering knowledge with practical design and operational constraints.
Strong quantitative, analytical, and technical reasoning skills.
Ability to produce clear, technically accurate, and independently verifiable engineering solutions.
Strong written and spoken English communication skills.
Location: United States; Canada; Australia; New Zealand; United Kingdom
About Gramian
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
About the Job
We are looking for accomplished Competitive Data Scientists, Machine Learning Engineers, and Applied Mathematics Specialists with a proven track record in data science competitions, particularly on Kaggle and similar platforms.
This opportunity is designed for candidates who have achieved at least Kaggle Expert ranking, including Masters and Grandmasters, and can demonstrate strong practical skills in machine learning, statistical modeling, quantitative reasoning, and programming.
You will use your competition experience to design challenging, reproducible technical tasks that require genuine problem-solving rather than plausible-looking answers. Your work will involve building execution environments, implementing verified reference solutions, developing reliable evaluation criteria, and testing how AI Coding Agents perform against complex data science challenges.
A verifiable Kaggle profile with Expert, Master, or Grandmaster ranking is a key qualification. Strong practical coding and debugging abilities are essential. Previous AI training experience is not required.
LOCATION:
Remote – US, Canada, Australia, New Zealand, UK
WORKLOAD:
Approximately 15 hours per week.
SCHEDULE:
Flexible; choose your working days and hours, including weekends.
PROJECT:
AI training focused on competitive data science, machine learning, and reproducible technical problem-solving.
AI EXPERIENCE:
Not required.
Key Responsibilities
Design challenging data science and machine learning tasks inspired by real-world problems and competitive data science scenarios.
Build reproducible execution environments, prepare datasets, configure dependencies, and implement verified reference solutions.
Develop automated tests and evaluation criteria that distinguish correct solutions from incomplete, incorrect, or unreliable approaches.
Use coding agents to execute assigned tasks, investigate their failures, and evaluate their problem-solving capabilities.
Identify implementation errors, flawed assumptions, data leakage, statistical inconsistencies, and other issues affecting solution correctness.
Apply competitive data science techniques and mathematical reasoning to validate solutions.
Ensure tasks have clear requirements, reliable expected outputs, and reproducible verification procedures.
Refine task difficulty and evaluation methods based on observed coding-agent performance.
Document task specifications, solution methodologies, technical reasoning, and verification steps.
Review and improve task quality to ensure scientific and computational accuracy.
Requirements
Demonstrated experience in competitive data science, machine learning, quantitative modeling, or applied mathematics.
Kaggle profile with at least Expert ranking (Master or Grandmaster ranking strongly valued).
Ability to provide a verifiable Kaggle profile demonstrating competition achievements and ranking.
Strong understanding of machine learning, statistical modeling, data analysis, and quantitative problem-solving.
Practical programming ability, particularly in Python.
Ability to independently implement, test, debug, and verify data science solutions.
Experience working with datasets, computational environments, and relevant machine learning libraries.
Strong analytical reasoning and the ability to explain technical decisions.
Ability to identify data leakage, implementation flaws, and methodological errors.
Excellent written communication and technical documentation skills.
Professional English communication skills.
Location: India; Japan; South Korea; Taiwan; Hong Kong; Pakistan
About Gramian
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
About the Job
We are seeking experienced Hardware Engineers with strong programming skills and hands-on experience using AI Coding Agents to contribute to specialized AI training projects focused on complex, real-world engineering challenges.
This opportunity is intended for engineers who combine deep technical knowledge with practical implementation experience. You will design, solve, and evaluate engineering problems that require first-principles reasoning, quantitative analysis, simulation, coding, and reproducible technical solutions.
We particularly value engineers who have personally owned substantial technical work, such as bringing hardware systems into production, validating engineering models against physical test data, developing verification frameworks, or diagnosing complex hardware failures.
Practical coding ability and hands-on experience with AI Coding Agents are essential. We are looking for engineers who can independently write and execute code, use AI-assisted coding tools effectively, and validate their technical outputs. Academic qualifications alone are not sufficient without demonstrable engineering and programming capabilities.
Previous experience in AI model training is not required.
LOCATION: Remote – US, Canada, Australia, New Zealand, UK, SEA, and APAC
WORKLOAD: Approximately 15 hours per week.
SCHEDULE: Flexible; choose your working days and hours, including weekends.
COMPENSATION: Output-based, with payment per task that meets project specifications.
PROJECT: AI training focused on real-world hardware engineering problems.
AI CODING AGENT EXPERIENCE: Mandatory.
Key Responsibilities
Create technically rigorous, self-contained hardware engineering problems based on realistic industry and research scenarios.
Develop detailed reference solutions using engineering calculations, simulations, scripts, experimental reasoning, and other appropriate methods.
Design engineering tasks that require quantitative reasoning, technical judgment, and practical problem-solving.
Use programming and engineering software to model, simulate, analyze, and validate hardware systems.
Develop Python scripts and other computational tools to automate engineering calculations and validation workflows.
Evaluate engineering solutions against physical principles, technical specifications, and real-world operating constraints.
Validate engineering models and simulation results against experimental or physical test data.
Develop and apply verification and testing methodologies.
Investigate complex hardware failures, identify root causes, and recommend corrective actions.
Use AI Coding Agents to support engineering workflows, code development, debugging, and technical problem-solving.
Document methodologies, assumptions, calculations, and reference solutions to ensure results are reproducible and independently verifiable.
Requirements
Bachelor's, Master's, or PhD degree in Electrical Engineering, Mechanical Engineering, Mechatronics, Aerospace Engineering, Systems Engineering, Applied Physics, or a closely related discipline.
Significant professional or research experience in hardware engineering, product development, systems integration, testing, validation, reliability, or failure analysis.
Demonstrated ownership of substantial engineering work, such as:
Taking a hardware product or subsystem into production.
Validating engineering models against physical testing.
Developing engineering test or verification systems.
Diagnosing and resolving complex hardware failures.
Mandatory hands-on experience working with AI Coding Agents.
Strong practical programming skills and the ability to independently write, understand, debug, and execute code.
Experience using programming languages or engineering tools relevant to hardware development and analysis.
Ability to connect first-principles engineering knowledge with practical design and operational constraints.
Strong quantitative, analytical, and technical reasoning skills.
Ability to produce clear, technically accurate, and independently verifiable engineering solutions.
Strong written and spoken English communication skills.
Location: US, Boston, MA
Workplace: OnSite
Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.
ABOUT THE ROLE
We're hiring a Senior Prototype Engineer to join our Hardware team based in Boston. This is a hands-on role where you will rapidly iterate, assemble, diagnose, and evolve advanced robotic platforms for real-world use.
WHAT YOU’LL DO
- Lead troubleshooting and resolution of complex electrical issues in prototype humanoid robots, including operational and in-development systems; perform detailed failure analysis and share learnings with hardware/software engineering teams.
- Collaborate closely with multidisciplinary engineers on prototype design, assembly, and bring-up, especially high-density electromechanical integrations.
- Create, maintain, and execute clear test procedures, troubleshooting guides, and repair runbooks for the prototyping lab to ensure high standards and rapid iteration cycles.
- Design, document, and iterate on cable assemblies, test jigs, and harnesses optimized for repeated use on dynamic robotic platforms.
- Identify and own opportunities for continuous process and product improvement—minimizing downtime and improving test/repair efficiency.
- Contribute to robust feedback loops across design, build, and test, driving first-pass yield and manufacturability.
WHAT WE'RE LOOKING FOR
- Demonstrated experience in rapid physical prototyping, hands-on debug of custom hardware, and troubleshooting complex electrical systems in robotics or similar domains.
- Working knowledge of low-voltage and mixed-signal circuits, connectors, sensors, and compact electromechanical systems.
- Track record communicating concisely via documentation—procedures, test plans, diagnostics, and lessons learned.
- Adept collaborating across mechanical, electrical, and software engineering boundaries to solve urgent, ambiguous issues.
- Comfortable in a high-velocity, high-ambiguity startup setting where priorities shift fast.
- Experience designing for manufacturability and reliability in the context of human-sized or mobile robotics is a plus.
- Familiarity with automated test and diagnostic tools used in modern hardware labs.
WHAT WE OFFER
- Comprehensive health coverage for US‑based employees, including fully paid medical, dental, and vision insurance, with virtual care and employee assistance resources.
- Meaningful time off to rest and recharge: 23 days of PTO (accrued), separate sick leave, and paid company holidays.
- 401(k) retirement plan with 4% employer match.
- Equity included–we believe builders should share in what they build.
- Free daily catered lunch, snacks, and drinks in‑office.
- Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.
- Freedom to influence the product and own key initiatives.
For this role in Massachusetts, the expected base salary range is $115K–$160K USD per year; your placement in that range depends on how your experience maps to our internal leveling.
Location: Europe
Workplace: Remote
OUR VISION & PRODUCTS
🚀 EverAI — Building the Future of AI Companionship
One of the Top 15 Largest & Fastest-Growing AI Companies in the World
50 Million Users in 2 years — Help Us Reach 100M first, 500M next
At EverAI, we’re shaping what it means to connect with AI. With 50 million users and counting, we're not just building products — we're creating entirely new categories.
Our flagship product is the world’s largest AI companionship platform, redefining relationships for millions. It is governed by our proprietary moderation system, EverGuard — an internal AI designed to ensure everything we build is safe, ethical, and human-first.
And we’re only just getting started!
OUR TEAM
We are an enthusiastic, passionate and hardworking team of ≈ 100 people. Our founding team has strong entrepreneurial experience building and scaling web products from 0 to IPO.
Alexis Soulopoulos [CEO]
• 10+ years in Tech Executive Leadership
• Co-Founder Mad Paws Holdings (from 0 to IPO)
• Forbes 30 under 30 + Deloitte TechFast50 ’22 & ‘23
Michael Monin [Co-founder & CTO]
• 10+ years as CTO / COO (web2/web3), 3 years in AI/LLM
• Serial-entrepreneur: MTK Digital (exited / 0->$20m revenue) and Zipchat (AI Chatbot for E-commerce brands)
Thomas Lacroix [Co-founder & CMO]
• 8+ years in Customer Acquisition & E-commerce Growth
• Serial-entrepreneur: Curatible (sold to Blackstone) and MTK Digital (exited / 0->$20m revenue)
Maruša Fasano [CFO/Legal]
• 25+ years in Finance, Strategy, M&A
• Ex-CFO/M&A @Curatible (exited to Blackstone)
• Ex-President of the Board @SotremoSA (exited)
• Co-founder/CFO @SoftOne (exited)
YOUR ROLE
Most LLM roles stop at experimentation.
Here, the models you improve power experiences for 50M+ users.
Most of our traffic runs on self-hosted, fine-tuned open-weight models. On our internal roleplay evals, our smaller fine-tuned models can outperform much larger off-the-shelf models. Your job is to make them better.
You’ll join a small AI team led by Marco, our LLM Tech Lead, working closely with our CTO, Product, Web and DevOps teams. You’ll work across data, post-training, evals, and model behavior, taking ideas from failure analysis to production.
The problems are real: personalization, character consistency, long conversations, better evals, multilingual behavior, and faster training cycles.
If you want to shape model behavior at consumer scale, this is the role.
KEY RESPONSIBILITIES
- Fine-tune open-weight LLMs using SFT, LoRA/QLoRA and post-training methods such as DPO and GRPO
- Diagnose model failures and turn them into experiments. Decide whether the answer is better data, post-training, prompting or classifiers
- Build training data and evals that directly shape what gets trained next
- Improve model behavior across personalization, consistency, tone, multilingual and group interactions
- Ship to production and use real user behavior to guide the next iteration
- Speed up the training loop so experiments are faster, easier to compare, and more reproducible
YOUR QUALIFICATIONS
- You’ve personally post-trained open-weight LLMs for a user-facing product and shipped them to production
- You’ve worked where AI was core to the product or business, not an experimental side feature
- Fine-tuning is core to your experience
- Strong Python, PyTorch and Hugging Face, with hands-on GPU training and debugging
- You build data and evals yourself and make decisions from evidence
- You can take work beyond notebooks into production
- You use AI tools daily in your own engineering work
- You are fully comfortable working with uncensored models and explicit NSFW content, including harmful material when developing and evaluating moderation system
BONUS POINTS
- Experience with conversational AI, roleplay products, or highly personalized consumer AI
- Multilingual LLMs
- Moderation, safety, or adversarial testing
- Multimodal models
- Open-source LLM / post-training contributions
WHY EVERAI?
📈 Exponential Growth: From 50M users in 2 years, to 100M next — and 500M beyond
🚀 Track Record of Category-Creating Innovation: We consistently launch world-first AI applications — setting the pace, not following it
🌍 Global Impact: Top-tier user growth, real-world adoption, and cultural relevance
🧠 Proven Leadership: A senior team that’s launched, scaled, and exited & IPO’d multiple scale ups — now fully focused on reshaping AI companionship
👥 Elite Remote Team: 100% remote and built to win — world-class talent from Tier 1 tech companies, with a culture of ownership, velocity, and radical creativity
🛡️ Ethical Core: Our AI ecosystem is governed by EverGuard, our proprietary AI moderation technology, ensuring responsible development at scale
WHAT WE OFFER
✍️ Contract Type: We prefer B2B, but we’re flexible, what matters is long-term commitment and impact
📍 Work From Anywhere: Fully remote. Choose the environment where you do your best work
🏝️ Paid Time Off: 4 weeks (20 working days) of PTO per year to recharge and reset
👨👩👧👦 Annual Gathering: A yearly in-person meetup to connect, brainstorm, and celebrate wins together
❤️🩹 Health & Wellness Support: Monthly allowance of 100 USD for health insurance expenses & access to unlimited 1:1 sessions with psychologists and lifestyle experts through OpenUp (also available to up to three of your family members)
🏢 Co-Working Space Budget: Work from a co-working space up to twice per month (35 EUR / 40 USD per visit) to stay inspired and connected
📚 Learning Budget: Dedicated funds to support your professional growth: courses, books, conferences, events, or certifications
💻 Company Laptop & Equipment: Laptop provided + monitor budget up to 250 USD + keyboard/mouse/mic/headphones budget up to 150 USD
⚡ AI Tools Access: Premium access to ChatGPT, Hugging Face, Claude Code, and any other tool needed to excel at your job, power your ideas and workflows
🎯 TOP TIER TALENT IS OUR MULTIPLIER
We’re a fully remote group of A-players from Tier 1 tech, led by an exec team who’ve launched, scaled, and exited multiple companies. We move fast, and care deeply about what we build — and who we build it with.
We’re looking for exceptional talent ready to ship & distribute world-first AI products at scale, fast, and co-create with us this category-defining business.
If that’s you — reach out and apply!
Location: Remote, United States
GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster.
The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems.
Co-create the future with us
as we build technology that transforms how the world develops software.
*
Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab.
An overview of this role
As a Staff Backend Engineer on GitLab's Core DevOps team, you'll provide technical leadership across your team and adjacent teams. You'll lead large backend initiatives, guide the modernization of a large monolith into modular, reusable, appropriately independent systems, and set standards that help teams move faster without compromising quality, security, reliability, or operability.
You'll work with Product, Frontend, Infrastructure, Security, Data, Engineering Managers, and engineers across product groups. You'll lead complex backend architecture, make product trade-offs, and influence technical direction without formal authority.
GitLab is an open core software company that develops an artificial intelligence-powered DevSecOps platform. Our mission is to enable everyone to contribute to and co-create the software that powers our world. We work in an all-remote, asynchronous environment where you communicate decisions clearly in writing and work independently.
What you’ll do
Lead the technical design and delivery of backend initiatives that span teams, and identify and remove systemic bottlenecks across product and infrastructure groups.
Drive modular backend, service, data, and platform architecture, including modernization of the monolith and legacy backends while preventing fragmentation and service sprawl.
Define and improve standards for application programming interfaces, contracts, compatibility, schema evolution, testing, security, performance, observability, operability, and maintainability.
Establish patterns for dependency management, data ownership, eventing, failure isolation, service maturity, and operational documentation.
Establish Go service patterns and Kubernetes operating practices where they matter to the production estate, and guide Rust adoption where it addresses systems, security, performance, or supply-chain needs.
Take part in on-call and incident response for systems your teams own, serve as a technical escalation point during complex incidents, and turn lessons from incidents into lasting improvements.
Partner with Product and Engineering leadership on platform roadmap decisions and investment trade-offs.
Mentor Senior and Intermediate engineers, reduce technical debt, build reusable patterns that improve team throughput, and lead adoption of artificial intelligence-assisted and agentic workflows with quality, security, privacy, and operational guardrails.
Take part in on-call or operational support where your team’s ownership model requires it.
What you’ll bring
A record of leading technical work across more than one team or a broad product area.
Deep backend architecture and production experience with complex applications, services, or platforms, including application programming interfaces, service platforms, data systems, modular monoliths, or shared backend components.
Experience modernizing a monolith or legacy backend architecture in production and using modular approaches such as bounded contexts, package encapsulation, ports and adapters, service extraction, or event-driven boundaries.
Experience building alignment through clear written proposals and decision records so teams document, understand, and adopt technical decisions.
Experience making trade-offs among customer outcomes, delivery speed, technical health, reliability, and long-term platform investment.
Experience mentoring engineers and shaping standards through code review, documentation, and practice.
Production experience with artificial intelligence-assisted or agentic engineering workflows, including improving how a team adopts them.
Due to customer requirements, you must be a United States Citizen (defined as any individual who is a citizen of the United States by law, birth, or naturalization) to fill this position
About the team
The Core DevOps team owns core repository capabilities, from Git command-line operations to web-based code exploration. We build features and platforms, improve existing capabilities, and improve maintainability, accessibility, performance, and workflows for teams using artificial intelligence-assisted development tools.
The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our
benefits
and
equity
. Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary.
United States Salary Range
$152,800
—
$259,200 USD
How GitLab Supports Full-Time Employees
Benefits to support your health, finances, and well-being
Flexible Paid Time Off
Team Member Resource Groups
Equity Compensation & Employee Stock Purchase Plan
Growth and Development Fund
Parental Leave
Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from
underrepresented groups
are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application.
Country Hiring Guidelines:
GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process.
Privacy Policy:
Please review our
Recruitment Privacy Policy.
Your privacy is important to us.
GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also
GitLab’s EEO Policy
and
EEO is the Law
. If you have a disability or special need that requires
accommodation
, please let us know during the
recruiting process
.
Location: 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
How do we know whether a model is safe - and how do we know whether the systems we built to catch misuse actually catch it?
Anthropic answers both questions with evaluations. We measure model behavior across misuse, prompt injection, and user well-being to inform training and deployment decisions. We also use AI to investigate potential misuse of Claude, analyzing real-world traffic to surface bad actors and emerging threats that drive enforcement actions. Neither is worth much unless the evaluations behind them are representative, robust, and trustworthy.
This role builds the methods and infrastructure that make them so. Sitting at the intersection of applied ML research and engineering, you'll design experiments to improve how we evaluate both model behavior and the agentic systems that govern it, build datasets that represent real abuse rather than clean approximations of it, and ship those methods into the pipelines that gate model training, agent changes, and launch decisions.
Responsibilities
Evaluation research and methodology.
Design and run experiments to improve evaluation quality — developing methods to generate representative test data, simulate realistic user behavior, and validate grading accuracy. Research how different factors (multi-turn conversations, tools, long context, user diversity) impact model safety behavior. Analyze evaluation coverage to identify measurement gaps, and evolve evals so they remain unsaturated and high-signal as model and agent capabilities advance.
Agentic investigation evals.
Build and own the evaluation harness for an agentic investigation system — defining metrics, test cases, and grading approaches for a complex, long-horizon agent. Measure agent performance end-to-end (detection precision and recall, investigation quality, robustness) and drive hill-climbing on the hardest harm areas. Construct RL environments to improve Claude's safety investigation capabilities.
Datasets grounded in real harm.
Construct high-quality eval datasets representing real-world misuse across harm areas such as cyber attacks, bio weapons, and influence operations, drawing from both real traffic patterns and synthetic generation. Collaborate with Policy and Enforcement to translate observed harm patterns into measurable evaluations.
Productionization and tooling.
Ship successful research into evaluation, regression, and release pipelines that run during model training, on every agent change, prompt update, and underlying model upgrade, and beyond launch. Build tooling that enables policy experts to author, run, and iterate on evaluations without engineering support. Surface findings to research and training teams to drive upstream model improvements.
Minimum qualifications
Experience building and maintaining data pipelines
Experience working with LLMs and a working understanding of their capabilities and failure modes — especially agentic systems with tool use and multi-step reasoning
Strong data analysis skills — you can draw reliable insights from large datasets
Ability to move fluidly between research prototyping and production-quality code
Ability to translate ambiguous problems into concrete, testable experiments
Care deeply about AI safety and want your work to have real impact
Preferred qualifications
8+ years of industry software engineering or ML engineering experience
Expertise in building or contributing to LLM or agent evaluation frameworks, benchmarks, or automated grading systems
Extensive experience in trust and safety, content moderation, or abuse detection systems
Experience in red teaming, adversarial testing, or jailbreak research on AI systems
Experience with synthetic data generation or data augmentation
Experience with distributed systems or large-scale data processing
Experience with prompt engineering or building LLM-powered applications
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:
$320,000
—
$485,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: Poland; Portugal; Ukraine
Workplace: Remote
Help scale the infrastructure behind a real-time iGaming platform serving 150M+ players worldwide while leading our SRE and Platform Engineering teams.
ABOUT PATRIANNA
At Patrianna, we build a high-performance B2B platform for the global iGaming industry, enabling partners to launch and scale digital gaming products across multiple international markets. Our platform serves as the foundation for multiple gaming brands, providing the core systems that power gameplay, integrations, and platform capabilities across different markets.
We operate in a fast-moving scale-up environment where impact matters more than process for its own sake. Teams are trusted to take ownership of the systems they build and the outcomes they deliver.
Our engineering culture is built around a few core principles:
- Pragmatic execution: We focus on solving meaningful engineering problems and delivering reliable systems without unnecessary bureaucracy;
- Clear ownership and accountability: Teams operate within defined responsibilities and leadership structures that ensure decisions are made and outcomes are delivered;
- Technical depth matters: We value engineers and managers who understand their systems deeply and make thoughtful technical decisions;
- Direct communication: We address problems openly, challenge assumptions, and resolve issues quickly.
We believe strong engineering leadership starts with technical credibility and ownership of outcomes.
AI-DRIVEN ENGINEERING CULTURE
We are actively building an AI-driven engineering organization with a clear and deliberate stance: artificial intelligence is a core part of how we build and deliver software — not an experiment, not a trend, and not an optional add-on.
AI is embedded into our engineering workflows, from system design and prototyping to refactoring, testing, and code review. We expect engineers to be fully comfortable working in AI-driven environments and to treat AI as a primary productivity multiplier. Strong engineering judgment, architectural ownership, and accountability remain essential—AI amplifies our engineers, it doesn’t replace responsibility for technical decisions.
THE ROLE
We are looking for a hands-on Engineering Manager to lead our DevOps function across two specialized engineering teams: Site Reliability Engineering (SRE) and Platform Engineering.
The SRE team is focused on production reliability, availability, observability, incident management, operational excellence, and continuously improving the resilience of our systems.
The Platform Engineering team works on larger strategic initiatives that evolve our infrastructure and engineering platform — improving scalability, automation, developer experience, deployment capabilities, infrastructure architecture, and operational efficiency.
You will be responsible for ensuring both teams have clear roadmaps, well-defined priorities, realistic commitments, and strong execution. You will create the structure and engineering practices necessary for teams to deliver complex infrastructure initiatives predictably while maintaining the reliability of a rapidly growing production platform.
This is not a coordination-only management role.
We expect our DevOps Engineering Manager to have deep technical expertise and remain close to the technology. You should be capable of understanding infrastructure architecture in depth, challenging technical decisions, reviewing proposed solutions, troubleshooting complex production problems, and working hands-on with the platform when necessary.
You will combine the technical depth of a senior DevOps/Platform engineer with strong engineering and operational management, delivery, and people leadership skills.
WHAT YOU WILL BE DOING
Management & Delivery:
- Own the DevOps roadmap and delivery outcomes – establish clear roadmaps across SRE and Platform Engineering, translate priorities into concrete initiatives and commitments, and ensure teams deliver against realistic timelines;
- Drive predictable execution – establish effective planning and execution practices, track progress against commitments, identify delivery risks early, manage dependencies, and ensure clear ownership of initiatives;
- Lead SRE and Platform Engineering – provide leadership across both operational reliability and longer-term platform development, balancing immediate production needs with strategic infrastructure improvements;
- Own people management – manage and develop DevOps engineers, including performance reviews, career development, compensation and promotion input, hiring, team structure, and handling performance concerns when needed;
- Partner with engineering teams – work closely with Engineering Managers, Team Leads, and engineers across the organization to understand infrastructure needs, resolve systemic problems, and ensure the platform enables rather than blocks product delivery.
Technical Leadership:
- Provide hands-on technical leadership – stay close to infrastructure and production systems, participate in architecture discussions, challenge technical decisions, review proposed solutions, and contribute directly when complex problems require it;
- Drive platform reliability – continuously improve availability, resilience, observability, incident response, capacity management, and operational readiness across the platform;
- Strengthen incident management – ensure incidents are handled effectively, root causes are understood, postmortems produce meaningful actions, and recurring operational problems are systematically eliminated;
- Evolve the engineering platform – drive initiatives around Kubernetes, cloud infrastructure, CI/CD, GitOps, Infrastructure as Code, observability, scalability, security, and developer experience;
- Improve engineering effectiveness – identify bottlenecks, repetitive operational work, and inefficient processes, and drive automation and platform improvements that increase engineering productivity;
- Drive infrastructure efficiency – continuously evaluate infrastructure architecture, resource utilization, and cloud costs, identifying opportunities to improve performance and reliability while keeping the platform cost-efficient.
WHAT WE ARE LOOKING FOR
Leadership & Management Requirements:
- Engineering leadership experience – proven experience leading infrastructure, DevOps, SRE, or Platform Engineering teams while balancing technical leadership, delivery ownership, and people management;
- Strong delivery ownership – ability to build realistic roadmaps, break complex technical initiatives into executable work, establish commitments and deadlines, identify risks, and drive initiatives through to completion;
- Strong communication skills – able to communicate clearly with engineers and leadership, challenge assumptions constructively, explain technical trade-offs, and create alignment around priorities and decisions.
Technical Requirements:
- Deep hands-on DevOps expertise – extensive experience building and operating production infrastructure, with the technical depth expected from a Senior/Lead/Staff-level DevOps, SRE, or Platform Engineer;
- Strong Google Cloud Platform experience – deep production experience with GCP, including GKE, Compute Engine, networking, IAM, DNS, load balancing, and cloud cost optimization;
- Deep Kubernetes expertise – strong understanding of Kubernetes architecture, networking, ingress, storage, autoscaling, security, cluster lifecycle, and production troubleshooting;
- Infrastructure as Code expertise – strong production experience with Terraform/Terragrunt, Helm, and infrastructure automation;
- CI/CD and GitOps expertise – strong experience designing and operating modern delivery platforms using technologies such as Argo CD, GitHub Actions, Jenkins, or Azure DevOps;
- Strong production operations background – experience operating high-availability production environments, participating in on-call rotations, troubleshooting distributed systems, and leading incident response;
- Observability expertise – strong understanding of metrics, logs, tracing, alerting, SLOs, and production monitoring using technologies such as Prometheus, Grafana, Loki/ELK, or similar platforms;
- Strong systems thinking – ability to reason about complex distributed systems, understand dependencies and failure modes, and make pragmatic architectural trade-offs across reliability, scalability, delivery speed, and cost.
NICE TO HAVE
- Experience leading both SRE and Platform Engineering teams;
- Experience operating high-load, real-time distributed platforms;
- Experience defining and operating SLOs, SLIs, and error budgets;
- Experience building internal developer platforms or developer self-service capabilities;
- Experience with Kafka and large-scale event-driven systems;
- Experience with PostgreSQL/AlloyDB and Redis;
- Experience driving cloud infrastructure cost optimization / FinOps initiatives;
- Experience in iGaming;
- Experience working in product companies or fast-growing scale-ups;
- Previous experience as a Staff/Principal DevOps Engineer, SRE, Platform Engineer, or Infrastructure Architect.
OUR TECH STACK
- Google Cloud Platform;
- Kubernetes / GKE;
- Terraform / Terragrunt;
- Helm;
- Argo CD;
- Jenkins / GitHub Actions / Azure DevOps;
- Kafka;
- AlloyDB for PostgreSQL;
- Redis / Memcached;
- Prometheus / Grafana;
- Loki / ELK;
- Sentry;
- Jira / Confluence / Slack / Bitbucket.
WHAT SUCCESS LOOKS LIKE IN THIS ROLE
After 3 months: You understand our infrastructure architecture, production environment, operational challenges, and the responsibilities of the SRE and Platform Engineering teams. Both teams have clear ownership, priorities, and roadmaps.
After 6 months: SRE and Platform Engineering operate against clear commitments with predictable execution. Reliability and operational problems are systematically tracked and addressed, while strategic platform initiatives move forward according to the roadmap.
After 12 months: The DevOps function operates as a high-performing engineering organization with strong technical ownership, predictable delivery, mature reliability practices, and a platform roadmap that measurably improves scalability, developer productivity, operational efficiency, and infrastructure reliability.
WHY YOU’LL LOVE IT
You’ll have significant ownership over the infrastructure and engineering platform behind systems serving millions of players worldwide.
You’ll work on problems where reliability, scalability, automation, developer productivity, and infrastructure architecture have direct business impact.
This role allows you to shape both how our production platform operates today and how our engineering platform evolves for the future.
You’ll lead highly technical engineers while remaining close enough to the technology to influence architecture, solve difficult engineering problems, and see the direct impact of your decisions.
We operate with minimal bureaucracy, fast decision-making, and a strong expectation of ownership.
What's on offer:
1. Full remote flexibility — work from wherever you do your best thinking;
2. Generous paid time off, including vacation, sick leave, and bank holidays;
3. Genuine, unlimited growth opportunities in a fast-scaling business;
4. Engaging company events and a team that actually enjoys working together.
Location: United States; San Francisco; Canada; New York; Ottawa; Toronto; Montreal
Workplace: Hybrid
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!
WHY THIS ROLE?
We're building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most driven, and most curious people to help us do it. As the founding lead of Agentic Analytics, a new team in our Analytics and Data Insights organization, you'll own how Cohere gets answers from its own data: an agentic analytics system that answers business questions over governed data, shows the source, query, and freshness behind every answer, and asks for clarification or declines when the evidence is insufficient.
Agentic analytics is far from a solved problem, and correctness is the hard part. A query that runs can still answer the wrong question. Agents go wrong when a business term maps to more than one table, when data goes stale, and when the right context never reaches the model. The worst failures are silent and plausible: a join that double-counts, a wrong denominator, missing data read as zero. Getting this right takes governed definitions, context an agent can use, and an evaluation bar that decides what ships.
You'll build on work already in motion: an internal analytics agent in pilot on our BigQuery warehouse, which is fed by tested ingestion pipelines and modeled in dbt. In your first year, you'll take it to production for teams across Cohere, one domain at a time, and make it replicable: each new domain stands up with configuration, a fresh evaluation set, and very little new code.
This is a hands-on staff engineering role reporting to our Senior Director of Data Analytics. You'll write production code and evaluation sets yourself while managing a small founding team that grows as the system proves itself. You may have held the title software engineer, AI engineer, or data scientist; what matters is that you've built a system like this and run it in production.
RESPONSIBILITIES
As the lead of Agentic Analytics, you will:
- Own the system end to end. Set the architecture for how a business question becomes a governed query and a verifiable answer: interpreting the question, retrieving the right context, applying approved definitions and joins, enforcing the asking user's permissions, and attaching the evidence (source, query, freshness) to every answer.
- Build and run it in production. Design the core services and write much of the first version yourself: agent-facing data tools (MCP or equivalent), context retrieval, agent skills for analytics, and the APIs that serve answers. Hold them to production standards for reliability, latency, cost, security, and observability. Put it where people already work: Slack, North, IDEs, and other agents.
- Hold every release to the evaluation bar. Build and run the evaluation harness, and define what correct means in each domain: ground-truth question sets, including held-out cases and questions the agent should clarify or decline; result-level scoring, correct-or-decline rates, coverage, and error severity; and regression tests on every change to context, skills, or models. Nothing ships below the bar, and the call on when a domain is ready for production is yours.
- Engineer the context layer. Turn metric definitions, approved joins, documentation generated from the code that builds each table, a business glossary, and worked examples into context the agent can use. Every correction becomes a reviewed definition and a regression test.
- Roll it out across Cohere. Bring domains such as marketing, revenue, finance, and product onto the system one at a time, each with named owners, certified definitions, and its own evaluation set. Measure adoption, accuracy, turnaround, and correction effort against how those teams work today.
- Make it replicable. Package the tools, skills, context templates, and evaluations, and document them well enough that other teams at Cohere can run the system without you.
- Hire and lead the team. Bring on the team's first engineers, set the technical bar, review the work, and develop the people doing it.
- Partner across Cohere. Work with our data platform team on the warehouse and semantic models, our model evaluation team on evaluation methodology, our security team on access, and each domain's owners on definitions and rollout.
QUALIFICATIONS
You may be a good fit, if you have:
- 10+ years building and operating production analytics or software systems, including technical leadership of a team or of systems that span teams
- Experience shipping LLM agents to production: tool use, MCP or similar, retrieval and context engineering, guardrails, and observability, with firm opinions on where they fail
- Hands-on experience building natural-language or agentic analytics (text-to-SQL, analytics agents, question answering over a semantic layer) that real users relied on, and evidence that it was right
- Depth in evaluating LLM systems: golden sets, result-level comparison, abstention metrics, error taxonomies, and regression testing in CI, plus the judgment to tell a good demo from a system you'd put in front of a CFO
- Strong Python and SQL, and experience designing and running production services and APIs on a major cloud (Google Cloud is a plus)
- Fluency with data: cloud warehouses (BigQuery, Snowflake, or similar), dbt, and semantic layers (MetricFlow, LookML, Cube, or similar). You think in grain, metric definitions, and approved joins, and you can tell when a number is wrong before it reaches a decision
- Experience building identity-aware access for agents, where the agent acts with the asking user's permissions and every query leaves an audit trail
- Experience hiring and developing engineers, with a leadership style grounded in empathy as much as in data
- Genuine excitement about AI: you follow the research, have opinions, and enjoy being in the weeds
- Comfort operating in ambiguity, leading through partners you don't manage, and writing design docs and eval reports that settle decisions across teams
If some of the above doesn't line up perfectly with your experience, we still encourage you to apply!
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: Latin America
Workplace: Remote
The company is a service for managing email outreach infrastructure. We help customers register and connect domains, create mailboxes, and configure them to work with email-sending tools.
We are looking for two experienced technical support engineers who enjoy understanding how a product works, finding the causes of unusual issues, and gradually getting more involved in software development.
ABOUT THE ROLE
You will work at the intersection of customer support and the engineering team: handling complex support requests, carrying out technical diagnostics, and seeing issues through to resolution.
First-line support handles routine questions. Your responsibility will be cases that require examining logs, checking settings, understanding API behavior, or reading code. If a solution requires changes to the product or infrastructure, you will pass your investigation findings to developers and help verify the fix.
WHAT YOU WILL DO
• Investigate technical support requests: reproduce issues, test hypotheses, and identify their root causes.
• Diagnose problems with domain registration and verification, DNS records, and the creation and connection of mailboxes.
• Investigate integration failures involving email providers and email outreach services, as well as authentication and access errors.
• Investigate issues with email sending and deliverability.
• Work with logs, APIs, internal tools, and data; write small scripts for diagnostics and automation.
• Resolve support requests independently within your scope of responsibility; involve developers or external provider support when needed.
• Clearly explain to customers and colleagues what is happening and what the next steps are.
• Contribute to the knowledge base, improve instructions, and hand over unresolved investigations to the next shift.
EXAMPLES OF TASKS
• Mailboxes have been created, but the required MX and SPF records have not appeared.
• A domain fails verification or is already linked to another Microsoft 365 tenant.
• After access permissions are changed, a mailbox stops connecting to an external service.
• A customer reports email deliverability problems: you need to gather information and investigate possible causes.
• The subscription status reported by a provider does not match the state of the mailboxes in the product.
WHAT WE ARE LOOKING FOR
• Experience in L2/L3 technical support, SaaS operations/support, system administration, or software development involving troubleshooting of user-reported issues.
• Ability to investigate issues independently: gather facts, isolate the problem, and verify the solution.
• Understanding of HTTP, REST APIs, JSON, authentication principles, and how web services interact.
• Confidence working with logs, the command line, and tools such as curl or Postman.
• Ability to read other people’s code and write small scripts in at least one programming language. JavaScript/TypeScript is especially useful.
• Basic SQL knowledge and the ability to work carefully with data.
• Understanding of DNS and the fundamentals of how email works.
• English sufficient for written communication with customers, providers, and the team, as well as reading documentation.
• A responsible approach: honoring shift commitments, keeping request statuses up to date, and following tasks through to completion.
NICE TO HAVE
• Experience at a domain registrar, hosting provider, email service, or email outreach platform.
• Experience working with Google Workspace, Microsoft 365, and Cloudflare.
• Knowledge of SMTP, IMAP, SPF, DKIM, and DMARC, plus hands-on experience troubleshooting deliverability.
• Experience with cloud platforms, monitoring, Git, Node.js, or NestJS.
Location: Foster City, CA
Workplace: Hybrid
Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation.
About the role:
Make Replit the single place where businesses can buy everything they need through their agents. As a Staff Software Engineer on Replit’s Money team, you’ll set technical direction and build the commerce platform that lets users discover, evaluate, purchase, and manage the products and services they need to build and run their businesses—without leaving Replit.
Replit already enables businesses to accept payments through integrations such as Stripe. This role builds on that foundation to expand what businesses can buy and accomplish through Replit Agent. You’ll design commerce experiences that combine the simplicity consumers expect with the controls enterprises need, making agent-assisted purchasing useful, trustworthy, and reliable.
You’ll own architecture and lead cross-team delivery across merchant and service-provider integrations, agent tools, purchasing workflows, and the lifecycle after a transaction. The challenge goes beyond executing a payment: agents need to understand what a user wants, present clear choices and costs, act within delegated authority, and verify that the purchase delivered the intended outcome. You’ll stay hands-on with design and code while aligning partners, mentoring engineers, and turning an ambitious product vision into incremental customer value.
You will:
- Set technical direction for Replit’s financial infrastructure, with an immediate focus on enterprise billing, spend controls, and financial correctness.
- Build shared services for usage-based billing, pricing, credits, subscriptions, and entitlements so product teams can launch without rebuilding billing.
- Automate enterprise contract lifecycles—from onboarding through amendments and renewals—keeping commercial terms, provisioned credits, and invoices in sync.
- Build timely budget enforcement, alerts, and overrides that give customers control over spend without disrupting their hosted apps.
- Make AI usage understandable: attribute costs to the right customer, workspace, user, or agent, including delegated work without double-counting.
- Build reconciliation and audit trails that make balances and invoices explainable and help Finance catch discrepancies before customers do.
- Simplify the billing stack through safe migrations that preserve balances, transaction history, and customer access.
- Own production reliability through testing, observability, incident response, and safe recovery from duplicate events, delayed usage, and partial failures.
- Stay hands-on while leading cross-team delivery, mentoring engineers, and partnering with Product, Finance, Sales, and Support.
Required skills and experience:
- A track record of Staff-level technical ownership: setting architecture and delivering complex initiatives across teams.
- Deep experience building and operating production backend or distributed systems.
- Strong fundamentals in API design, data modeling, databases, and event-driven architecture.
- Sound judgment around transactions, consistency, concurrency, idempotency, and failure recovery.
- Experience evolving live systems and migrating data without compromising correctness or availability.
- Product judgment that balances customer needs, delivery speed, and long-term system quality.
- Clear communication with technical and non-technical partners, including translating business requirements into system behavior.
- Hands-on leadership through implementation, design reviews, mentoring, and production ownership.
Preferred Qualifications
- Experience with billing, payments, subscriptions, credits, entitlements, or other financial systems.
- Experience with enterprise contracts, negotiated pricing, invoicing, or quote-to-cash automation.
- Experience with high-volume usage metering, pricing calculations, or low-latency spend controls.
- Experience building reconciliation, financial reporting, or auditable transaction histories with Finance and Accounting.
- Experience integrating billing, payment, or CRM platforms, with judgment about what to build versus buy.
Bonus Points:
- Experience with AI or cloud infrastructure billing, including variable costs and attribution across distributed workloads.
- Experience building customer-facing spend visibility, budgets, or internal tools that reduce manual billing work.
- Experience with cloud marketplace billing, payment recovery, or fraud and dispute workflows.
- Familiarity with agentic commerce or delegated spending. These are additional strengths, not requirements.
What we value:
- Customer outcomes: success means a business can get what it needs through its agent, with clear costs and a verified result—not merely a completed API call.
- User control and trust: agents act within explicit authority, surface consequential choices, and make purchases and ongoing commitments understandable.
- Consumer simplicity and enterprise readiness: straightforward experiences should coexist with the controls organizations need.
- End-to-end ownership: we own the experience from intent through purchase, fulfillment, and ongoing management.
- Pragmatic technical leadership: we build on what exists, deliver incremental value, and invest in correctness and extensibility where they matter.
- Clear collaboration: we document decisions, surface risks early, and help other teams and partners succeed.
Full-Time Employee Benefits Include:
💰 Competitive Salary & Equity
💹 401(k) Program with a 4% match (US Only)
⚕️ Health, Dental, Vision and Life Insurance
🩼 Short Term and Long Term Disability
🚼 Paid Parental, Medical, Caregiver Leave
🏝 Flexible Time Off (FTO) + Holidays
🚗 Commuter Benefits (In-Office & US Only)
📱 Monthly Wellness Stipend
🧑💻 Autonomous Work Environment
🖥 In Office Set-Up Reimbursement (In-Office Only)
🚀 Quarterly Team Gatherings
☕ In Office Amenities (In-Office Only)
Want to learn more about what we are up to?
- Self-driving Company https://replit.com/blog/self-driving-company
- Replit Agent at Scale https://replit.com/blog/evaluating-and-improving-agent-at-scale
- AI Adoption https://replit.com/blog/ai-adoption
- Build Open-Source Apps https://replit.com/build/open-source-app-builder
Interviewing + Culture at Replit
- Operating Principles https://blog.replit.com/operating-principles
- Reasons not to work at Replit https://blog.replit.com/reasons-not-to-join-replit
To achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.
Location: San Francisco, CA • New York, NY • United States
Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us!
We’re hiring a Researcher, AI Evaluations to join AI Insights within Figma’s Research team. This is a senior individual contributor role with no direct reports, reporting to the AI Insights lead and working directly with AI Research within AI Platform. You’ll strengthen the team’s model, agent system, and evaluation work through hands-on studies, clear rubrics, and reliable measures of quality that reflect user needs, and your findings will guide model and product improvements.
This is a full time role that can be held from one of our US hubs or remotely in the United States.
What you’ll do at Figma:
Own evaluation research for priority AI Research workstreams. Define quality criteria, design studies, analyze results, and recommend actions
Build rubrics, representative evaluation datasets, benchmarks, and quality thresholds that reflect user needs and expert design judgment
Work with AI Research and Modeling Platform engineers to integrate validated methods into repeatable evaluations and regression tests
Explain quality, failure patterns, and uncertainty. Recommend actions that guide model selection, model improvements, product priorities, and release decisions
Validate automated graders against human ratings, including LLM-as-judge methods that use a large language model to score outputs. Identify bias, gaps, and uncertainty
Connect user research with AI Research’s model development work. Share reusable methods, review work, and mentor peers
We’d love to hear from you if you have:
7+ years of experience in research, applied research, or a related field, with a proven track record of independently leading complex evaluation projects and delivering measurable impact
Hands-on experience evaluating AI products, with demonstrated ability to translate evaluation findings into meaningful model and product improvements
Expertise in designing human evaluations, scoring rubrics, datasets, and benchmarks, including measuring inter-rater agreement and validating automated graders
Strong qualitative and quantitative research skills, with the ability to analyze data, interpret uncertainty, and draw actionable insights into model behavior and performance
Excellent problem-solving and stakeholder management skills, with the ability to navigate ambiguity, prioritize risks, balance speed with rigor, and deliver recommendations that influence cross-functional decisions
While it’s not required, it’s an added plus if you also have:
Experience integrating automated evaluations and regression testing into engineering workflows, with familiarity in tools such as Braintrust, LangSmith, DeepEval, or equivalent platforms
Proven ability to develop scalable, reusable evaluation frameworks and drive the adoption of consistent quality standards across teams
Background in product design, product management, data science, or engineering, with familiarity in Figma or similar design and developer tools
Strong statistical expertise in sampling, significance testing, and agreement metrics, with experience conducting experiments or analyzing performance metrics for AI-powered features
Advanced training in a quantitative or behavioral discipline, gained through formal education or equivalent hands-on experience
At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
Pay Transparency Disclosure
Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location.
Figma offers equity to employees, as well as a competitive package of additional benefits, including health, dental, and vision coverage; retirement benefits with company contributions; parental leave and reproductive or family planning support; mental health and wellness benefits; and paid time off. Figma provides paid sick leave, holidays, and other leave benefits in compliance with applicable federal, state, and local laws, including the requirements of the Washington Minimum Wage Act and related regulations. Exempt employees are eligible for employer‑provided paid flexible PTO in addition to flexible paid sick leave. PTO is subject to manager approval. Additional benefits may include company recharge days, cell phone and home internet reimbursements, and a number of lifestyle spending accounts. Figma also offers sales incentive compensation for most sales roles and an annual bonus plan for eligible non-sales roles. All compensation and benefits are subject to applicable plan terms and may be modified by Figma at any time, consistent with applicable law.
Annual Base Salary Range:
$169,000
—
$250,000 USD
At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an
equal opportunity workplace
- we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status
,
or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to
accommodations-ext@figma.com
. These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities.
Examples of accommodations include but are not limited to:
Holding interviews in an accessible location
Enabling closed captioning on video conferencing
Ensuring all written communication be compatible with screen readers
Changing the mode or format of interviews
To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding.
By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with
Figma's Candidate Privacy Notice
.
Application limits:
To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles:
Candidates may submit up to 5 applications during any rolling 30-day period.
Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection.
Once the applicable days has passed, candidates are welcome to apply again.
Location: Hamburg
adjoe builds the technologies behind mobile apps growth and monetization. With our core product Playtime Arcade, we've become the global leader in rewarded advertising, an ad unit built on a simple premise: users earn real in-app rewards for engaging with new apps. The result is one of the most effective value exchanges in adtech, connecting advertisers and publishers with over 770 million users annually.
Architecting Intelligence to Optimize 200M+ Daily Decisions
As the intelligence core of our engineering organization, our Data Science team doesn't just deploy models, we engineer the fundamental decision engine that powers our platform. At a scale of 770 million users and 100,000+ predictions per second, we are solving a multi-objective optimization problem that balances user incentives, advertiser ROI, and long-term platform health in real time.
Our architecture is built on a 1PB+ behavioral data lake, providing the high-fidelity input necessary to train deep learning models that predict individual user engagement with precision. We aren't just optimizing clicks, we are dynamically calculating optimal reward structures to sustain a global value exchange.
Engineered for performance, our stack leverages PyTorch for model training, NVIDIA Triton to achieve sub-100ms inference. We own the full ML lifecycle from high-level research and feature engineering to deployment and A/B experimentation. Here, you will find the autonomy, the data depth, and the massive scale required to solve the most complex optimization challenges in the adtech ecosystem.
The data infrastructure behind this runs at real scale: 2TB ingested in real time every day, 100+ Airflow jobs and data pipelines, and ML models handling p99 latency of 100ms across 100,000+ predictions per second.
What you will do:
- Analyze and evaluate the performance of our machine learning models using user-level and aggregated data, identify inefficiencies and failure patterns, and turn findings into actionable recommendations for our Data Science teams.
- Define and improve metrics for measuring ML model performance and business impact, working closely with Data Scientists and Product Managers to ensure we optimize for the right outcomes.
- Design, prepare and analyze A/B tests and other experiments to measure the impact of new models, features and algorithmic changes. Assess statistical significance, experiment quality and practical business impact.
- Act as a strategic analytical partner to Product, Data Science, and Business leads. You proactively translate ambiguous business challenges into analytical roadmaps and turn complex ML insights into clear recommendations that shape product strategy.
- Challenge product and technical decisions with data, bringing an independent analytical perspective to model development, experimentation and product strategy.
- Drive analytical projects with end-to-end ownership: from initial scoping and hypothesis generation to stakeholder alignment and post-decision impact. Establish reusable frameworks and best practices that raise the bar for how we use data across teams.
- Mentor and guide other analysts on the team, fostering a culture of high analytical standards, strong business intuition, and effective communication.
Who you are:
- You have a degree in mathematics, statistics, physics, computer science, economics, analytics, or a similar quantitative field.
- You have 5+ years of relevant experience in Data Analytics, Product Analytics, Experimentation, or Data Science, with a proven track record of delivering measurable business impact and working closely with senior cross-functional stakeholders.. Experience in AdTech, mobile apps or ML-driven products is a strong plus.
- You’re proficient in SQL and comfortable working with large datasets.
- You have strong Python skills and are comfortable using them for data analysis and statistical modelling.
- You have a solid understanding of statistics and experimentation, including hypothesis testing, confidence intervals, statistical significance and A/B test analysis.
- You have an understanding of machine learning concepts and model evaluation and are comfortable working with Data Scientists. You don't necessarily need to build ML models yourself, but you should understand how to assess their performance and limitations.
- You have excellent data visualization skills and experience building dashboards using tools such as QuickSight, Power BI, Tableau, Streamlit or similar.
- You can articulate complex algorithmic and behavioral insights clearly to non-technical stakeholders, align differing viewpoints, and comfortably present recommendations to leadership.
- You thrive with ambiguity and have a high degree of ownership. You proactively identify high-value opportunities instead of waiting for tasks to be assigned, and you take pride in seeing initiatives through to real-world outcomes.
Fuel for the Journey: Benefits to Support Your Ambitions
- Invest in Your Future: Regular feedback and our development program support your growth, helping you expand your skill set and achieve your career goals.
- Easy Arrival to adjoe: From signing to settling in Hamburg, we’ve got you covered. Need a visa? No problem. Ready to build your new life and career at adjoe in Hamburg? We support every ambition—from learning German to a relocation bonus that helps you settle in and make Hamburg feel like home.
- Live Your Best Life, at Work and Beyond: We work in a hybrid setup with 3 core office days, plus flexible working hours. Enjoy 30 vacation days, 3 weeks of remote work per year, and free access to an in-house gym with lots of different fitness classes and mental health support through our Employee Assistance Program (EAP).
- Thrive Where You Work: Enjoy the Alster lake view from our central office with top notch equipment, fun open spaces, and a large variety of snacks and drinks.
- Join the Community! Participate in regular team and company events, including hackathons and social gatherings. We work together, and we celebrate together, too.
Skip writing cover letters. Tell us about your most passionate personal project, your desired salary and your earliest possible start date. We are looking forward to your application!
We welcome applications from people who will contribute to the diversity of our company.
We welcome applications from people who will contribute to the diversity of our company.
Location: Kuala Lumpur, Malaysia
About Us
Established in 2018, Bybit is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions. Powered by world-class technology and a user-first mindset, Bybit delivers a seamless ecosystem across trading, payments, wealth management, custody, institutional services, and Web3 — connecting users to the future of digital finance.
Our core values define how we build. We listen, care and improve to create products and experiences that put users first. Backed by a global team of ambitious builders, problem-solvers, and innovators, we foster a high-performance and fast-moving environment where talent is empowered to drive real impact at the global scale. Supported by 24/7 multilingual customer service and a strong commitment to innovation, we are shaping the future of finance through technology, collaboration, and bold execution.
Today, Bybit is recognized as one of the most trusted and transparent platforms in the digital asset industry, continuing to expand its global presence while building the infrastructure for the next generation of financial services.
Responsibilities
Design and implement solutions for user incentives, experience improvements, and business automation in support of retention goals. Independently drive requirements analysis, technical design, development, testing, production rollout, ongoing operation, and post-launch evaluation for your modules.
Develop and maintain user incentive and financial benefit modules. Strengthen rule execution, monetary calculations, disbursement, state transitions, idempotency, consistency, failure compensation, reconciliation, and auditing to ensure accuracy and traceability.
Contribute to the engineering and productionization of AI applications and AI-powered user experiences, continuously improving output quality, responsiveness, system stability, and operating costs.
Bring AI into real-world use cases by designing, developing, and iterating on AI Agents and agentic workflows. Integrate models, tools, and internal systems to support knowledge retrieval, troubleshooting, operational assistance, and business automation.
Establish evaluation, execution observability, and safety controls for AI workflows. Improve context and state management, failure recovery, budget controls, and human intervention mechanisms. Enforce data access permissions, sensitive information protection, and boundaries on fund-related operations. Ensure that critical monetary calculations and writes are governed by deterministic rules and authorized execution paths.
Help build team-wide AI-assisted engineering workflows. Develop reusable Skills, tools, context conventions, and validation mechanisms to enable effective AI use in requirements analysis, development, testing, code review, and troubleshooting, improving delivery efficiency while maintaining engineering quality.
Required Qualifications
A bachelor’s degree or above in Computer Science or a related field, with at least four years of backend development experience. Either Go or Java is acceptable.
Strong programming fundamentals, including knowledge of the concurrency model, memory management, and performance optimization of at least one mainstream backend language. Ability to independently troubleshoot complex issues.
Experience developing distributed systems and contributing to the design of core business modules or systems. Hands-on experience handling concurrency conflicts, idempotency, duplicate message consumption, cross-service consistency, timeouts, and failure recovery.
Proficiency with common backend technologies, including RPC frameworks, caches, message queues, and relational databases, with an understanding of their appropriate use cases and reliability limitations.
AI-assisted engineering capability — a core requirement:
Proficiency in using AI coding tools for requirements decomposition, system analysis, coding, testing, and code review. Ability to validate outputs and maintain engineering quality rather than relying solely on generated code.
AI application engineering capability — a core requirement:
Hands-on experience developing and deploying AI/LLM capabilities in real-world scenarios. Ability to clearly explain the problem definition, personal contribution, technical trade-offs, and outcome validation. Experience must extend beyond basic tool usage or demonstration-only projects.
Fund-related business experience — a mandatory requirement:
Hands-on development experience with systems involving funds or monetary value, such as commission rebates, settlement, reconciliation, payments, accounting ledgers, vouchers, promotional credits, or subsidies. Experience addressing monetary precision, duplicate disbursements, failure compensation, or financial reconciliation, with the ability to explain the stages you owned and the mechanisms used to ensure correctness.
Proactivity, business understanding, and cross-functional collaboration skills. Ability to translate business goals into technical problems and acceptance criteria. Commitment to testing, code review, observability, permission boundaries, and data security, with ownership of delivery and production outcomes.
Preferred Qualifications
AI Agent / agentic workflow development experience — a key priority:
Hands-on experience designing, developing, and continuously iterating on Agent workflows involving tool calling, workflow orchestration, context and memory management, state persistence, failure recovery, or human intervention. Projects may include business products, internal tools, or actively used and maintained personal projects.
Experience evaluating Agent performance and improving reliability. Ability to identify issues through evaluation datasets, failure cases, execution traces, or business metrics, and validate the impact of improvements.
Experience building team-wide AI-assisted engineering workflows, such as custom Skills, Rules, context conventions, automated testing, or AI code review pipelines that have been adopted by the team.
Experience independently owning complex business modules or driving cross-system projects, including proposing solutions, coordinating dependencies, and delivering outcomes.
Familiarity with complex rule systems, microservices, and asynchronous task orchestration. Ability to determine when to use traditional workflows versus Agents based on cost, determinism, and error risk.
Additional Advantages
Experience developing retention, user incentive, lifecycle engagement, or growth platforms, including collaboration with Product and Operations to evaluate outcomes using business data and experiments.
Practical experience with RAG, vector retrieval, knowledge bases, MCP, AI translation, search, or Agent orchestration frameworks, with the ability to explain technology choices and their limitations.
Engineering experience at a cryptocurrency exchange or fintech company, or actively maintained and used personal projects and open-source contributions.
Why Join Us
At Bybit, we are committed to fostering a supportive and enriching work environment.
Our benefits include:
- Study Growth Fund: We support your professional development and continuous learning.
- Internal Events: Participate in regular team-building activities, workshops, and events designed to promote collaboration and innovation.
- Global Collaboration: Be part of a diverse, international team, working alongside colleagues from around the world.
- Career Advancement: Access opportunities for growth and advancement within a rapidly expanding global company.
- Internal Mobility: Grow with us- Your long-term development is important to us. We offer internal job opportunities to help build your career path.
Al Jubail, Saudi Arabia
Doha, Qatar
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УдалённоUnited States; Canada; Australia; New Zealand; United Kingdom
УдалённоseniorIndia; Japan; South Korea; Taiwan; Hong Kong; Pakistan
ОфисseniorUS, Boston, MA
УдалённоEurope
УдалённоRemote, United States; The base salary range for this role’s listed level is currently for residents of the United States only
New York City, NY; San Francisco, CA; Seattle, WA
УдалённоPoland; Portugal; Ukraine
ГибридUnited States; San Francisco; Canada; New York; Ottawa; Toronto; Montreal; We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities
УдалённоLatin America
ГибридСША; 💹 401(k) Program with a 4% match (US Only); 🚗 Commuter Benefits (In-Office & US Only); We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds
San Francisco, CA • New York, NY • United States
seniorWe support every ambition—from learning German to a relocation bonus that helps you settle in and make Hamburg feel like home
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