Why Cast AI?

Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, Cast AI continuously optimizes performance, reliability, and efficiency in production.

The old way doesn't work. As Kubernetes and AI environments grow, manual decisions don’t. Cast AI replaces tickets, alerts, and manual tuning with continuous automation that adapts infrastructure as conditions change. Efficiency and cost savings follow naturally from that automation.

Over 2,100 companies already rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS.

Global team, diverse perspectives
We're headquartered in Miami, but our impact is international. We take a global and intentional approach to diversity. Today, Cast AI operates across 34 countries spanning Europe, North America, Latin America, and APAC, bringing a wide range of perspectives into how we build and lead. 

Unicorn momentum
In January 2026, we achieved unicorn status with a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group (a $50+ billion Korean conglomerate). Our valuation now exceeds $1 billion, and we're just getting started.

Join us as we build the future of autonomous infrastructure.

Kimchi is an open-source AI inference platform built for teams running serious agentic coding workloads. We're building the harness, the routing, and the infrastructure layer that makes running your own AI coding stack possible - and affordable. We're early, moving fast, and the developer community is central to how we grow.

What you'll do

• Build things publicly with Kimchi - tutorials, demos, integrations - that show developers how to solve real problems. Think live build logs, OSS integrations, or benchmarks you'd want to read yourself.
• Be the voice of the the developer community: Discord, GitHub discussions, Reddit, HN - be present where developers are already talking about the problems we solve
• Be the structured feedback loop between dev community and product - synthesize what you're hearing into actionable signals for the product team. 
• Write technical content that ranks and spreads: setup guides, benchmark breakdowns, comparison posts, integration walkthroughs
• Speak at conferences, meetups and run workshops - representing Kimchi as a technical peer
• Identify where new users get stuck and advocate hard for fixes
• Help shape Kimchi's voice in the developer community - what we stand for, what we say when there is trending news in the market 

What we're looking for

• You've built real software and can talk about it credibly - ideally you've used agentic coding tools and have opinions about them
• You're a strong technical writer - you can explain complex things clearly and make them resonate with the developer audience
• You're comfortable being the public face of a technical product: blog posts, talks, live demos, community threads
• Huge plus: You'd have tested and found problems Kimchi solves interesting -  before this job posting even existed
• Bonus: you've worked in or around Kubernetes, LLM inference, or developer tooling

What’s in it for you?

• Enjoy a flexible, remote-first global environment.
• Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology.
• Equity options.
• Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks.
• Spend 10% of your work time on personal projects or self-improvement. 
• Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills.
• Team-building budget and company events to connect with your colleagues.
• Equipment budget to ensure you have everything you need.
• Extra days off to help maintain a healthy work-life balance.

Hiring process

• Screening call with Recruiter
• Hiring Manager interview
• 1-2 additional interviews based on the role
• Culture Check interview with an executive

*As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr.
*Please note that Cast AI does not provide any form of visa sponsorship/work permit.
#LI-Remote

We are looking for a Cloud Support Engineer who thrives on helping customers get the most out of Pulumi — supporting teams as they adopt, scale, and evolve their infrastructure-as-code practice using real programming languages, automation, and developer-first workflows.

We are seeking a technical and empathetic Cloud Support Engineer to join our growing customer operations team at Pulumi. As a founding member of our support team, you will play a crucial role in defining the function while providing technical assistance and support to our ever-growing customer base. You will ensure the smooth operation and optimal utilization of our infrastructure-as-code platform. This is an excellent opportunity to work with cutting-edge technologies and be part of a fast-growing company at the forefront of our industry.

At Pulumi, you’ll be challenged, continue learning, share knowledge with others, and collaborate with a talented and supportive team.

While Pulumi is headquartered in Seattle, WA., we are dedicated to being a remote first company and this role can be located anywhere in the United Kingdom or Spain.

In This Role You Will:

• Provide technical support and assistance to customers via various communication channels (e.g., email, chat, community) regarding IaC best practices and DevOps concepts.
• Troubleshoot and resolve customer issues related to infrastructure deployments, configuration management, automation, and other infrastructure-as-code topics.
• Collaborate with cross-functional teams, including engineering, product, and sales to identify and resolve complex technical and business issues.
• Actively contribute to the creation and maintenance of technical documentation, including FAQs, knowledge base articles, and troubleshooting guides.
• Stay updated with the latest trends and best practices in IaC, DevOps, cloud services (AWS, Azure, GCP, K8s) and related technologies.
• Participate in on-call rotations to provide after-hours support when necessary.

We’re Looking For Someone With:

• Minimum of 5 years of experience in a related field, with a strong focus on Infrastructure as Code, DevOps, and code or scripting.
• Proficiency in infrastructure-as-code concepts and tools, such as Pulumi, Terraform, Cloudformation and CDK.
• In-depth knowledge of cloud service providers, including AWS, Azure, GCP, and Kubernetes.
• Comfortable authoring readable maintainable code in one or more of the following; Python, TypeScript, GO, or Java.
• Experience using AI-powered support tools and assistants (e.g., LLM-driven troubleshooting tools, AI agents, or copilots) to accelerate customer issue resolution, improve diagnostic accuracy, and enhance knowledge base contributions.
• Strong troubleshooting and problem-solving skills, with the ability to analyze and resolve complex technical issues.
• Certification(s) in relevant technologies, such as AWS Certified DevOps Engineer, Azure DevOps Engineer Expert, or Certified Kubernetes Administrator (CKA).
• Excellent communication skills, both written and verbal, with the ability to effectively convey technical concepts to both technical and non-technical audiences.
• Self-motivated and able to work independently as well as collaboratively in a team environment.
• Strong attention to detail and a commitment to delivering high-quality customer support.

Compensation:

• Base Salary Hiring Range (Spain): £60,000 to £111,000
• Base Salary Hiring Range (UK): €52,000 to €97,000
• All full-time employee offers at Pulumi include base salary, bonus or variable, equity and benefits (details below). 

Overview:

We are building the next generation of our SaaS platform, and we need someone to own the quality architecture that makes it all trustworthy. As a Principal Technology Architect - QA, you will design the systems, standards, and governance that raise the bar for quality across every product segment we ship.

We are an AI-first organization. You will put that into practice by bringing AI-driven testing, intelligent automation, and modern quality tooling into the way our teams work every day. This is a hands-on architecture role, not a policy desk. You will build test frameworks, design quality gates, set reliability targets, and create the shared infrastructure that teams actually adopt because it makes their lives easier.  You will work closely with engineering leadership to connect quality strategy to business outcomes. When you recommend a change, people across the org will listen, because your technical credibility and track record back it up.  You will also mentor engineers, shape how we hire for quality mindset, and help grow the next generation of technical leaders on our teams.  If you get excited about solving hard problems at scale, rethinking how quality works in a modern SaaS org, and leaving things better than you found them, we would love to talk.

What you will do:

• Set the quality architecture direction for the org: design quality gates, define reliability targets, and choose the testing infrastructure that all product segments build on.
• Build and maintain a governance model for quality practices so that standards, processes, and tooling are adopted consistently across engineering teams.
• Design and deliver scalable test automation frameworks that teams can adopt and extend to improve coverage, speed, and confidence in every release.
• Bring AI into quality engineering: evaluate and roll out AI-driven test generation, intelligent test selection, defect prediction, and automated monitoring.
• Own the performance and resilience strategy: set performance budgets, define monitoring standards, and create disaster recovery and incident response frameworks.
• Partner with product and engineering leaders to balance release velocity with system health, making sure teams can ship fast without cutting corners on quality.
• Evaluate and introduce new tools, patterns, and practices that keep our quality approach current as the platform and industry evolve.
• Mentor engineers across teams, raise the bar on how we hire for quality mindset, and contribute to engineering maturity across the organization.
• Represent Precisely externally as a thought leader in quality engineering through talks, writing, or industry engagement.

What we are looking for:

Required:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Equivalent work experience is accepted in place of a degree. An advanced degree is a plus.
• Experience: 15+ years of progressive experience in software quality engineering, test architecture, or related technical leadership roles, with demonstrated org-wide architecture leadership
• Quality architecture: Deep expertise in test automation frameworks, CI/CD pipeline design, quality gate implementation, and testing strategies for large-scale SaaS platforms.
• AI: Hands-on experience applying AI to quality workflows (e.g. AI-driven test generation, intelligent test selection, or automated defect detection)
• Leadership: Track record of driving adoption of technical standards across multiple teams or product areas, including working with leaders who do not report to you
• Travel is required: Yes – Approximately 10%

AI Skills/Knowledge:

• Comfortable using generative AI tools (e.g. GitHub Copilot, Claude Code, or custom LLM integrations) to accelerate day-to-day quality workflows such as test generation, defect triage, and root-cause analysis.
• Able to critically evaluate AI-generated outputs and set guardrails so that AI-produced test artifacts meet reliability, security, and compliance standards.
• Experience evaluating and integrating AI-powered quality tools (e.g. autonomous testing platforms, AI-based test maintenance, predictive analytics for defect detection) into org-wide workflows.
• Open to continuously adopting new AI capabilities as they emerge and excited to shape how the org integrates them into quality practices.

Preferred Skills:

• Experience defining and scaling quality practices across multiple product segments in a large SaaS or cloud-native organization.
• Familiarity with contract testing, chaos engineering, or advanced reliability practices (SLOs/SLIs, error budgets).
• Bonus points for experience establishing quality centers of excellence or community-of-practice models across engineering organizations.
• Exposure to security testing practices, compliance frameworks, or regulated industry quality standards.
• Experience with observability and monitoring platforms (Datadog, Splunk, Grafana, PagerDuty) at an architectural level.
• Track record of representing an organization externally through conference talks, published writing, or industry working groups in quality engineering.

#LI-SR1

See yourself at Twilio

Join the team as Twilio’s next Security Engineer, Security Automation on Twilio’s Information Security Team.

About the job

This position is needed to assist Twilio’s Information Security Team operate more efficiently by improving and automating our critical security workflows.

As a Software Engineer, Security Automation on this team, you will participate in all phases of the software development life cycle which includes requirements gathering with security teams, technical design, estimations, sprint planning, coding, testing, deployments and on-call support. You will own, operate and maintain automated workflows that support various security programs including but not limited to cloud security, product security, Governance, Risk & Compliance (GRC)  and enterprise security, employing Agile methodologies to continuously deliver value to our partners.

Responsibilities

In this role, you’ll:

• Develop and implement automated and AI-powered security solutions to protect Twilio's Cloud and Enterprise infrastructure, leveraging data orchestration frameworks and LLM-based approaches.
• Build workflows that integrate structured and unstructured data sources into orchestrated pipelines, enabling intelligent decision-making and risk reduction at scale.
• Design and prototype LLM-driven applications to automate security analysis, incident response, and governance tasks, while ensuring explainability and accuracy.
• Collaborate with cross-functional teams to identify security needs and deliver advanced AI-enabled solutions that address those needs effectively.
• Contribute significantly to defining our security automation and AI roadmap, balancing near-term and long-term business impact with technical feasibility and scalability.
• Own and maintain the operational health of automation and AI-driven systems, ensuring they continue to meet reliability and performance requirements (SLOs and KPIs).
• Support on-call operations for tools, pipelines, and AI models owned by the team.
• Document and share knowledge through clear technical documentation of processes, procedures, AI models, and orchestration systems.
• Stay up-to-date on emerging trends in security automation, data orchestration, and AI/LLMs—and apply them to Twilio’s security operations for continuous innovation.

Qualifications 

Not all applicants will have skills that match a job description exactly. Twilio values diverse experiences in other industries, and we encourage everyone who meets the required qualifications to apply. While having “desired” qualifications make for a strong candidate, we encourage applicants with alternative experiences to also apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

Required:

• Minimum of five (5) years of experience as a software engineer developing internal tools and automating workflows at scale
• Proficiency in Python (or another scripting language) for development, testing, and automation of security and infrastructure workflows
• Hands-on experience applying AI/ML models, including LLMs, to automate complex business or security processes and build intelligent solutions
• Solid understanding of software security principles, secure coding practices, and security automation
• Experience with data orchestration frameworks (e.g., Airflow, Dagster, Prefect) to manage and scale automation pipelines
• Familiarity with infrastructure-as-code (Terraform), CI/CD systems (BuildKite or similar), and container orchestration platforms (Kubernetes, Docker)
• Strong problem-solving, communication, and collaboration skills, with the ability to iterate quickly on feedback and work across security and engineering teams

Desired:

• Experience with Security Orchestration, Automation, and Response (SOAR) technologies and practices, with a focus on scaling automated incident response
• Proven ability to design and implement security automation frameworks that enable rapid delivery of reliable, reusable, and scalable automated solutions
• Strong interest in or hands-on experience with building and applying AI/ML models (including LLMs) to automate complex workflows in cybersecurity, compliance, or infrastructure operations
• Ability to bridge AI/automation capabilities with security strategy, driving adoption of next-generation solutions across cloud and enterprise environments
• Passion for continuous innovation in leveraging orchestration, automation, and AI to solve real-world security challenges

Location

This role will be remote, and based in Ireland.

Travel

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

What We Offer

There are many benefits to working at Twilio, including, in addition to competitive pay, things like generous time-off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

See yourself at Twilio

Join the team as Twilio’s next Security Engineer, Security Automation on Twilio’s Information Security Team.

About the job

This position is needed to assist Twilio’s Information Security Team operate more efficiently by improving and automating our critical security workflows.

As a Software Engineer, Security Automation on this team, you will participate in all phases of the software development life cycle which includes requirements gathering with security teams, technical design, estimations, sprint planning, coding, testing, deployments and on-call support. You will own, operate and maintain automated workflows that support various security programs including but not limited to cloud security, product security, Governance, Risk & Compliance (GRC)  and enterprise security, employing Agile methodologies to continuously deliver value to our partners.

Responsibilities

In this role, you’ll:

• Develop and implement automated and AI-powered security solutions to protect Twilio's Cloud and Enterprise infrastructure, leveraging data orchestration frameworks and LLM-based approaches.
• Build workflows that integrate structured and unstructured data sources into orchestrated pipelines, enabling intelligent decision-making and risk reduction at scale.
• Design and prototype LLM-driven applications to automate security analysis, incident response, and governance tasks, while ensuring explainability and accuracy.
• Collaborate with cross-functional teams to identify security needs and deliver advanced AI-enabled solutions that address those needs effectively.
• Contribute significantly to defining our security automation and AI roadmap, balancing near-term and long-term business impact with technical feasibility and scalability.
• Own and maintain the operational health of automation and AI-driven systems, ensuring they continue to meet reliability and performance requirements (SLOs and KPIs).
• Support on-call operations for tools, pipelines, and AI models owned by the team.
• Document and share knowledge through clear technical documentation of processes, procedures, AI models, and orchestration systems.
• Stay up-to-date on emerging trends in security automation, data orchestration, and AI/LLMs—and apply them to Twilio’s security operations for continuous innovation.

Qualifications 

Not all applicants will have skills that match a job description exactly. Twilio values diverse experiences in other industries, and we encourage everyone who meets the required qualifications to apply. While having “desired” qualifications make for a strong candidate, we encourage applicants with alternative experiences to also apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

Required:

• Minimum of five (5) years of experience as a software engineer developing internal tools and automating workflows at scale
• Proficiency in Python (or another scripting language) for development, testing, and automation of security and infrastructure workflows
• Hands-on experience applying AI/ML models, including LLMs, to automate complex business or security processes and build intelligent solutions
• Solid understanding of software security principles, secure coding practices, and security automation
• Experience with data orchestration frameworks (e.g., Airflow, Dagster, Prefect) to manage and scale automation pipelines
• Familiarity with infrastructure-as-code (Terraform), CI/CD systems (BuildKite or similar), and container orchestration platforms (Kubernetes, Docker)
• Strong problem-solving, communication, and collaboration skills, with the ability to iterate quickly on feedback and work across security and engineering teams

Desired:

• Experience with Security Orchestration, Automation, and Response (SOAR) technologies and practices, with a focus on scaling automated incident response
• Proven ability to design and implement security automation frameworks that enable rapid delivery of reliable, reusable, and scalable automated solutions
• Strong interest in or hands-on experience with building and applying AI/ML models (including LLMs) to automate complex workflows in cybersecurity, compliance, or infrastructure operations
• Ability to bridge AI/automation capabilities with security strategy, driving adoption of next-generation solutions across cloud and enterprise environments
• Passion for continuous innovation in leveraging orchestration, automation, and AI to solve real-world security challenges

Location

This role will be remote, and based in the UK.

Travel

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

What We Offer

There are many benefits to working at Twilio, including, in addition to competitive pay, things like generous time-off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

Why Cast AI?

Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, Cast AI continuously optimizes performance, reliability, and efficiency in production.
The old way doesn't work. As Kubernetes and AI environments grow, manual decisions don’t. Cast AI replaces tickets, alerts, and manual tuning with continuous automation that adapts infrastructure as conditions change. Efficiency and cost savings follow naturally from that automation.
Over 2,100 companies already rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS.

Global team, diverse perspectives

We're headquartered in Miami, but our impact is international. We take a global and intentional approach to diversity. Today, Cast AI operates across 34 countries spanning Europe, North America, Latin America, and APAC, bringing a wide range of perspectives into how we build and lead.

Unicorn momentum

In January 2026, we achieved unicorn status with a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group (a $50+ billion Korean conglomerate). Our valuation now exceeds $1 billion, and we're just getting started.

Join us as we build the future of autonomous infrastructure.

About the role

Throughput. Latency. KV cache utilization.

Move those three numbers in the right direction, and two things happen: customers get faster, cheaper inference, and our margins improve. That's the entire thesis of this role. Every kernel you tune, every quantization scheme you ship, every scheduler tweak you land shows up directly in a customer's p99 and on our P&L.
This is a high-impact seat. It is also a high-autonomy seat as you'll be given the room to lead the technical direction of inference optimization at Kimchi, not execute someone else's roadmap.

The problem: running LLMs in production is a moving target. The "right" model and serving configuration for a workload depend on traffic shape, sequence-length distribution, batch dynamics, GPU SKU, memory bandwidth, quantization tolerance, and a dozen other variables that shift week to week. Most teams pick a model once, over-provision GPUs, and absorb the cost. Kimchi is the system that makes that decision automatically - continuously matching workloads to the most cost-efficient, best-performing LLM and serving configuration on a customer's infrastructure. We're building the optimization layer between the model and the hardware, and we need engineers who understand both sides deeply.

Stack

Python · vLLM · SGLang · TensorRT-LLM · PyTorch · CUDA-adjacent tooling · Kubernetes · gRPC · ClickHouse · PostgreSQL · GCP Pub/Sub · AWS / GCP / Azure · GitLab CI · ArgoCD · Prometheus · Grafana · Loki · Tempo.

Requirements:

• 5+ years building real ML systems, with a portfolio that shows depth in inference or training infrastructure (not just model training notebooks).
• Strong Python - production services, not scripts.
• Hands-on experience with at least one of vLLM, SGLang, or TensorRT-LLM, and a working mental model of why an inference engine performs the way it does on a given GPU.
• Fluency with quantization tradeoffs - you've measured quality regressions, not just compression ratios.
• Comfort with distributed systems: collective communication, sharding strategies, and the practical failure modes of multi-GPU and multi-node setups.
• A bias toward measurement. You instrument before you optimize, and you can tell the difference between a real win and a benchmark artifact.
• Self-direction. This role comes with a wide mandate; you should be excited by that, not unsettled by it.

Responsibilities:

• Push throughput. Continuous batching, speculative decoding, chunked prefill, kernel-level tuning across vLLM, SGLang, and TensorRT-LLM. Find the ceiling on each GPU SKU, then raise it.
• Cut latency. Attack TTFT and TPOT separately. Profile, identify the actual bottleneck (compute, memory bandwidth, scheduling, networking), and fix it - not the bottleneck you assumed.
• Get more out of the KV cache. Paged attention, prefix caching, eviction policies, cache reuse across requests, quantized KV. This is where a lot of the unrealized throughput lives, and it's an area you'll own.
• Quantize without regressing quality. INT8, INT4, FP8 across weights, activations, and KV. Empirical work: measure quality on real workloads, not just perplexity benchmarks.
• Shrink cold starts and memory footprint. Faster init, smarter weight loading, tighter memory accounting - the difference between a model that scales and one that doesn't.
• Scale across nodes. Distributed inference topologies, network-aware placement, checkpointing strategies that don't bottleneck on storage or interconnect.
• Set the technical direction. Decide what we benchmark, what we adopt, and what we build ourselves. Bring the team along with strong writeups and reproducible experiments.

What’s in it for you?

• Competitive salary (depending on the level of experience).
• Enjoy a flexible, remote-first global environment.
• Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology
• Equity options.
• Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks.
• Spend 10% of your work time on personal projects or self-improvement. 
• Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills.
• Annual hackathon to spark new ideas and strengthen team bonds.
• Team-building budget and company events to connect with your colleagues.
• Equipment budget to ensure you have everything you need.
• Extra days off to help maintain a healthy work-life balance.

Hiring process

• Screening call with Recruiter
• Hiring Manager interview
• Technical interview (system design)
• Live coding
• Culture Check interview with an executive

*As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr.
*Please note that Cast AI does not provide any form of visa sponsorship/work permit.

#LI-Remote

About the Role

We’re looking for a Staff Software Engineer to build AI-powered tools and integrations that plug directly into game engines, editors, clients, and backend services. You’ll deliver high-quality C++ integrations across proprietary studio engines, ship robust build/QA automation, and partner with multiple PlayStation Studios teams to make AI an everyday part of development.

What You’ll Be Doing

• Build and maintain engine/editor plugins, runtime SDKs, and services that integrate AI (LLMs and related systems) into game clients, servers, and build tools.
• Ship performant, memory-aware C++ by profiling, optimizing, and debugging across PC/console builds with tight frame budgets.
• Design stable API surfaces for game teams (C++/C API, gRPC/HTTP) with versioning, telemetry, and backward compatibility.
• Stand up CI/CD for game builds and tools (UBT or proprietary build systems; artifact packaging; nightly/regression suites; distributed/accelerated builds).
• Automate QA for tooling and in-engine features using engine test frameworks and headless runs, and wire results into CI and dashboards.
• Implement production LLM integrations (prompting, RAG/tool calls, guardrails/safety, observability, timeouts/retries, and cost controls).
• Collaborate with studio engineering, tech art, design, and QA to land integrations across varied codebases and pipelines.
• Document patterns, provide sample projects, and deliver internal training so solutions scale across PlayStation Studios.
• Influence standards and tech choices for AI in our dev stack, and contribute to shared libraries and best practices.

Qualifications

• You have at least five years of experience building production software in modern C++ (C++17/20) with strong fundamentals in memory management, concurrency, performance, and debugging.
• You have shipped tools or runtime features in AAA engines, including work on plugins/modules, asset and build pipelines, and editor/runtime integration.
• You have delivered features or tooling that integrate with LLMs or other ML services, and you understand prompt design, evaluation, safety, and telemetry for production usage.
• You have implemented engine-level automated testing (functional and integration), including headless execution and CI gating.
• You work fluently with large code/asset repositories and are comfortable with both Perforce and Git.
• You communicate clearly across disciplines and translate diverse studio requirements into pragmatic, maintainable solutions.
• You write thorough documentation and favor well-tested, maintainable code.

Nice to Have

• You have built networking/service integrations for game backends (gRPC/HTTP) and implemented telemetry/observability (logs, metrics, traces).
• You have packaged SDKs/plugins for multiple studios and managed semantic versioning and migration tooling.
• You understand console platform requirements and certification workflows.
• You are familiar with security, privacy, and responsible-AI practices in production systems.

Please note; this position can be completed remotely from The UK

POS-31662

Role Summary

HubSpot is building the next generation of AI experiences across our go-to-market products. We’re hiring a Senior Machine Learning Engineer II to join the Flywheel Context (Contacts) team, where you’ll build the context platform layer that powers accurate, high-performing AI assistants and agents.

This is a backend-leaning ML engineering role focused on shipping production software—designing systems that help other engineering teams retrieve relevant facts, manage long/complex context, and evaluate quality at scale. If you love building durable platforms (not just prototypes), this role is for you.

What You’ll Do

• Design, build, and operate backend services that power context retrieval and enrichment for AI assistants and agents.

• Build platform capabilities for storing, searching, and retrieving “insights” and relevant facts across HubSpot’s GTM data.

• Develop systems to manage and compress context when it gets large (e.g., long contact histories, high-volume CRM data).

• Create tooling that allows other engineering teams to ship assistants/agents faster, with consistent APIs and reusable primitives.

• Build and maintain evaluation and measurement approaches (offline evals, golden datasets, automated metrics, human review loops) to ensure context quality and answer accuracy.

• Collaborate closely with sister platform teams and downstream product engineering teams (your “customers”) to integrate platform capabilities into real experiences.

• Own end-to-end delivery: architecture, implementation, observability, performance, reliability, and iteration.

Required Qualifications

• Strong track record shipping production backend systems as a senior engineer (ownership from design to delivery).

• Professional Java experience building maintainable, testable services in production (this is core to the role).

• Experience implementing ML workflows in production (e.g., retrieval/ranking pipelines, feature/data pipelines, model/embedding services, evaluation frameworks).

• Comfort working with data tooling and data-intensive systems (large datasets, pipelines, and service integrations).

• Experience operating software at meaningful scale (e.g., high throughput, significant data volume, performance and reliability constraints).

• Strong engineering fundamentals: system design, code quality, debugging, observability, and operational excellence.

Nice-to-Have Qualifications

• Experience with search/retrieval/relevance/ranking systems (highly aligned to context work).

• Experience with RAG-style systems, embeddings, vector search, or hybrid retrieval strategies.

• Familiarity with LLM evaluation patterns (golden sets, automated metrics, human review), hallucination mitigation, and quality measurement.

• Experience with distributed systems, event-driven architectures, or stream processing.

• Cloud/platform experience (e.g., Kubernetes, AWS/GCP) and running services in production.

• Some Python experience (useful, but not the primary language).

The Problems You'll Solve

At Carta, our employees set out on a mission to unlock the power of equity ownership for more people in more places. We believe that the problems we solve today unlock the opportunities of tomorrow. 

As a Senior Machine Learning Engineer II at Carta, you'll spend your time building agentic systems to power new products, automate complex document workflows, and accelerate Carta's business. You will also work closely with the SRE team to develop Carta's infrastructure around LLM integration and agentic processes. Example responsibilities will include:

• Develop agentic systems to classify, extract and review data from complex financial and legal documents.
• Develop agentic systems for document acquisition and management.
• Partner with product managers, engineers, designers, and business teams to incorporate agentic and LLM-powered products and user-flows.
• Own, coordinate, and solve complex, cross-functional problems that extend beyond the traditional boundaries of machine learning.

The Team You'll Work With

At Carta, our Machine Learning team is on a mission to power data products and automation through cutting-edge techniques. We work closely with Carta's core business units and product teams to develop LLM-powered and agentic systems for document intelligence, fund administration, legal tech, customer onboarding and more. This role is foundational to our team, where you'll work with one of the world's most valuable datasets and document repositories. Our systems directly enable revenue growth and operational efficiency for the company.

Our team consists of specialized Machine Learning scientists and engineers, collaborating with product analytics and data engineering experts. We foster a culture of partnership, working closely with teams across Carta to solve impactful problems. We strongly believe that being helpful accelerates results, and we support one another to achieve success at Carta.

The Impact You'll Have

You will own significant projects that directly align with the company's strategic initiatives in agentic systems, AI adoption and document intelligence. Your contributions will empower leaders across the organization to deliver innovative products, optimize operational efficiency, and make well-informed product decisions. Additionally, you will have the opportunity to develop foundational infrastructure for our team and establish best practices for integrating our agentic and LLM-powered systems into production environments. Your work will not only impact Carta's current machine learning capabilities but also pave the way for future engineers, enabling them to build upon your efforts seamlessly.

About You

Candidates must have a strong foundation in machine learning and software development, be proficient in Python, and have an analytical mindset. You have a strong bias towards simplicity, are excited by “zero to one” projects, and can efficiently communicate findings to leadership. Example traits that we value:

• 8+ years of industry experience solving complex data problems with descriptive and predictive statistical models
• Proficiency with AI-assisted software development, multi-agent development, skills & AI integration into development processes
• Experience with large language models (LLMs) and their applications in document intelligence
• Experience using LLMs and agentic frameworks such as Agno, Anthropic’s Agent SDK, Strands Agents SDK, A2A, LangChain or similar
• Experience with LLM observability and evals platforms such as Braintrust, Weights&Biases, LangFuse or similar
• Strong written and verbal communication skills
• A collaborative attitude and a helpful personality
• Experience building durable workflows in e.g. Temporal

Hudson River Trading (HRT) is hiring an AI Researcher to join the HAIL team. HAIL (HRT AI Labs) is the team at HRT responsible for developing and maintaining our most powerful models, which are used by our trading teams to drive a significant fraction of our trading. We are building and deploying "foundation models for markets", that ingest and train on vast amounts of market data, to make predictions about future market state. We are seeking experienced AI researchers to join our team to accelerate our efforts.

Researchers have great independence to pursue the research directions they think would be most impactful as part of a small focused team with minimal bureaucracy. They are enabled by state-of-the-art research clusters with very high GPU-to-researcher ratios, and supported by excellent engineering, hardware, and systems teams to realize their vision. Your work will be directly, clearly, highly impactful on the business, and it will be challenging: this is a field with no easy or obvious solutions. You'll be responsible for improving every part of our models: from featurization of data, to architecture design, to training dynamics, to how trading decisions are made.

Qualifications

• Must have two or more years work experience in deep learning research, for any domain: robotics, biology, chemistry, physics, audio, video, etc.
• Experience translating methods between areas of application is highly valued.
• LLM experience is valuable, but not necessary.
• Strong engineering skills valued, especially any of: GPU kernel development, lower-level Pytorch/JAX development, intermediate C++, FPGA/ASIC experience, HPC experience.

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. 

This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package which includes medical, dental, vision, basic life insurance, and enrollment in our company’s retirement savings plans. Employees will receive sick and parental leave, as well as other paid time off (including 20 vacation days and 10 paid holidays in the US). Please note that benefits and time off policies will vary across non-US locations.

Principle Product Marketing Specialist | Bokun 

About Tripadvisor 

The Tripadvisor Group connects people to experiences worth sharing, and aims to be the world’s most trusted source for travel and experiences. We leverage our brands, technology, and capabilities to connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories. The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP), include a portfolio of travel brands and businesses.

About Bókun

Bókun, a fast-growing subsidiary of TripAdvisor Inc., is a leading reservation system and channel management platform for tours and activities operators globally. We empower our clients to streamline their back-end operations and connect to a vast ecosystem of online travel websites, enabling them to grow their businesses. As a key player in travel technology, Bókun combines the agility of a startup with the stability of a publicly traded organisation.

Bókun is seeking a Principle Product Marketing Specialist to own our AI-powered content strategy and bottom-of-funnel content programme. Reporting directly to the Senior Product Marketing Manager, this role sits at the intersection of product marketing, content, and emerging AI search — responsible for positioning Bókun as a citable source in commercial AI prompts — building the library of high-intent onsite content (product-led blogs, FAQs, templates, integration content) that gets Bókun surfaced, recommended, and chosen at the moment buyers make decisions

This is not a traditional Product Marketing role. You will be the person who understands how LLMs surface information, how AI search tools like ChatGPT, Perplexity, Gemini, and Google AI Overviews decide what to recommend — and who builds a content engine designed to win in that world.

What You'll Do:

AI & LLM Content Strategy

• Content creation explicitly designed to be surfaced and cited by AI tools at the decision stage of the buyer journey

• Build and maintain a structured library of authoritative content (feature explainers, comparison guides, how-tos, FAQs) engineered to rank in and be recommended by LLMs

• Position Bókun as a citable source in commercial AI prompts by creating and owning high-intent onsite content — product-led blogs, FAQs, templates, and integration content designed to be surfaced when buyers are actively evaluating solutions

• Monitor how Bókun is represented across AI search tools and identify gaps, inaccuracies, and opportunities to improve our presence

• Stay ahead of how AI search behaviour is evolving and continuously adapt our content approach

Bottom-of-Funnel Content

• Create and own a programme of bottom-of-funnel content designed to convert buyers at the moment of decision — how-to guides, feature walkthroughs, use case explainers, and platform comparison content

• Build content that directly answers the specific questions buyers ask when evaluating Bókun against competitors — structured for both human readers and AI citation

• Develop and maintain a content calendar focused on high-intent, decision-stage topics across the customer lifecycle

Video & Explainer Content

• Script, brief, and project-manage short-form explainer and how-to videos that educate new and existing customers on Bókun features

• Collaborate with design and production to deliver video content that works across the website, social, email, and in-product

GTM & Product Marketing 

• Support Go-to-Market strategy and execution for new features and launches, contributing AI-first content assets to each GTM

• Conduct post-launch content analysis to identify gaps and optimise for both human and AI search performance

• Maintain a pulse on the competitive landscape and ensure Bókun's content positioning reflects market realities

Cross-functional Collaboration

• Work closely with product, engineering, sales, and the broader marketing team to ensure content is accurate, timely, and aligned with product direction

• Bring an AI search and LLM perspective into cross-functional planning conversations

Job Location: Hybrid

This role is a hybrid position that requires 2 days per week in our London, UK office.

Requirements:

• 3-5 years of experience in product marketing, content marketing, or a related discipline, preferably in SaaS, B2B, or travel technology

• Genuinely curious about how AI search and LLMs work — you've thought about how tools like ChatGPT, Perplexity, and Gemini decide what to surface, and you want to build content that wins in that environment

• Experienced in creating bottom-of-funnel content — how-tos, feature guides, comparison pages, decision-stage explainers — that drives real conversion

• Comfortable scripting and briefing video content; bonus if you've managed short-form explainer video production end-to-end

• Strong writer with the ability to produce clear, structured, benefit-led copy across formats — from long-form guides to concise feature explainers

• Analytical and data-driven — you use performance data to understand what's working and iterate quickly

• Familiar with AI content tools and comfortable using them to scale output without sacrificing quality (e.g. Perplexity, Notebook LM, ChatGPT, Jasper or equivalent)

• Self-directed and comfortable managing multiple projects in a fast-moving environment

• Highly collaborative — you know that great content requires close partnership with product, engineering, and sales

Nice To Have:

• Experience with SEO and structured content for search (schema, FAQs, entity-based SEO)

• Familiarity with how AI Overviews, featured snippets, and LLM training data intersect with content strategy

• Experience in travel tech or marketplace platforms

• Hands-on experience with tools like Mixpanel, GA4, or similar for content performance tracking

What We Offer 

• Competitive compensation packages (routinely benchmarked against the latest industry data), including base salary and annual bonuses
• “Work your way” with flexibility to suit your lifestyle. Tripadvisor Group takes a remote-friendly approach to collaboration across a worldwide team, with the option to join on-site as often as you’d like or as required by your team.
• Flexible schedule. Work-life balance is ingrained in our culture by design. Trust and accountability make it work.
• Donation matching. Give back? Give more! We match qualifying charitable donations annually.
• Tuition assistance. Want to level up your career? We love to hear it! Receive annual support for qualified programs.
• Lifestyle benefit. An annual benefit to spend on yourself. Use it on travel, wellness, or whatever suits you.
• Travel perks. We believe that travel is employee development, so we provide discounts and more.
• Employee assistance program. We’re here for you with resources and programs to help you through life’s challenges.
• Health benefits. We offer great coverage and competitive premiums.
• Generous referral scheme. Help us grow and be rewarded with generous awards for referring successful candidates.

Our Cultural Pillars:

Traveler first

We exist to create value for our customer, the traveler. We enable our suppliers and partners to unlock this value. Their collective behaviors and insights are what drives us. 

Execution is our edge

We act fast, experiment, learn from failure, iterate, and improve the solutions of tomorrow across every aspect of our business. Our execution is agile, data-driven, prioritised, and built to scale. We assume no problem is someone else’s problem and finish what can be done today, knowing tomorrow will bring fresh challenges. 

We succeed together

The best outcomes are driven by empathic, humble, and diverse subject matter experts working toward shared goals. We collaborate relentlessly, challenge assumptions, give actionable feedback, and set each other up for success through empowered teams with a clear charter. We transparently take ownership of our growth, individually and as a team. We celebrate the quality of our effort, our learnings, and our collective achievements.

We strive to create an accessible and inclusive experience for all candidates. If you need a reasonable accommodation during the application or the recruiting process, please make sure to reach out to your individual recruiter or our team at AccessibleRecruiting@tripadvisor.com.

If you have any additional questions about careers at Tripadvisor you can email us at recruitment@tripadvisor.com. We have all the answers!

#LI-Hybrid

#LI-JP

Job Title: Senior Python Engineer

Location: Remote (UK) with Occasional Travel - Applications from non-UK countries will be rejected
Division: Inizio Medical – Data & AI Team

About Inizio Medical

Inizio Medical is part of Inizio, the world’s leading healthcare and communications group. We are a trusted partner to pharmaceutical and healthcare clients, translating complex science into meaningful impact. Our division focuses on evidence-based communications and education for healthcare professionals and payers.

About the Role

We are seeking a senior, hands-on Python Engineer to join our growing Data & AI team. This role is ideal for an engineer who enjoys building robust backend systems, APIs, and services that power modern applications at scale.

You will work on the backend foundations of next-generation applications, including systems that incorporate generative AI and LLM-based capabilities. Prior experience with generative AI is not required—we are looking first and foremost for a strong Python engineer with excellent software engineering fundamentals who is interested in applying those skills in a fast-evolving domain.e

You’ll collaborate closely with software engineers, data scientists, and product teams to design, build, and operate production-grade systems used in real-world healthcare and life sciences environments.

Key Responsibilities

• Design, build, deploy, and maintain scalable Python services and APIs using modern backend and cloud-native patterns.
• Develop clean, testable, and well-structured Python code for data-intensive and workflow-driven applications.
• Build and integrate backend components that support AI-enabled features (e.g., orchestration layers, inference services, data pipelines).
• Integrate with third-party APIs and external services, ensuring reliability, performance, and cost efficiency.
• Own production concerns including logging, monitoring, error handling, and performance optimisation.
• Contribute to CI/CD pipelines, infrastructure-as-code, and containerised deployments.
• Collaborate with product, data, and engineering stakeholders to translate requirements into high-quality technical solutions.
• Write clear technical documentation for engineers and non-technical audiences.
• Contribute to a collaborative, pragmatic, and high-quality engineering culture.

About You

• Strong professional experience as a Python engineer, building and operating production systems (e.g., SaaS platforms, backend services, data-driven applications).
• Deep knowledge of Python fundamentals, including application architecture, performance considerations, testing, and maintainability.
• Experience building backend systems using frameworks such as FastAPI, Flask, Django, or similar.
• Solid understanding of cloud-based architectures (AWS and/or Azure), containers, and microservices.
• Experience working with CI/CD pipelines, version control, and modern development workflows.
• Strong debugging and problem-solving skills in distributed or data-heavy systems.
• Comfortable collaborating in cross-functional, Agile teams and taking ownership of delivered solutions.
• Curious, pragmatic, and motivated by building reliable systems that deliver real-world impact.

Nice to Have (Not Required)

• Exposure to data platforms or analytics workflows (e.g., Databricks, Airflow).
• Familiarity with LLMs, generative AI APIs, or AI-enabled application patterns.
• Experience with observability and monitoring tools (e.g., Prometheus, Grafana, Sentry).
• Contributions to open-source projects or shared internal libraries.
• Experience in regulated or high-compliance domains (e.g., healthcare, life sciences, finance).

What We Offer

• Competitive salary and benefits package, including private medical insurance and company pension.
• Flexible, remote-first working environment with occasional travel.
• The opportunity to work on meaningful, high-impact products within a global healthcare organisation.
• A friendly, low-ego culture that values engineering quality, learning, and collaboration.

Ready to Apply?

If you’re a strong Python engineer who enjoys building high-quality systems and is interested in applying your skills to emerging technologies in healthcare, we’d love to hear from you.

About the Role: 

We are seeking a highly experienced and results-oriented Staff Technical Program Manager (TPM) to drive AI-first engineering excellence efforts. Our mission is to improve engineering velocity, and you will act as a force multiplier on mission-critical, large, complex initiatives with a focus on AI enablement. In this role, you will be driving the technical roadmap that transforms how our engineering teams build software through AI-assisted workflows. This high-impact role requires a deep understanding of infrastructure, developer productivity, and the evolving landscape of AI tooling.

What you´ll do

• Lead the end-to-end program management for Engineering Excellence / AI readiness / AI DLC rollout projects.
• Integrate Claude Code and other AI-native development tools and skills management into existing engineering workflows for measurable productivity gains.
• Support Engineering Platform teams in efforts to modernize CI/CD pipelines, enabling automated AI-driven testing, code reviews, and deployment orchestration.
• Drive technical strategy and alignment across Engineering, Security, and Product leadership to address the unique challenges of AI-generated code and agentic autonomy.
• Align roadmaps across multiple teams and domains to roll out AI advances.
• Mentor other TPMs and engineers, raising the collective technical bar for AI-integrated program management across the organization.
• Solve problems, improve processes, remove bottlenecks, share updates - all the TPM bread and butter, AI-assisted (by you!) to be made as simple as possible, but not simpler.

Who You Are 

• Bachelor's degree or above in Computer Engineering, Computer Science, or a related technical field. You are an engineer or scientist by training.
• 10+ years of experience in technical program management or software engineering leadership. You are a manager by earned experience.
  Software development background with programming language proficiency and the ability to participate in architectural reviews. You are still a developer at heart.
• Extensive experience with AI-assisted development tools (e.g., Claude Code) and a strong understanding of LLM capabilities. You are hands-on.
• Expert-level knowledge of CI/CD methodologies, infrastructure-as-code, and cloud-native development environments. You automate at scale.
• Proven track record of leading large-scale, complex technical rollouts across multiple business units. You deliver.

Who we are

Typeform is a refreshingly different form builder. We help over 150,000 businesses collect the data they need through forms, surveys, and quizzes that people enjoy. Designed to look striking and feel effortless to fill out, Typeform drives 500 million responses every year and integrates with essential tools like Slack, Zapier, and HubSpot.

About the role

We are looking for a Senior Product Manager to own and evolve Integrations, the surface that connects every Typeform experience to the tools customers use to run their business.

Integrations is where Typeform stops being a destination and becomes part of the customer’s stack. Every response captured can flow into a CRM, a marketing tool, a database, a chat, or a spreadsheet, wherever the next step happens. That layer needs to be deep, dependable, and easy to extend, at the scale of 500 million responses a year for 150,000 businesses across the long tail of tools they rely on. It has to be reliable, observable, secure, and able to scale as customer stacks become more sophisticated.

In this role, you will own Integrations end to end. You will evolve the platform while partnering with Automations and Typeform AI to make the integrations layer the substrate for both customer configured and agentic workflows.

Your work will define how Typeform plugs into the rest of the SaaS world for tens of thousands of customers, and how AI agents take action through it.

About the team

The Integrations team owns the layer that connects Typeform to the broader SaaS ecosystem: the connectors, auth flows, the action catalog, and the partner experience that makes it all work. Hundreds of millions of integration calls flow through this surface every year.

The team sits inside the Workflow Automations group alongside Automations, and works closely with Data Capture upstream, as well as with the Partnerships team and external partners across the long tail of tools customers rely on.

Things you will do

• Own both data out and data in integrations end to end, and drive the strategy in line with the Workflow Automations group vision and priorities
• Build and maintain traditional API integrations, as well as agentic MCP based integrations
• Evolve the platform so customers, partners, and agents can build on it with confidence
• Deepen priority integrations, the ones that move the most business, and define how new ones are onboarded
• Partner with Automations to make integrations the substrate AI agents act through, without fragmenting the surface
• Set the architectural direction for the integrations platform remit, partnering closely with engineering on the trade offs that come with it
• Define and own the next phase of Integrations, with a clear thesis and quarterly sequencing
• Influence group level decisions through compelling storytelling and strategic framing
• Monitor competitors, market trends, and shifts in customer expectations, including the fast moving AI landscape, to identify opportunities and guide strategy
• Work cross functionally with engineering, design, research, marketing, customer success, sales, and Partnerships to align on priorities and technical direction
• Leverage AI tools to accelerate discovery, analysis, documentation, and decision making

What you already bring to the table

• A strategic thinker with strong product instincts and high ownership
• Platform PM experience with real depth; you have built or shipped integration platforms, connector frameworks, or developer facing surfaces, and understand what it takes to scale them
• Deep familiarity with developer facing surfaces, including APIs, webhooks, SDKs, OAuth and auth flows, and event systems
• Familiarity with agents, LLMs, context management, and RAG
• An understanding of how integrations underpin workflow automation and agentic action, alongside a strong point of view on the platform shift happening across both
• An AI native mindset; you actively build with LLMs, agents, and tool use frameworks, and treat AI fluency as a core multiplier rather than a buzzword
• Technical depth and comfort engaging with engineers on the underlying mechanics of an integrations product, including auth flows, connector architecture, rate limiting, retries, and event flows, not just the abstraction layer
• Comfort with technical trade off discussions around reliability, observability, performance, and partner contract changes
• Strong product sense and the ability to identify what makes an integrations surface feel reliable, deep, and effortless
• A customer first mindset with strong discovery and validation skills; able to pair early customer signals with data to test ideas quickly
• Strong storytelling and strategic framing skills; able to align and influence cross functional teams and leadership through clarity and narrative
• A strong triad collaborator who builds solid relationships with engineering and design, and leads through influence
• High agency and a proactive mindset
• Strong product craft, including writing clear specifications and managing complex cross team initiatives
• A data driven approach to decision making and prioritisation; able to define the measurement model for the Integrations surface without relying on a data analyst for every question
• Comfort operating in ambiguous environments and defining direction where none exists
• Experience working in distributed and remote teams, with the ability to maintain alignment and momentum asynchronously
• A mindset of continuous learning, improvement, and collaboration

Nice to have

• Experience shipping integration platforms or iPaaS products such as Zapier, Make, Workato, Tray.io, or n8n
• Experience as a PM on a third party integrations surface inside a horizontal SaaS ecosystem such as Slack, HubSpot, Salesforce, or Notion
• Experience designing developer platforms, including SDKs, developer portals, marketplaces, and partner programs
• Experience launching an LLM powered or agentic feature where integrations were the action surface
• Experience working with external partners and partner business development teams

This is where you will make an impact

Integrations is where Typeform stops being a destination and becomes part of the customer’s stack. You will own the layer that connects 150,000 businesses to the hundreds of tools they rely on: the connectors, auth, the action catalog, and the platform that makes it all work.

You will also help lead the shift from manual connections to agentic action, the moment integrations stop being a checkbox and become the substrate every workflow and every agent runs through.

About the Role

We’re hiring an AI Solutions Architect to lead the future of IT systems and automation at Fortis. This senior-level role focuses on improving how our internal tech works — using AI, automation, and innovative design to make everything more secure, scalable, and efficient.

You’ll lead the design of our IT tools and platforms, ensuring they’re modern, user-friendly, and powered by cutting-edge AI like LLMs (think ChatGPT, Gemini, and similar tools). This role reports to the Director of IT. It works closely with Security, Legal, Engineering, and other departments to ensure our IT systems are robust, safe, compliant, and built to scale.

This isn’t just an execution or admin role — it’s a leadership position for someone who can research, propose, and help drive future-focused IT strategies across the business.

What You'll Achieve

• Define and implement scalable, secure, AI-driven IT architectures aligned with business needs.
• Research, propose, and implement AI/LLM-based automation for IT processes, support systems, and knowledge management.
• Lead AI initiatives and strategy sessions, chairing technology trend discussions and quarterly IT innovation reviews.
• Architect and deploy cloud-native, automation-first IT systems — focused on resilience, performance, and zero-touch management.
• Implement AI-powered IT service desk solutions, compliance monitoring, incident response, and proactive issue resolution.
• Guide IT Operations in optimizing hardware lifecycle, SaaS platforms, and IT asset tracking through AI/automation-driven efficiency.
• Collaborate closely with Security and Legal teams to align AI and IT architecture with compliance, risk management, and privacy standards.
• Drive tool rationalization and consolidation projects using AI analytics to inform more intelligent decision-making.
• Partner with engineering, AI/ML teams, and vendors to integrate IT systems into our broader AI development ecosystem.

What You’ll Need to Be Successful

• Solid experience in IT engineering, IT architecture and cloud-native systems — with a recent, strong focus on AI, automation, and LLMs.
• Experience with AI technologies like large language models (LLMs), MLOps tools, and generative AI platforms (e.g., ChatGPT/OpenAI, Gemini AI, Notion AI). You’ve used these tools to help build or improve systems, not just test them.
• Practical experience building, integrating, or experimenting with AI models, LLMs, and AI-driven workflows.
• Working knowledge of enterprise IT environments, including Google Workspace, Okta, JAMF, Intune, Zoom, Slack, and Cisco Meraki, plus an understanding of cloud infrastructure (AWS, GCP, or Azure).
• Exceptional skills in technical documentation, architecture diagramming, and project planning and execution, plus an understanding of  GDPR, NIST, and SOC 2.
• Ability to explain complex technology and AI clearly and simply to all audiences. Skilled at leading conversations that shape the right technology direction, drive innovation, and bring new ideas to life. 
• Confident in leading executive meetings, managing AI committees, and guiding leadership teams toward smart, forward-thinking technology decisions.
• Game/software development experience strongly preferred where LLMs or automation were part of the tech stack, showcasing creativity, speed, and next-gen thinking.

About the Role

We’re hiring an AI Solutions Architect to lead the future of IT systems and automation at Fortis. This senior-level role focuses on improving how our internal tech works — using AI, automation, and innovative design to make everything more secure, scalable, and efficient.

You’ll lead the design of our IT tools and platforms, ensuring they’re modern, user-friendly, and powered by cutting-edge AI like LLMs (think ChatGPT, Gemini, and similar tools). This role reports to the Director of IT. It works closely with Security, Legal, Engineering, and other departments to ensure our IT systems are robust, safe, compliant, and built to scale.

This isn’t just an execution or admin role — it’s a leadership position for someone who can research, propose, and help drive future-focused IT strategies across the business.

What You'll Achieve

• Define and implement scalable, secure, AI-driven IT architectures aligned with business needs.
• Research, propose, and implement AI/LLM-based automation for IT processes, support systems, and knowledge management.
• Lead AI initiatives and strategy sessions, chairing technology trend discussions and quarterly IT innovation reviews.
• Architect and deploy cloud-native, automation-first IT systems — focused on resilience, performance, and zero-touch management.
• Implement AI-powered IT service desk solutions, compliance monitoring, incident response, and proactive issue resolution.
• Guide IT Operations in optimizing hardware lifecycle, SaaS platforms, and IT asset tracking through AI/automation-driven efficiency.
• Collaborate closely with Security and Legal teams to align AI and IT architecture with compliance, risk management, and privacy standards.
• Drive tool rationalization and consolidation projects using AI analytics to inform more intelligent decision-making.
• Partner with engineering, AI/ML teams, and vendors to integrate IT systems into our broader AI development ecosystem.

What You’ll Need to Be Successful

• Solid experience in IT engineering, IT architecture and cloud-native systems — with a recent, strong focus on AI, automation, and LLMs.
• Experience with AI technologies like large language models (LLMs), MLOps tools, and generative AI platforms (e.g., ChatGPT/OpenAI, Gemini AI, Notion AI). You’ve used these tools to help build or improve systems, not just test them.
• Practical experience building, integrating, or experimenting with AI models, LLMs, and AI-driven workflows.
• Working knowledge of enterprise IT environments, including Google Workspace, Okta, JAMF, Intune, Zoom, Slack, and Cisco Meraki, plus an understanding of cloud infrastructure (AWS, GCP, or Azure).
• Exceptional skills in technical documentation, architecture diagramming, and project planning and execution, plus an understanding of  GDPR, NIST, and SOC 2.
• Ability to explain complex technology and AI clearly and simply to all audiences. Skilled at leading conversations that shape the right technology direction, drive innovation, and bring new ideas to life. 
• Confident in leading executive meetings, managing AI committees, and guiding leadership teams toward smart, forward-thinking technology decisions.
• Game/software development experience strongly preferred where LLMs or automation were part of the tech stack, showcasing creativity, speed, and next-gen thinking.

About the Role

We’re hiring an AI Solutions Architect to lead the future of IT systems and automation at Fortis. This senior-level role focuses on improving how our internal tech works — using AI, automation, and innovative design to make everything more secure, scalable, and efficient.

You’ll lead the design of our IT tools and platforms, ensuring they’re modern, user-friendly, and powered by cutting-edge AI like LLMs (think ChatGPT, Gemini, and similar tools). This role reports to the Director of IT. It works closely with Security, Legal, Engineering, and other departments to ensure our IT systems are robust, safe, compliant, and built to scale.

This isn’t just an execution or admin role — it’s a leadership position for someone who can research, propose, and help drive future-focused IT strategies across the business.

What You'll Achieve

• Define and implement scalable, secure, AI-driven IT architectures aligned with business needs.
• Research, propose, and implement AI/LLM-based automation for IT processes, support systems, and knowledge management.
• Lead AI initiatives and strategy sessions, chairing technology trend discussions and quarterly IT innovation reviews.
• Architect and deploy cloud-native, automation-first IT systems — focused on resilience, performance, and zero-touch management.
• Implement AI-powered IT service desk solutions, compliance monitoring, incident response, and proactive issue resolution.
• Guide IT Operations in optimizing hardware lifecycle, SaaS platforms, and IT asset tracking through AI/automation-driven efficiency.
• Collaborate closely with Security and Legal teams to align AI and IT architecture with compliance, risk management, and privacy standards.
• Drive tool rationalization and consolidation projects using AI analytics to inform more intelligent decision-making.
• Partner with engineering, AI/ML teams, and vendors to integrate IT systems into our broader AI development ecosystem.

What You’ll Need to Be Successful

• Solid experience in IT engineering, IT architecture and cloud-native systems — with a recent, strong focus on AI, automation, and LLMs.
• Experience with AI technologies like large language models (LLMs), MLOps tools, and generative AI platforms (e.g., ChatGPT/OpenAI, Gemini AI, Notion AI). You’ve used these tools to help build or improve systems, not just test them.
• Practical experience building, integrating, or experimenting with AI models, LLMs, and AI-driven workflows.
• Working knowledge of enterprise IT environments, including Google Workspace, Okta, JAMF, Intune, Zoom, Slack, and Cisco Meraki, plus an understanding of cloud infrastructure (AWS, GCP, or Azure).
• Exceptional skills in technical documentation, architecture diagramming, and project planning and execution, plus an understanding of  GDPR, NIST, and SOC 2.
• Ability to explain complex technology and AI clearly and simply to all audiences. Skilled at leading conversations that shape the right technology direction, drive innovation, and bring new ideas to life. 
• Confident in leading executive meetings, managing AI committees, and guiding leadership teams toward smart, forward-thinking technology decisions.
• Game/software development experience strongly preferred where LLMs or automation were part of the tech stack, showcasing creativity, speed, and next-gen thinking.

About the Role

We’re hiring an AI Solutions Architect to lead the future of IT systems and automation at Fortis. This senior-level role focuses on improving how our internal tech works — using AI, automation, and innovative design to make everything more secure, scalable, and efficient.

You’ll lead the design of our IT tools and platforms, ensuring they’re modern, user-friendly, and powered by cutting-edge AI like LLMs (think ChatGPT, Gemini, and similar tools). This role reports to the Director of IT. It works closely with Security, Legal, Engineering, and other departments to ensure our IT systems are robust, safe, compliant, and built to scale.

This isn’t just an execution or admin role — it’s a leadership position for someone who can research, propose, and help drive future-focused IT strategies across the business.

What You'll Achieve

• Define and implement scalable, secure, AI-driven IT architectures aligned with business needs.
• Research, propose, and implement AI/LLM-based automation for IT processes, support systems, and knowledge management.
• Lead AI initiatives and strategy sessions, chairing technology trend discussions and quarterly IT innovation reviews.
• Architect and deploy cloud-native, automation-first IT systems — focused on resilience, performance, and zero-touch management.
• Implement AI-powered IT service desk solutions, compliance monitoring, incident response, and proactive issue resolution.
• Guide IT Operations in optimizing hardware lifecycle, SaaS platforms, and IT asset tracking through AI/automation-driven efficiency.
• Collaborate closely with Security and Legal teams to align AI and IT architecture with compliance, risk management, and privacy standards.
• Drive tool rationalization and consolidation projects using AI analytics to inform more intelligent decision-making.
• Partner with engineering, AI/ML teams, and vendors to integrate IT systems into our broader AI development ecosystem.

What You’ll Need to Be Successful

• Solid experience in IT engineering, IT architecture and cloud-native systems — with a recent, strong focus on AI, automation, and LLMs.
• Experience with AI technologies like large language models (LLMs), MLOps tools, and generative AI platforms (e.g., ChatGPT/OpenAI, Gemini AI, Notion AI). You’ve used these tools to help build or improve systems, not just test them.
• Practical experience building, integrating, or experimenting with AI models, LLMs, and AI-driven workflows.
• Working knowledge of enterprise IT environments, including Google Workspace, Okta, JAMF, Intune, Zoom, Slack, and Cisco Meraki, plus an understanding of cloud infrastructure (AWS, GCP, or Azure).
• Exceptional skills in technical documentation, architecture diagramming, and project planning and execution, plus an understanding of  GDPR, NIST, and SOC 2.
• Ability to explain complex technology and AI clearly and simply to all audiences. Skilled at leading conversations that shape the right technology direction, drive innovation, and bring new ideas to life. 
• Confident in leading executive meetings, managing AI committees, and guiding leadership teams toward smart, forward-thinking technology decisions.
• Game/software development experience strongly preferred where LLMs or automation were part of the tech stack, showcasing creativity, speed, and next-gen thinking.

The Role

Portfolio Data Integration is part of the broader Addepar Platform team. The overall Addepar Platform provides a single source of truth “data fabric” used by the Addepar product set, including a centralized and self-describing repository (a.k.a Data Lake), a set of API-driven data services, an integration pipeline, analytics infrastructure, warehousing solutions, and operating tools. The team has responsibility for all data acquisition, conversion, cleansing, disambiguation, modeling, tooling and infrastructure related to the integration of client portfolio data.

Addepar’s core business relies on the ability to quickly and accurately ingest data from a variety of sources, including 3rd party data providers, custodial banks, data APIs, and even direct user input. Portfolio Data integrations and feeds are a highly critical cross-section of this set, allowing our users to get automatically updated and reconciled information on their latest holdings onto the platform.

As a data engineer for this team, you will execute the development of new data integrations and maintenance of existing processes in order to expand and improve our data platform. You’ll be adding automation and functionality to our distributed data pipelines by writing PySpark code and integrating it within our Databricks Data Lake. The team operates with an AI-augmented engineering workflow — LLM tools are integrated into code review, testing, and documentation as standard practice, not an experiment. As you gain more experience, you’ll contribute to increasingly challenging engineering projects within our platform with the ultimate goal of dramatically increasing the throughput of data ingestion for Addepar. This is a crucial, highly visible role within the company. Your team is a big component of growing and serving Addepar’s client base with minimal manual effort required from our clients or from our internal data operations team.

Applicants must have, and maintain, the right to work in the United Kingdom from the first day of employment. Please note that visa sponsorship is not available for this role.

What You’ll Do

• Complete individual project priorities, deadlines, and solutions.
• Build pipelines that support the ingestion, analysis, and enrichment of financial data in partnership with business data analysts
• Improve the existing pipeline to increase the throughput and accuracy of data
• Develop and maintain efficient process controls and accurate metrics to ensure quality standards and organizational expectations are met
• Partner with members of Product and Engineering to design, test, and implement new processes and tooling features that improve data quality as well as increase operational efficiency
• Identify areas of automation opportunities and implement improvements
• Understand data models and schemas, and work with other engineering teams to recommend extensions and changes
• Use AI-assisted development workflows — The team uses LLM tools (Claude Code) as a standard part of the engineering workflow: pre-review, test generation, code analysis, and documentation. You'll be expected to adopt and contribute to these workflows
• Maintain and improve automated quality gates — Work with AI-powered code review tooling to enforce coding standards, catch regressions before human review, and reduce manual toil in the PR process

Who You Are

• Prior professional data engineering/analysis experience
• Experience with object-oriented programming (we use PySpark/Python)
• Knowledge of SQL or relational database concepts
• Experience in data modeling, visualization, and ETL pipelines
• Comfort working with AI/LLM tools as part of your development workflow (e.g., code assistants, automated review, AI-generated tests). You don't need to be an expert — but you should be curious and willing to adopt new tooling quickly
• Knowledge of financial concepts (e.g., stocks, bonds, etc.) is helpful but not necessary
• Passion for the world of FinTech and solving previously intractable problems at the heart of investment management

ABOUT THE ROLE

Tide is hiring a Senior Staff Software Engineer to lead the architecture of our agentic platform.

You will shape the shared capabilities that allow AI systems to operate safely, reliably, and at scale across Tide. That includes context, orchestration, tool execution, trust controls, observability, and evaluation. You will participate in key build versus buy decisions, integrate external components where they accelerate us, and ensure we own the parts that matter most for Tide’s trust, data advantage, and long-term platform leverage.

WHAT YOU WILL DO

• Define the architecture for Tide’s agentic platform
• Drive the design of shared services such as context APIs, tool layers, policy controls, and auditability
• Partner with product, data, security, and engineering teams to turn use cases into reusable platform capabilities
• Set standards for reliability, safety, scalability, and developer experience
• Provide technical leadership across teams and unblock critical decisions
• Implement cost-management and routing logic to optimize LLM spend across different providers
• Design and build automated evaluation pipelines to measure agent reasoning accuracy and safety trajectories

WHAT WE ARE LOOKING FOR

• Deep experience building platform or infrastructure systems at scale
• Strong judgement across APIs, distributed systems, data, and cloud-native architecture
• Track record of leading complex cross-team technical problems
• Experience integrating third-party platforms without losing control of core architecture
• Strong understanding of reliability, security, and observability
• Experience with AI platform components is valuable, but not essential
• Experience in highly regulated industries (Fintech, Healthtech, etc.) where safety and compliance are core to the product is highly desirable 

WHY THIS ROLE MATTERS

This role will help determine whether Tide builds isolated AI pilots or a reusable platform that compounds value across productivity, risk, and connectivity.

OUR TECH STACK:

• Java, Spring Boot and JOOQ to build the RESTful APIs of our microservices (but we welcome people who are used to any strongly typed general purpose programming language!)
• Event-driven architecture with messages over SNS+SQS and Kafka to make them reliable
• Primary datastores are MySQL and PostgreSQL via RDS or Aurora (we are heavy AWS users)
• Docker, Terraform, EKS used by the Cloud team to run the platform
• DataDog and Rollbar to keep it running
• GitHub with Sonarcloud, Semgrep and solid testing to power the CI/CD pipelines - new joiners are encouraged to have something deployed to production in their first 2 weeks
• Angular 2+ with ngrx on Web, Flutter for the Mobile App
• Fivetran/Snowflake/Looker for the BI insights and Python/Faust/Flask/Tecton + some ML libs for the automated decisioning and risk management

WHAT YOU’LL GET IN RETURN

• The gross monthly salary for this position ranges from 7400€ to 11560€, depending on your skills, and experience.
• Private Health Insurance
• 25 days paid annual leave
• 3 paid days off for volunteering or L&D activities
• Parental Leave days 
• Family-Friendly Leave 
• Personal L&D budget in the amount of 500 EUR per year
• Mental wellbeing platform Plumm
• WFH equipment allowance
• Sabbatical Leave
• Share options
• Team Events

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

ABOUT THE ROLE

Tide is hiring a Senior Staff Software Engineer to lead the architecture of our agentic platform.

You will shape the shared capabilities that allow AI systems to operate safely, reliably, and at scale across Tide. That includes context, orchestration, tool execution, trust controls, observability, and evaluation. You will participate in key build versus buy decisions, integrate external components where they accelerate us, and ensure we own the parts that matter most for Tide’s trust, data advantage, and long-term platform leverage.

WHAT YOU WILL DO

• Define the architecture for Tide’s agentic platform
• Drive the design of shared services such as context APIs, tool layers, policy controls, and auditability
• Partner with product, data, security, and engineering teams to turn use cases into reusable platform capabilities
• Set standards for reliability, safety, scalability, and developer experience
• Provide technical leadership across teams and unblock critical decisions
• Implement cost-management and routing logic to optimize LLM spend across different providers
• Design and build automated evaluation pipelines to measure agent reasoning accuracy and safety trajectories

WHAT WE ARE LOOKING FOR

• Deep experience building platform or infrastructure systems at scale
• Strong judgement across APIs, distributed systems, data, and cloud-native architecture
• Track record of leading complex cross-team technical problems
• Experience integrating third-party platforms without losing control of core architecture
• Strong understanding of reliability, security, and observability
• Experience with AI platform components is valuable, but not essential
• Experience in highly regulated industries (Fintech, Healthtech, etc.) where safety and compliance are core to the product is highly desirable 

WHY THIS ROLE MATTERS

This role will help determine whether Tide builds isolated AI pilots or a reusable platform that compounds value across productivity, risk, and connectivity.

OUR TECH STACK:

• Java, Spring Boot and JOOQ to build the RESTful APIs of our microservices (but we welcome people who are used to any strongly typed general purpose programming language!)
• Event-driven architecture with messages over SNS+SQS and Kafka to make them reliable
• Primary datastores are MySQL and PostgreSQL via RDS or Aurora (we are heavy AWS users)
• Docker, Terraform, EKS used by the Cloud team to run the platform
• DataDog and Rollbar to keep it running
• GitHub with Sonarcloud, Semgrep and solid testing to power the CI/CD pipelines - new joiners are encouraged to have something deployed to production in their first 2 weeks
• Angular 2+ with ngrx on Web, Flutter for the Mobile App
• Fivetran/Snowflake/Looker for the BI insights and Python/Faust/Flask/Tecton + some ML libs for the automated decisioning and risk management

WHAT YOU’LL GET IN RETURN: 

Our location-specific employee benefits are designed to cater to the unique needs of Tideans: 

• Remote first
• 25 days of paid annual leave
• 3 paid days off for volunteering or L&D activities
• Private Health Insurance
• Mental Health Support Platform
• FitPass
• Family and friendly leave (according to statutory)
• Personal L&D budget
• Share Options

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

ABOUT THE ROLE

Tide is hiring a Senior Staff Software Engineer to lead the architecture of our agentic platform.

You will shape the shared capabilities that allow AI systems to operate safely, reliably, and at scale across Tide. That includes context, orchestration, tool execution, trust controls, observability, and evaluation. You will participate in key build versus buy decisions, integrate external components where they accelerate us, and ensure we own the parts that matter most for Tide’s trust, data advantage, and long-term platform leverage.

WHAT YOU WILL DO

• Define the architecture for Tide’s agentic platform
• Drive the design of shared services such as context APIs, tool layers, policy controls, and auditability
• Partner with product, data, security, and engineering teams to turn use cases into reusable platform capabilities
• Set standards for reliability, safety, scalability, and developer experience
• Provide technical leadership across teams and unblock critical decisions
• Implement cost-management and routing logic to optimize LLM spend across different providers
• Design and build automated evaluation pipelines to measure agent reasoning accuracy and safety trajectories

WHAT WE ARE LOOKING FOR

• Deep experience building platform or infrastructure systems at scale
• Strong judgement across APIs, distributed systems, data, and cloud-native architecture
• Track record of leading complex cross-team technical problems
• Experience integrating third-party platforms without losing control of core architecture
• Strong understanding of reliability, security, and observability
• Experience with AI platform components is valuable, but not essential
• Experience in highly regulated industries (Fintech, Healthtech, etc.) where safety and compliance are core to the product is highly desirable 

WHY THIS ROLE MATTERS

This role will help determine whether Tide builds isolated AI pilots or a reusable platform that compounds value across productivity, risk, and connectivity.

OUR TECH STACK:

• Java, Spring Boot and JOOQ to build the RESTful APIs of our microservices (but we welcome people who are used to any strongly typed general purpose programming language!)
• Event-driven architecture with messages over SNS+SQS and Kafka to make them reliable
• Primary datastores are MySQL and PostgreSQL via RDS or Aurora (we are heavy AWS users)
• Docker, Terraform, EKS used by the Cloud team to run the platform
• DataDog and Rollbar to keep it running
• GitHub with Sonarcloud, Semgrep and solid testing to power the CI/CD pipelines - new joiners are encouraged to have something deployed to production in their first 2 weeks
• Angular 2+ with ngrx on Web, Flutter for the Mobile App
• Fivetran/Snowflake/Looker for the BI insights and Python/Faust/Flask/Tecton + some ML libs for the automated decisioning and risk management

WHAT YOU’LL GET IN RETURN: 

Our location-specific employee benefits are designed to cater to the unique needs of Tideans: 

• 25 days paid annual leave
• 3 paid days off for volunteering or L&D activities
• Extended maternity and paternity leave covered by the company
• Personal L&D budget in the amount of 500 EUR per year
• Additional health & dental insurance
• Mental wellbeing platform
• Fully covered Multisports card
• Food vouchers
• Snacks, light food, drinks in the office
• WFH equipment allowance
• Flexible working from home
• Sabbatical Leave
• Share options

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

Location : London, Bulgaria, Serbia and Lithuania

ABOUT THE ROLE

Tide is hiring a Senior Staff Software Engineer to lead the architecture of our agentic platform.

You will shape the shared capabilities that allow AI systems to operate safely, reliably, and at scale across Tide. That includes context, orchestration, tool execution, trust controls, observability, and evaluation. You will participate in key build versus buy decisions, integrate external components where they accelerate us, and ensure we own the parts that matter most for Tide’s trust, data advantage, and long-term platform leverage.

WHAT YOU WILL DO

• Define the architecture for Tide’s agentic platform
• Drive the design of shared services such as context APIs, tool layers, policy controls, and auditability
• Partner with product, data, security, and engineering teams to turn use cases into reusable platform capabilities
• Set standards for reliability, safety, scalability, and developer experience
• Provide technical leadership across teams and unblock critical decisions
• Implement cost-management and routing logic to optimize LLM spend across different providers
• Design and build automated evaluation pipelines to measure agent reasoning accuracy and safety trajectories

WHAT WE ARE LOOKING FOR

• Deep experience building platform or infrastructure systems at scale
• Strong judgement across APIs, distributed systems, data, and cloud-native architecture
• Track record of leading complex cross-team technical problems
• Experience integrating third-party platforms without losing control of core architecture
• Strong understanding of reliability, security, and observability
• Experience with AI platform components is valuable, but not essential
• Experience in highly regulated industries (Fintech, Healthtech, etc.) where safety and compliance are core to the product is highly desirable 

WHY THIS ROLE MATTERS

This role will help determine whether Tide builds isolated AI pilots or a reusable platform that compounds value across productivity, risk, and connectivity.

OUR TECH STACK:

• Java, Spring Boot and JOOQ to build the RESTful APIs of our microservices (but we welcome people who are used to any strongly typed general purpose programming language!)
• Event-driven architecture with messages over SNS+SQS and Kafka to make them reliable
• Primary datastores are MySQL and PostgreSQL via RDS or Aurora (we are heavy AWS users)
• Docker, Terraform, EKS used by the Cloud team to run the platform
• DataDog and Rollbar to keep it running
• GitHub with Sonarcloud, Semgrep and solid testing to power the CI/CD pipelines - new joiners are encouraged to have something deployed to production in their first 2 weeks
• Angular 2+ with ngrx on Web, Flutter for the Mobile App
• Fivetran/Snowflake/Looker for the BI insights and Python/Faust/Flask/Tecton + some ML libs for the automated decisioning and risk management

WHAT YOU'LL GET IN RETURN

• Flexible working options
• Group Life Insurance
• Vitality Health Insurance, with a proactive focus on mental and physical wellbeing
• 25 days holiday with the ability to buy extra days
• 3 days for L&D or volunteering time off per year
• We invest in your development with a £1,000 professional L&D budget per year
• Access to ‘salary sacrifice’ benefits such as Cycle to Work scheme and pension contribution
• Spacious brand-new office near Old Street with an all-day snacks bar
• Enhanced family-friendly leave
• Sabbatical leave

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Growth Marketing is a team of performance-driven marketers and channel specialists. We partner closely with growth, creative, analytics and regional marketing to drive revenue through self-serve and sales motions. We work globally, across all Stripe offerings and with all company segments - from startups to the largest enterprises.

What you’ll do

Stripe is seeking an SEO to lead the SEO strategy for Stripe Docs, in close partnership with the Global SEO Lead. This individual will play a key role in growing the SEO channel by developing and executing efforts to increase Stripe’s revenue and visibility. The scope includes on-site optimization, content development, international SEO, and technical SEO.

While the ideal candidate is well-versed in all SEO disciplines, sensibilities around user-experience, design, engineering, copywriting, data, product management, and marketing are also required. In this role, you will work closely with cross-functional partners, including Growth Marketing, Product Marketing, Content Marketing, Engineering, Developer Relations, Design, Product, and Analytics. 

Responsibilities

• On-site optimization: enhance the website’s content and structure to improve search engine rankings and user experience.
• International SEO: develop strategies to optimize the website for multiple countries and languages, driving global visibility and engagement.
• Technical SEO: address backend improvements to ensure the website is compatible and optimized for search engine technologies and LLM agents.
• Roadmap development: develop strategic plans outlining key SEO initiatives and timelines to achieve short-term and long-term objectives.
• Performance reporting: analyze and report on KPIs to track progress and identify opportunities for further enhancement.

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 4+ years of experience crafting and executing SEO strategies.
• Motivated self-starter with high attention to detail, strong follow-through, and the ability to problem-solve independently and carry out tasks with autonomy.
• Tech savvy and cognizant of developments in technology/fintech. 
• Deep expertise in researching and interpreting search queries for developer audiences.
• Basic experience with HTML, CSS, and other web programming acumens.
• Deep expertise in all disciplines of SEO, including technical, on-site, and off-site SEO.
• Ability to develop and prioritize content roadmaps to build net new pages that drive incremental business performance.
• Data-driven, and results-oriented leader that’s proficient in B2B and SEO performance data.
• Proven track record of building scalable systems to successfully execute SEO plans.
• Deep expertise in IA and site architecture.
• Ability to develop exhaustive creative briefs for cross-functional execution. 
• Excellent communication, presentation, and soft skills (written and verbal) to effectively evangelize and educate on SEO internally.
• Strong cross-functional collaborator with the ability to build relationships and simplify complex topics for partners. Must possess intermediate sensibilities in user-experience, design, engineering, copywriting, conversion rate optimization, data, product management, and marketing
• Ability to develop and prioritize roadmaps that successfully deliver on business objectives.
• Excellent international SEO skills.
• Strong experience creating performance reporting and measuring success.
• Ability to work extensively in Google Drive apps (Docs, Sheets, Slides), Excel, Looker, Tableau, Google Analytics and other reporting software.
• Experience managing stakeholders, with the ability to handle multiple work streams and requests from a variety of stakeholders, balancing each of them to deliver on the true north objectives of the channel and business.
• Strong experience using a variety of SEO tools, including Google Search Console, Google Keyword Planner, SEMRush, and ScreamingFrog.
• Proficient in professional English literacy.

Preferred qualifications

• Experience crafting SEO strategies to acquire technical users (i.e. engineers) and/or partnering closely with Developer Marketing or Developer Relations is highly preferred.
• In-house, enterprise SEO experience is highly preferred.
• Intermediate software engineering background.
• Experience in the following industries: payments, fintech, billing, accounting, tax, startups, enterprise business, and platforms.
• Experience optimizing YouTube video content for search. 
• Multilingual literacy is advantageous in any of: German, French, Japanese, Italian, and/or Spanish.
• Experience with localization / translation.
• B2B experience.
• SQL experience and ability to gather data.
• Experience with telemetry and web analytics.
• Bachelor's degree or 4 years relevant experience.

The role

This role is for Nebius AI R&D, a team focused on applied research and the development of AI-heavy products. Examples of applied research that we have recently published include:

• investigating how test-time guided search can be used to build more powerful agents;
• dramatically scaling task data collection to power reinforcement learning for SWE agents;
• maximizing efficiency of LLM training on agentic trajectories.

One example of an AI product that we are deeply involved in is Nebius Token Factory — an inference and fine-tuning platform for AI models.

This role will require expertise in distributed systems to build large-scale LLM training platform.

Your responsibilities will include: 

• Designing and developing LLM training platform.
• Maintaining our ML infrastructure, ensuring optimal performance, scalability and reliability.
• Improving job scheduling strategies to minimize resource fragmentation. 

We expect you to have:

• 5+ years of professional software development experience.
• Strong software engineering skills (we mostly use Python and Go).
• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing.
• Experience with developing web services.
• A commitment to maintaining extreme rigor in all job-related activities.

Nice to have:

• Previous experience working with language models or other similar NLP technologies.
• A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.
• Strong engineering skills, including experience in developing large distributed systems or high-load web services.
• Open-source projects that showcase your engineering prowess.

The role

Token Factory is a part of Nebius Cloud, one of the world’s largest GPU clouds, running tens of thousands of GPUs. We are building an inference & fine-tuning platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to train & deploy at massive scale.

• Advanced Fine-Tuning: Enhancing fine-tuning methodologies - both LoRA-based and full-parameter - for cutting-edge LLMs (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-4.7), focusing on both model quality and training efficiency.

• Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. This involves building model training and evaluation pipelines in JAX for speculative decoding, experimenting with architectures (dense/MoE, auto-regressive/parallel), and deriving scaling laws to guide resource allocation.                                                                                
• Low Precision Training & Inference: Investigating low-precision (FP8, NVFP4/MXFP4) methodologies for supervised fine-tuning and reinforcement learning - spanning both inference and training - optimized for modern hardware

We expect you to have:

• A profound understanding of theoretical foundations of machine learning and reinforcement learning.

• Deep expertise in modern deep learning for language processing and generation

• Experience with training large models on multiple computational nodes

• Reasonable understanding of performance aspects of large neural network training (sharding strategies, custom kernels, hardware features etc.)

• Strong software engineering skills (we mostly use Python)

• Deep experience with modern deep learning frameworks (we use JAX)

• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing

• Strong communication and leadership abilities

Nice to have:

• Previous experience working with language models or other similar NLP technologies.

• Familiarity with important ideas in LLM space, such as MHA, RoPE, ZeRO/FSDP, Flash Attention, quantization

• A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.

• Strong engineering skills, including experience in developing large distributed systems or high-load web services.

• Open-source projects that showcase your engineering prowess

• Excellent command of the English language, alongside superior writing, articulation, and communication skills.

Location: Miami, FL | London, UK | Remote (US)

The Problem and the Role

OpenFX is on a mission to move money as freely as data, unrestricted by time zones, banking hours, or legacy systems. We are building the infrastructure that will power the next generation of cross-border payment systems for institutions.

We are seeking a Developer Experience Lead, who will report to the head of Product Growth, to own the entire developer-facing surface of our platform, from documentation to integration support to API governance. We have built a world-class financial engine, but how external developers experience that engine has no owner. This role fills that gap.

This is a foundational role. You will be the first hire in this function. You will architect the documentation ecosystem from the ground up, define the processes that keep it accurate as the platform evolves, and directly support the clients who integrate with our APIs. Over time, you will shape how Developer Experience operates as a discipline at OpenFX, influencing product decisions, integration strategy, and the developer journey end-to-end.

You will set the bar higher than industry standards, building a knowledge system that turns complex FX liquidity and cross-border payment flows into a Hello World integration in under 15 minutes.

What You'll Actually Do & Own

• Drive API Product Adoption: You own API adoption as a measurable outcome. You instrument the funnel from API key activation to first API call to first transaction to expanded endpoint usage. You set the baseline, define the targets, and drive the cross-functional work to move the number. Every quarter, more developers are activated, more endpoints are used, and integrations go deeper. This is what you are accountable for, not pages shipped.
• Architect the Documentation System: Documentation is the primary adoption surface. You own the information architecture and the words. You design the taxonomy that scales from a simple Quickstart guide to complex Treasury Operations references. You determine how we version, layer, and present information so it does not collapse under its own weight as the platform grows. You build it on docs-as-code infrastructure that engineers can contribute to. You measure documentation by whether it moves adoption, not by completeness for its own sake.
• Own the OpenAPI Workflow: Your first technical priority is aligning the OpenAPI spec to production reality. Then you implement and enforce a contract-first governance model where the spec is treated as a product contract, not a generated afterthought. Spec linters run in CI as merge blockers. OpenAPI updates are part of engineering's Definition of Done. Breaking changes are detected automatically and routed through a defined deprecation process. You sit in Product and Engineering reviews as the First User: if an API is too hard to explain in writing, it is too hard to use, and you have the authority to push back before code ships.
• Drive Developer Advocacy: You are the external voice of OpenFX inside the developer community and the internal voice of the developer inside OpenFX. You write technical content that earns developer trust: deep-dive blog posts on idempotency under retries, sample apps that demonstrate real cross-border payment flows, integration pattern guides for PSP, neo-bank, and treasury use cases. You build feedback loops that turn integration friction into product changes. As volume justifies, you represent OpenFX at developer-focused events, conferences, and partner enablement sessions. You are the reason developers choose OpenFX over a competitor whose docs they could not understand.
• Own Integration Triage: You are the technical front door for client integration questions during US business hours. You triage whether each issue is a documentation gap, an API design problem, or a code bug. You fix documentation gaps directly and route the rest to engineering with structured context. You build the repeatable onboarding playbook that turns one-off Slack threads into a scalable process. You partner with GTM, who owns the client relationship; you own the developer experience surface that surfaces during integration.

What Success Looks Like

• API Product Adoption: You own the adoption funnel from API key activation to first API call to first transaction to expanded endpoint usage. You instrument it, set the baseline, define the target, and drive the cross-functional work to move the number. This is the metric you are accountable for.
• Time to First API Call: Drops from around 3 days to under 15 minutes within 90 days. You own the Quickstart, code snippets, and onboarding tutorials that make this speed possible, and you advocate for the product changes needed to remove the rest of the friction.
• Instructional support tickets: reduced 40% within 90 days, with 42% of onboarding support requests as the baseline.
• Spec drift: no spec drift incidents that reach production. The OpenAPI spec stays aligned to production as the platform evolves.
• V1 Developer Portal: a public API doc portal (References, Guides, Changelog, sample apps) is live, searchable, and built on docs-as-code infrastructure. 100% of public endpoints have accurate request and response examples.
• Developer advocacy presence: a published cadence of technical content (deep-dive guides, sample apps, integration patterns) that builds developer trust and drives inbound adoption. Establish the baseline, grow it quarterly.
• DX roadmap: a written plan for SDK strategy, portal evolution, adoption analytics, and Agent Experience foundations and expansion (CLI, MCP)

Requirements

• 5+ years owning a developer-facing API product or platform. B2B or infrastructure. You drove a measurable adoption outcome, not just shipped pages. You can point to the integration experience you built, the funnel you owned, and the metric you moved.
• Direct client integration work. You have sat on integration calls with B2B or institutional clients, diagnosed friction live, and fed it back into product changes (not just documentation updates). You know what breaks during real integrations, not what should break in theory.
• Product instinct for API design. You have opinions on endpoint design, parameter naming, authentication UX, error response formats, idempotency keys, and SDK ergonomics. You have opinions on these calls and get changes shipped before code hits production.
• Engineering fluency. You read code well enough to extract logic independently. You understand distributed system concepts (latency, rate limiting, idempotency, eventual consistency, async patterns). You can sit in a code review and have something useful to say.
• Contract-first governance experience. You have implemented or enforced OpenAPI workflows where the spec is treated as a product contract, not a generated artifact.
• Financial services or fintech context. You know the difference between authorized and settled. You have worked on payments, trading, or banking APIs.
• Agent Experience instinct. You have shipped or experimented with MCP servers, agent-native SDKs, llms.txt, evaluation suites for LLM-driven API consumption, or other agent-readable API patterns. You have a point of view on what Developer Experience looks like when AI agents are first-class consumers.

Preferred

• Interactive docs experience: code playgrounds, Try It Now, in-browser sandbox.
• Multimedia documentation skills: video tutorials, sequence diagrams, architecture diagrams that complement written documentation.
• Developer advocacy or DevRel experience: you have written technical content for an external developer audience, shipped sample apps, or represented a product at developer events.

Why This Role?

• Foundational Ownership: You are the first hire in this function. You define the hiring standards, the voice, and the culture of Developer Experience at OpenFX. As the function scales, you lead the team.
• Greenfield Architecture: You are building the DX product from the ground up. You build the system right the first time, selecting the stack, the taxonomy, and the governance model from scratch.
• The Frontier of Finance: You will learn the inner workings of global finance (FX liquidity, settlement, treasury), and you will apply them to the new payment stack as well as the legacy rails of the past. Our technology is novel; you teach developers how to think about the future of money and define the vocabulary of the industry. 
• Where This Role Grows: The next milestone is Agent Experience. AI agents are becoming first-class consumers of APIs alongside human developers. As Developer Experience matures, you lead the expansion into agent-native tooling: MCP servers that expose OpenFX as agent-callable tools, SDKs and CLIs designed for both human and autonomous consumption, semantically structured documentation that LLMs can parse natively, evaluation suites that test whether agents can invoke OpenFX correctly from natural language, and sandboxing patterns that let agents transact safely. Few companies have a clear owner for what Agent Experience means at the API layer. You define this discipline at OpenFX, and you do it from a foundation of human Developer Experience that already works.
• The Team: You are joining a team of ex-Stripe, J.P. Morgan, and Kraken alumni.  We are backed by Accel, Atomico, M13, Northzone, Pantera, and we believe that our APIs are core to our product. 

• Serverless AI has clear product-market fit with measurable activation and retention metrics improving quarter over quarter.
• Multi-node jobs and autoscaling endpoints are shipped and adopted by customers running production workloads.
• Cold start time is reduced from 1-3 minutes to under 60 seconds for common workloads through a combination of product and infrastructure improvements you drove.
• Developer experience (CLI, docs, error messages, onboarding flow) sets the standard that developers expect from a next-generation AI cloud.
• At least 3 product decisions you made are directly attributable to customer conversations or data analysis you conducted.

• Co-own the Serverless AI product roadmap — Jobs, Endpoints, and DevPods — taking primary ownership of specific product areas while collaborating closely with the other PM on shared priorities and cross-cutting decisions.
• Write detailed, technically precise PRDs that engineering teams can execute against. Our PRDs specify CLI syntax, API contracts, state machines, and billing models — not abstract feature descriptions.
• Make build/buy/defer decisions on capabilities like autoscaling, multi-node orchestration, HTTPS termination, secret injection, and health checking based on customer signal and strategic priorities.

• Understand the full workload lifecycle: container image pull → VM provisioning → GPU attachment → workload execution → cleanup — well enough to identify bottlenecks and propose solutions.
• Evaluate technical trade-offs in areas like container cold start optimization (image caching, snapshot restore, warm pools), GPU scheduling and bin-packing, and storage mount performance.
• Work directly with engineers on architecture decisions for distributed training support, endpoint autoscaling policies, and fault tolerance mechanisms.
• Stay current on the fast-moving serverless GPU infrastructure space — new inference frameworks (vLLM, TensorRT-LLM, SGLang), container runtimes, orchestration approaches — and translate trends into product direction.

• Run customer discovery and feedback sessions with ML engineers and platform teams at AI startups and enterprises. Turn qualitative insight into specific product actions.
• Analyze usage data, activation funnels, and churn patterns to identify where users get stuck and what features drive retention.
• Track market dynamics, emerging technologies, and industry trends to inform product strategy and ensure Nebius stays ahead of where the market is heading.
• Define and iterate on pricing, packaging, and tier strategy for Serverless AI.

• Own the technical content strategy: quickstart guides, tutorials, reference architectures, and example workloads that reduce time-to-first-job.
• Partner with marketing on developer-focused campaigns, webinars, and conference presence.
• Work with Solution Architects and Sales to qualify serverless-fit opportunities and support technical evaluations.

• You have built, shipped, and iterated on infrastructure or platform products used by developers or ML engineers. Not consumer apps. Not dashboards. Infrastructure.
• You understand containers at a practical level — Docker, image registries, container runtimes, resource limits, networking. You've debugged why a container won't start, why GPU isn't visible inside it, or why a mount isn't working.
• You have working knowledge of GPU computing for AI/ML: what GPU types exist and when to use them, how training and inference workloads differ in resource requirements, what vLLM / TensorRT-LLM / Triton are and why they matter.
• You can read a CLI reference and know if it's well-designed. You've shaped developer-facing APIs, CLIs, or SDKs.
• You have run real customer discovery — not surveys, but technical conversations with engineers where you learned something that changed your product direction.
• You have 3+ years of product management experience in cloud infrastructure, AI/ML platforms, or developer tools.

• Ability to whiteboard a workload lifecycle (submit → schedule → provision → execute → cleanup) and identify failure modes at each step.
• Understanding of autoscaling trade-offs: scale-to-zero vs. warm pools, scaling metrics (queue depth, latency, utilization), cold start implications.
• Familiarity with inference serving concepts: batching, model loading, quantization, KV-cache management, multi-model serving.
• Understanding of distributed training concepts: data parallelism, model parallelism, communication overhead, checkpointing.
• Ability to reason about pricing models: per-second vs. per-request vs. per-token, and how pricing interacts with product architecture.

• Experience at a serverless or GPU cloud company.
• Hands-on ML engineering background — you've trained models, deployed inference endpoints, or built ML pipelines yourself.
• Experience with Kubernetes for ML workloads (Kubeflow, KServe, Ray Serve) and understanding of why many ML teams want to avoid it.
• Prior experience building a product from early stage to scale in a fast-growing market.
• Background in systems engineering, distributed systems, or site reliability engineering.

• You are more comfortable in a terminal than in a slide deck.
• You form strong opinions based on data and direct customer signal, and you update them when evidence changes.
• You are energized by building at pace — small team, fast-evolving product, big opportunity.
• You care about developer experience at the level of error messages, CLI flag naming, and documentation quality.
• You'd rather ship a smaller thing that works perfectly than a bigger thing that's mediocre.

About Nebius

Nebius AI is an AI cloud platform with one of the largest GPU capacities in Europe. Launched in November 2023, the Nebius AI platform provides high-end, training-optimized infrastructure for AI practitioners. As an NVIDIA preferred cloud service provider, Nebius AI offers a variety of NVIDIA GPUs for training and inference, as well as a set of tools for efficient multi-node training. 

Nebius AI owns a data center in Finland, built from the ground up by the company’s R&D team and showcasing our commitment to sustainability. The data center is home to ISEG, the most powerful commercially available supercomputer in Europe and the 16th most powerful globally (Top 500 list, November 2023).  

Nebius’s headquarters are in Amsterdam, Netherlands, with teams working out of R&D hubs across Europe and the Middle East. 

Nebius AI is built with the talent of more than 500 highly skilled engineers with a proven track record in developing sophisticated cloud and ML solutions and designing cutting-edge hardware. This allows all the layers of the Nebius AI cloud – from hardware to UI – to be built in-house, distictly differentiating Nebius AI from the majority of specialized clouds: Nebius customers get a true hyperscaler-cloud experience tailored for AI practitioners. We’re growing and expanding our products every day. 

If you’re up to the challenge and are excited about AI and ML as much as we are, join us!

We are seeking a Staff or Principal Applied AI Researcher to join a fast growing team building an agent native search platform - the web access layer for AI systems.

You can think of this as Google for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines.

We are designing how AI agents - not humans - retrieve, evaluate, and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval and ranking under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24 by 7.

This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production.

What you'll work on:

• Designing agent native retrieval systems optimised for machine consumption rather than human search UX
• Building systems where LLMs iteratively plan, query, refine, and reason over results
• Developing ranking and retrieval approaches for multi step, agent driven workflows under real world constraints

Your responsibilites:

• Drive applied research and technical direction across retrieval and ranking systems
• Design and evolve multi stage retrieval architectures (query understanding, rewriting, reranking, iterative retrieval)
• Develop methods for grounding LLMs in real time web data at scale
• Define and implement new evaluation paradigms and metrics for agentic systems, where correctness is not reducible to clicks
• Lead experimentation on modern retrieval approaches (embeddings, hybrid search, reranking) and bring them into production
• Analyse trade-offs across relevance, latency, and cost at scale
• Work closely with engineering to deploy systems in high throughput, low latency environments
• Own ambiguous problems end to end and contribute to product and research direction
• Mentor engineers and help raise the technical bar of the team

Must haves:

• 8+ years of experience in applied AI, ML, or software engineering
• Proven track record of shipping ML or AI systems to production at scale
• Deep experience with search, retrieval, ranking, recommendation systems, or assistants
• Strong understanding of modern deep learning, especially transformers and embeddings
• Experience with LLM integrated or knowledge intensive systems
• Experience designing evaluation frameworks and metrics for ML systems
• Strong programming skills in Python and at least one of Go, C++, or similar
• Ability to operate in a fast moving, product driven environment with high ownership and autonomy

Nice to haves

• Experience with large scale search or recommendation systems
• Background in agentic AI systems (agents, tool use, autonomous workflows)
• Experience with RAG, multi step retrieval, or tool use
• Publications, open source, or similar signals of technical depth and impact

The role

This role is for Nebius AI R&D, a team focused on applied research in AI. Examples of applied research that we have recently published include:

• applying reinforcement learning for agent training in long-context multi-turn scenarios
• dramatically scaling task data collection to power reinforcement learning for SWE agents
• building a decontaminated evaluation for SWE agents that is regularly updated
• investigating how test-time guided search can be used to build more powerful agents

The results often lead to collaboration with adjacent teams where our research findings are applied in practice.

We are currently looking for senior- and staff-level ML engineers to work on research in areas such as:

• Guided search and reinforcement learning for agentic systems
• Reinforcement learning for reasoning models
• Web-scale problem collection for training agents
• Efficient model distillation

Some examples of what your responsibilities might include are:

• Conducting experiments to figure out efficient ways to train a large language model on traces of interactions with various environments
• Exploring methods of guided generation and search in the trajectory space
• Coming up with ways to mine relevant data at web scale and figuring out efficient ways to use this data in model post-training
• Conducting experiments with different reinforcement learning configurations in verifiable domains
• Exploring methods to train AI agents on tasks with non-verifiable reward signals

We expect you to have:

• A profound understanding of theoretical foundations of machine learning and reinforcement learning
• Deep expertise in modern deep learning for language processing and generation
• Substantial experience with training large models on multiple computational nodes
• Strong software engineering skills (we mostly use python)
• Deep experience with modern deep learning frameworks (we use jax)
• Strong communication and leadership abilities
• Experience designing, executing, and analyzing machine learning experiments with proper statistical rigor
• Ability to formulate research questions, design experiments to test hypotheses, and draw meaningful conclusions from results
• Ability to document research findings clearly and contribute to technical publications or report

Nice to have:

• Experience with deep reinforcement learning for LLMs, including techniques such as reward modeling, DPO, PPO etc
• Familiarity with important ideas in LLM space, such as RoPE, ZeRO/FSDP, Flash Attention, quantization
• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field Master’s or PhD preferred
• Track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment
• Experience in engineering complex systems, such as large distributed data processing systems or high-load web services
• Open-source projects that showcase your engineering prowess
• Excellent command of the English language, alongside superior writing, articulation, and communication skills
• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing

We are seeking a Senior Applied ML Engineer to join a fast-growing team building an agent-native search platform for AI systems, the emerging web access layer for AI. You will develop and deploy machine learning models that power retrieval, ranking, and indexing at scale, helping AI systems access fresh, reliable information in real time. This is a high-impact role working on a production system used 24x7, tackling challenges comparable to large-scale web search.

Your responsibilities:

• Design, train, and deploy ML models for retrieval, reranking, and search relevance in production
• Build and optimise embedding-based indexing and large-scale retrieval systems
• Develop models supporting crawling, data selection, and content understanding
• Define and improve quality metrics for agent-native search and build evaluation pipelines
• Work on systems operating at very large scale, including high-throughput query workloads
• Collaborate closely with engineering teams to integrate ML models into production services
• Analyse performance trade-offs across latency, quality, and cost
• Experiment with and apply state-of-the-art techniques in search, retrieval, and LLM-integrated systems
• Contribute to product and architectural decisions in a fast-moving environment

Must-haves:

• 5+ years of experience in software engineering or applied machine learning
• Strong programming skills in Python, Go, or C++
• Proven experience deploying ML models in production systems
• Hands-on experience with retrieval, ranking, recommendation, or similar ML problems
• Strong understanding of machine learning and modern deep learning techniques
• Experience working with large-scale data systems and high-throughput environments
• Ability to design evaluation frameworks and define meaningful model metrics
• Product-oriented mindset with a focus on impact and iteration
• Strong problem-solving skills and ability to work in a distributed team

Nice-to-haves:

• Experience with search systems or large-scale information retrieval
• Familiarity with embeddings, transformers, and modern NLP systems
• Experience working on LLM-powered or agent-based systems
• Contributions to open-source projects, technical publications, or conference talks
• Participation in competitive ML (e.g. Kaggle) or similar signals of strong technical ability

We conduct coding interviews as part of the process.

The role

We’re looking for a Software Engineer with strong C++ expertise to join the team building and operating Nebius Data Platform — a distributed storage and a processing platform that acts as the company’s “source of truth” and the backbone of many internal (and some external) products.

Nebius Data Platform is a single multi-tenant ecosystem based on YTsaurus — instead of running separate HDFS/Kafka/HBase-style systems, we provide storage, compute, and analytics capabilities inside one platform.

Built on top of the open-source YTsaurus ecosystem, we run and extend our own Nebius distribution and develop significant in-house functionality (core and platform-level). We can design, implement, and roll out features end-to-end on our clusters without waiting for upstream approvals and contribute upstream when it makes sense.

At scale today, this includes~500 servers, ~20k CPU cores and ~10 PB of compressed data in our largest production cluster, supporting workloads ranging from business-critical pipelines and financial transactions to large-scale ML/LLM training datasets and compute.

What’s inside the platform

You’ll work on a system that includes (and ties together):

• Distributed Storage (Cypress): transactional semantics, tiered storage, erasure coding, replication, and strong reliability expectations.
• Compute & ETL: a cluster-wide job scheduler (tens of thousands of cores), MapReduce, YQL for SQL-like data processing, and SPYT (Spark over YTsaurus) for modern data engineering.
• Interactive analytics (CHYT): ClickHouse® instances spun up directly on compute nodes for fast SQL over data in-place.
• Dynamic Tables: low-latency NoSQL KV with distributed ACID transactions for OLTP-style workloads and feature stores.
• Orchestracto: workflow orchestration deeply integrated with the platform (Airflow-like, but platform-native).

What you’ll do

We’re looking for engineers who combine strong systems skills with product sense: understanding who uses the platform, why certain capabilities matter, and making pragmatic trade-offs to maximize impact. On our team, engineering work is expected to be connected to real users and outcomes — you’ll regularly align with internal stakeholders, clarify requirements, and help drive prioritization.

In this role, you will:

• Design and implement new functionality in YTsaurus core (C++) with production reliability in mind.
• Build and evolve platform-level capabilities: platform architecture and operating model—multi-cluster growth, shared primitives, and a consistent experience that scales with new teams and use cases.
• Improve end-to-end platform experience for internal (and external-facing) users: APIs, guardrails, debugging workflows, and automation.
• Own production quality: incident response / on-call rotation, root cause analysis, and turning learnings into durable fixes.

Example projects

• Roll out sharded YTsaurus masters (incl. Kubernetes operator support) and build automatic balancing of metadata across master cells (consensus groups) to remove control-plane bottlenecks and unlock 10–100x cluster growth.
• Make CHYT interactive SQL faster and more predictable at high load via performance work like data-skipping / min-max-style indexes and improved execution introspection.
• Turn Orchestracto into a platform product by defining the building blocks, developer experience, and governance for how teams create and share workflows.
• Scale and harden Parquet-on-S3 for native YTsaurus workloads by tackling replication/movement, consistent lifecycle semantics, and master-server metadata optimizations for performance and reliability.
• Design and ship complete, trustworthy audit trails for data changes (who/what/when) across heterogeneous storage and compute paths.

Tech stack

• Core: modern C++ (C++20, async + multithreaded primitives)
• Services & tooling: Go and Python (microservices, utilities, integration tests)

What we expect

• 5+ years of software engineering experience.
• Strong C++ skills (you’ll write core code).
• Working knowledge of Python and/or Go (you don’t have to be expert, but should be comfortable navigating them).
• Experience developing and/or operating high-load, distributed services.
• Production mindset: ability to use SSH, read logs/metrics/traces, and debug distributed systems behavior.
• Solid CS fundamentals: algorithms, data structures, concurrency basics.

Nice to have

• Experience with Big Data systems (YTsaurus/Hadoop/Spark/ClickHouse/Kafka-like ecosystems).
• Experience with multi-tenant platforms, schedulers, resource isolation, quotas, and reliability engineering.
• Strong performance engineering skills (profiling, lock contention, latency/throughput tradeoffs).

We conduct coding interviews as part of the process.

• 5+ years of experience in technical recruitment, with a strong focus on senior-level hiring.
• Proven track record hiring in AI/ML, LLMs, Inference, distributed systems, HPC, infrastructure, GPU engineering, or related areas.
• Strong sourcing expertise and deep understanding of modern engineering roles, tech stacks, and motivations of senior candidates.
• Ability to operate autonomously in a fast-moving environment, balancing multiple complex searches.
• Excellent communication, stakeholder management, and analytical skills.
• Curiosity, creativity, and the ability to translate complex technical requirements into effective sourcing strategies.

The role 

Nebius Token Factory is a next-generation platform for LLM inference and deployment. It gives companies and developers access to dozens of state-of-the-art open-source models (LLMs, Vision, Embeddings, Image Generation) with enterprise-grade guarantees, including private endpoints, zero-retention data flow, transparent pricing, and easy scaling without GPU ops overhead.

Token Factory is part of Nebius, a company building next-generation cloud infrastructure for the global AI economy, helping teams solve real-world problems and scale AI without massive infrastructure costs or large in-house ML teams.

We are looking for a strong Product Designer  who will help turn complex AI infrastructure into a clear, controllable, and thoughtfully designed product for a professional audience. In this role, you’ll work on one of the most technically advanced AI products on the market, immerse yourself in modern LLM and AI infrastructure operating at production scale, and have real influence on UX and product decisions across core user scenarios.

You’re welcome to work in our offices in Amsterdam, Berlin, London or Prague with a hybrid work schedule.

Your responsibilities will include: 

• Designing clear, scalable interfaces for core end-to-end AI workflows: model selection and comparison, deployment and inference, inference observability and analysis, fine-tuning, dataset management, batch inference, and agent configuration.
• Own the end-to-end design of services and features within the Nebius Token Factory, from discovery to delivery.
• Being ready to write high-quality interface copy — clear, precise text that helps users navigate complex scenarios and make informed decisions.
• Developing a deep understanding of how AI systems work under the hood, translating complex technical processes (fine-tuning, data pipelines, agent workflows) into clear and manageable user interfaces.
• Collaborating with product managers to formulate hypotheses, validate them with data and user feedback, and improve key product scenarios.
• Using modern AI tools as part of the design process across research, ideation, and prototyping stages (Figma Make, Cursor, lovable.dev, ChatGPT, Claude, etc.).
• Working closely with product, engineering, and ML teams — discussing, revisiting, and improving solutions based on feedback and shared understanding.
• Clearly present design solutions and rationale to cross-functional teams
• Contribute to the development and maintenance of the design system, ensuring consistency and quality across the product  

We expect you to have: 

• 5+ years of experience in product teams (SaaS / B2B / DevTools experience is a strong plus). Strong product thinking and the ability to turn complex processes into clear and transparent user journeys.
• Experience working on technically complex products where understanding system logic and processes matters as much as UI. Ability to balance usability, consistency, and innovation in complex systems.
• Willingness to dive into the AI domain: how datasets are prepared for fine-tuning, how fine-tuning works, how agents and their workflows are structured.
• Openness to collaboration: ability to listen, argue constructively, and incorporate team feedback.
• Interest in UX research and a clear understanding of its value for product decisions.

It will be an added bonus if you have: 

• Experience with AI products, ML platforms, or developer tools.
• Understanding of API-first products.
• Experience designing enterprise-grade interfaces.
• Interest in product architecture and how systems work “under the hood.”

The role

Token Factory is a part of Nebius Cloud, one of the world's largest GPU clouds, running tens of thousands of GPUs. We are building a high-performance inference and fine-tuning platform designed to push foundation models to their hardware limits. Our mission is to maximize throughput, minimise latency, and optimise cost-per-token across tens of thousands of GPUs.

Some directions we are currently working on, and which you can be a part of:

• Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. Squeezing the maximum performance for a wide range of LLM architectures at scale (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-5).
• Inference engines support: Implement novel speculative decoding architectures, optimise components of various LLM designs (dense/MoE, autoregressive/parallel), and contribute to open-source inference engines.
• Low Precision Training & Inference: Design and productionise low-precision (FP8, NVFP4/MXFP4) training and inference pipelines with measurable gains in throughput and cost-efficiency.

We expect you to have:

• A profound understanding of theoretical foundations of machine learning and transformer architecture.
• Experience profiling GPU workloads using Nsight, PyTorch profiler, or similar tools
• Understanding of GPU memory hierarchy and compute/memory tradeoffs
• Familiarity with important ideas in LLM space, such as MHA, RoPE, KV-cache, Flash Attention, and quantisation
•  Understanding of performance aspects of large neural network training (sharding strategies, custom kernels, hardware features etc.)
•  Strong software engineering skills (we mostly use Python)
• Deep experience with modern deep learning frameworks
• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing
• Strong communication and leadership abilities

Nice to have:

• Experience working with open-source inference engines (vLLM, SGLang, TensorRT-LLM), including contributions
• Experience with kernel languages or DSLs such as Triton, Cute, CUTLASS, CUDA
• A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.
• Strong engineering skills, including experience in developing large distributed systems or high-load web services.
• Open-source projects that showcase your engineering prowess
•  Excellent command of the English language, alongside superior writing, articulation, and communication skills.

The Role

We are opening a 3–6 month Early Career program within our AI R&D team. You will work alongside experienced researchers to solve challenges in LLMs, reinforcement learning, and agentic systems.

We are looking for Early talents to support research in:

• Reinforcement learning for agents and reasoning models
• Building reinforcement learning environments
• Efficient model distillation and evaluation

Your responsibilities will include:

• Assist in designing and running experiments to train LLMs and speculators for them
• Help analyze experimental results and document findings
• Write and maintain code for data mining, processing, and model evaluation
• Collaborate with the team to explore new methods in the selected research direction
• Participate in technical discussions and discuss future steps of research
• Advanced methods for efficient speculative decoding
• Inference optimization techniques

We expect you to have:

• Strong knowledge of computer science and machine learning fundamentals
• Experience with Python and familiarity with deep learning frameworks
• Ability to write clean, efficient code
• Strong problem-solving skills and a willingness to learn quickly
• Good communication skills in English
• Permitted to work in the job’s location

Nice to have:

• Previous experience with NLP/reinforcement learning/AI agents projects
• Familiarity with current LLM concepts
• Enrollment in or completion of a degree in Computer Science, AI, or a related field
• Contributions to open-source projects

What we offer

• Competitive salary and comprehensive benefits package
• Mentorship from experienced AI, ML, and cloud infrastructure professionals
• Hands-on experience with real customer workloads and production systems
• Remote work flexibility and a collaborative, supportive team environment
• Opportunity to be considered for a full-time role after the Early Talent Program

We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us!

The opportunity
At Unity, we’re fostering a culture built on Empathy, Respect, and Opportunity. We are looking for a Staff Product Manager of AI Solutions & Strategic Enablement to lead the orchestration of AI across our enterprise. This isn't just about building applications; it’s about defining the framework, governance, and integration strategies that allow AI to transform how Unity operates.
This strategic lead sits at the heart of the Enterprise AI team with a company-wide remit. You will act as the bridge between cutting-edge technical capabilities and high-value business outcomes, reporting directly to the Senior Manager of Strategy and Execution. You will navigate the complex intersection of Engineering, IT, Security, Legal, and Finance to ensure AI isn't just a "feature," but a scalable business lever.

What you'll be doing

• Architect the AI Portfolio: Instead of managing a single product, you will curate a portfolio of AI-enabled solutions, ensuring they align with Unity’s overarching business objectives and provide a cohesive user experience across departments.
• Drive Business Transformation: Work with cross-functional leaders to identify high-friction business processes and design AI-driven interventions. You will define the ROI frameworks and success metrics that justify AI investment.
• Enablement & Governance: Partner with Security, Legal, and IT to build the "Golden Path" for AI adoption—creating the standards, guardrails, and shared capabilities that allow teams to deploy AI safely and efficiently.
• Strategic Interfacing: Act as the primary translator between technical ML teams and business stakeholders. You will translate complex technical constraints into business risks and opportunities.
• Lead Through Influence: Direct the roadmap for shared AI infrastructure and internal "platforms" that enable other teams to build their own solutions, ensuring we aren't reinventing the wheel in silos.
• Evangelism & Change Management: Articulate a compelling vision for the "AI-augmented workplace." You will lead the communication strategy to ensure new capabilities are understood, adopted, and iteratively improved based on real-world business impact.

What we're looking for

• 6+ years of Product/Program Management experience, with at least 3 years focused on AI/ML or complex platform ecosystems. You have a track record of moving needles on business-wide metrics, not just shipping features.
• Systems Thinker: You understand the "Big Picture." You can see how a change in data infrastructure impacts Legal compliance, which in turn affects the end-user experience.
• Strategic Technical Fluency: Deep understanding of the LLM lifecycle (fine-tuning, RAG, prompt engineering, latency/cost trade-offs) and how these technologies integrate into enterprise tech stacks.
• Master of Influence: Proven ability to drive alignment in "dotted-line" environments. You can mediate between a developer’s desire for technical excellence and a business leader’s need for rapid ROI.
• Business Acumen: Experience building business cases for emerging tech, managing vendor relationships (OpenAI, Anthropic, etc.), and navigating the build-vs-buy-vs-partner matrix.

You might also have

• Experience in Management Consulting or Internal Strategy: A background in high-level organizational problem-solving.
• Operational Excellence: Experience scaling internal platforms or centers of excellence (CoE) within a global SaaS environment.
• A "Solution Architect" Mindset: You enjoy the challenge of making disparate systems talk to each other to solve a human problem.

Additional information

• Relocation support is not available for this position.
• Work visa/immigration sponsorship is not available for this position

Life at Unity

Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit www.unity.com.

Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.

Your privacy is important to us. Please take a moment to review our Prospect and Applicant Privacy Policies. Should you have any concerns about your privacy, please contact us at DPO@unity.com.

#SEN

CX Services Program Manager

Product Domain  |  Premium · Ultimate · DAP & AI Adoption

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.

An overview of this role

As a CX Services Program Manager on the CX Services Portfolio team, you will own the complete customer journey for one of GitLab core product areas — Premium, Ultimate, or the GitLab Duo Agent Platform (DAP). That means owning the customer journey from how we guide customers from their first touchpoint all the way through deep platform adoption, paying careful attention to how we serve customers across every service capacity: scaled and digital motions (free resources, community, self-serve), Customer Success Tiers, Professional Services engagements, and Education and Training offerings. You will design, manage, and enable the services that move customers forward at every stage of that journey.

This is a role that sits at the intersection of product thinking, service design, and cross-functional influence. You do not deliver customer engagements — you build the offerings, frameworks, and enablement that allow GitLab PS, CS, and AE teams to do so at scale. You will act as the product manager for your product area tooling and collaborate on requirements with the CX Engineering Platform team, helping shape the CX Services Roadmap.

We expect everyone on this team to work with an AI-forward mindset — and we mean that in two directions. First, you will use AI actively in your own daily work: synthesizing research, drafting offer frameworks, writing requirements, and building enablement materials faster than would otherwise be possible. We are not looking for people who are curious about AI in theory. We want people who are already inside it — who have developed opinions about which tools work best for which tasks and can point to specific workflow changes that have made a real difference. Second, because we are designing services to help enterprise customers adopt AI at scale, the best people for these roles are the ones who understand that transformation firsthand.

You will partner with stakeholders at every level of the organization — from individual contributors in the field who deliver your services day-to-day, through to a cross-functional group of leaders shaping the CX Services Roadmap. The ability to communicate clearly and credibly across that full range is as important as the ability to design a great service.

This role reports to the Sr. Manager, CX Services Team.

What you'll do

• Own the end-to-end service portfolio for your assigned product area — offer design, pricing, BOM standards, lifecycle management, field enablement, and sunset decisions
• Map and continuously refine the complete customer journey for your product area, defining how customers are guided across scaled digital motions, Customer Success Tiers, Professional Services, and Education and Training
• Define measurable customer outcomes and value anchors for each offering, ensuring every service can clearly articulate what success looks like and how it is verified
• Act as product manager for your product area tooling requirements into the CX Engineering Platform team — writing requirements, reviewing prototypes, managing a backlog, and conducting UAT
• Partner with PS Engineers, Customer Success, Project Managers, and Solution Architects to gather field input and translate it into refined or net-new service offerings
• Build and maintain relationships with stakeholders across the full organizational range — from PSEs and CSMs who deliver your services in the field, through to VP-level PS and CS leadership and C-suite executives
• Collaborate with your peers across the CX Services Portfolio team to design consistent customer experiences and ensure services are properly sequenced across the customer lifecycle
• Create and maintain field enablement materials — playbooks, objection handling guides, Highspot pages, talk tracks, and training sessions — for CSMs, CSAs, PSEs, and AEs
• Use AI tools actively in your daily workflow to accelerate research, drafting, synthesis, and requirement writing — and contribute what you learn to the team shared AI practice
• Track service performance data including utilization rates, margin, and customer outcome achievement, and use insights to drive continuous portfolio improvement

What you'll bring

• 7+ years of experience in professional services, customer success, solutions architecture, or product management at a SaaS company
• Demonstrated experience designing or managing service offerings — not just delivering them. You have written a scope of work, defined pricing, and built a delivery kit
• Strong understanding of DevOps, application development, SDLC, or security domains — you do not need GitLab product knowledge on day one, but you need the technical foundation to develop it quickly
• Technical depth sufficient to design credible services. You do not need to have delivered these engagements yourself, but you need to understand them well enough that the practitioners who do will trust your judgment
• Deep familiarity with AI/ML engineering workflows, LLM capabilities, and agentic systems — and the organizational change management required for enterprise AI adoption
• A demonstrated AI-forward working style — you actively use agentic coding and AI tools as part of your daily workflow. You have formed opinions about how these tools change the way you work, and you can walk us through a specific workflow you have built or discovered that materially changed your output quality or speed
• Proven ability to build trust and communicate effectively across the full stakeholder range — individual contributors, managers, directors, VPs, and C-suite — in a remote, async-first environment
• Commercial acumen: fluency in how professional services and subscription services are priced, packaged, and sold in an enterprise context
• Strong written communication skills: you can produce crisp executive summaries, clear requirements, and field-ready enablement materials without extensive editing

About the team

The CX Services Portfolio team sits within CX Engineering at GitLab. We are responsible for designing, enabling, and optimizing the service offerings that help customers achieve business outcomes across GitLab three modernization journeys: AI, Security, and DevOps. We do not deliver customer engagements directly — we build the frameworks, offerings, and enablement that allow our CSM, CSA, PSE, and AE teams to do so at scale. We work in close partnership with the CX Engineering Platform team, for whom we act as product managers, and with delivery organizations across Professional Services, Customer Success, and Education Services.

How GitLab will support you

• 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
• Home office support

Hiring process

• TEXT

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.

An overview of this role

As a Staff Backend Engineer (Python) on the Duo Chat team in AI Engineering, you'll lead the backend architecture that powers GitLab Duo Chat across the GitLab DevSecOps platform. You'll solve hard problems in building reliable, secure, and scalable AI-powered chat workflows so customers can plan, write, review, and secure code faster, with confidence. This is a hands-on technical leadership role where you'll set direction for how we integrate and evolve large language model providers (including Google Vertex AI) across Ruby on Rails and Python services, raise the bar on observability and testing, and guide the team through ambiguous, high-impact technical decisions. Over your first year, you'll be expected to drive key architectural choices, reduce technical debt that slows iteration, and help the team ship durable improvements to response quality, reliability, and maintainability.

Some examples of our projects:

• Integrate new generative AI models and providers into GitLab Duo Chat to expand capabilities and improve response quality
• Improve debugging, observability, and test coverage for AI-powered chat workflows to increase reliability at scale

What you'll do

• Define the technical architecture and technical roadmap for the Duo Chat group, aligning backend execution with product direction and engineering priorities
• Solve the highest-scope and most ambiguous backend problems, delivering secure, well-tested, performant solutions with minimal guidance
• Integrate and extend generative AI capabilities in GitLab Duo Chat, including large language models (LLMs) and providers such as Google Vertex AI
• Develop, ship, and maintain backend features across Python and Ruby on Rails services that power Duo Chat experiences across the GitLab platform
• Design, implement, and review GraphQL application programming interface (API) contracts and supporting backend logic to ensure reliability, scalability, and clear frontend integrations
• Improve observability, debugging workflows, and incident readiness by strengthening logging, tracing, and production troubleshooting practices
• Drive code quality and long-term maintainability by setting internal standards, leading code reviews, and identifying and reducing technical debt
• Mentor engineers across the team and participate in Tier 2 on-call rotations, contributing to root cause analysis and follow-up improvements to resiliency and testing (including RSpec)

What you'll bring

• Production experience building and operating backend services in Python, including background jobs, APIs, and data models
• Ability to define and evolve technical architecture by weighing trade-offs, selecting patterns and tools, and setting a clear technical direction for others to follow
• Experience setting and driving a technical roadmap in partnership with product and engineering stakeholders
• Proficiency designing and maintaining REST and/or GraphQL APIs with attention to scalability, maintainability, and backward compatibility
• Hands-on experience integrating large language models into applications, including prompt design and building features powered by generative AI
• Strong SQL skills and experience working with relational databases such as PostgreSQL, including efficient queries and data modeling
• Experience mentoring engineers through code review, architectural guidance, and shared standards, and communicating complex technical decisions in a clear, async-first way
• Comfort contributing in a mature codebase across Python and Ruby on Rails, with openness to learning and applying transferable skills from related technologies or domains

About the team

The Duo Chat team sits within GitLab's AI Engineering organization and is responsible for building and evolving GitLab Duo Chat, the AI-powered chat experience embedded across the GitLab DevSecOps platform. You'll work with a small, cross-functional group of backend, frontend, and AI specialists who collaborate asynchronously across time zones, using GitLab issues, merge requests, and documentation as the primary way of working. The team focuses on integrating and scaling generative AI capabilities (including providers like Google Vertex AI), improving reliability and performance, and strengthening debugging, observability, and testing workflows so customers can safely use AI to plan, write, review, and secure their code across GitLab.

An overview of this role

As a Senior Backend Engineer (AI) in the Verify stage at GitLab, you'll help shape and scale the core infrastructure behind GitLab CI. You'll play a key role in how we integrate AI into CI/CD workflows, working on features that improve performance, reliability, and usability for people running millions of CI jobs, from small teams to the largest enterprises.

AI is a top priority in the year ahead. In this role, you'll go beyond using AI tools — you’ll design, build, and iterate on AI-assisted and agentic CI experiences. You’ll help define and implement patterns for how we measure success, how we instrument behavior in production, and how we account for large language model limitations in real-world environments. You’ll also help integrate GitLab's Duo Agent Platform into CI workflows at scale, on a foundation that's fast, reliable, secure, and observable.

In this role, you will:

• Collaborate with Engineering, Product, and UX partners to refine priorities: where we can move faster, where we’re missing data, and where there’s whitespace to innovate.
• Contribute to defining what success looks like across our AI agents, ensuring we’re not just shipping, but learning from how features perform in production.
• Keep a close eye on the competitive landscape and emerging AI-native DevOps tools, helping us understand what it takes to keep GitLab CI best-in-class in an increasingly agentic world.

Examples of Agentic CI work we have planned for the upcoming year:

• AI Pipeline Builder, the foundational CI agent that auto-creates pipelines for new projects and serves as the launchpad for onboarding new CI users.
• Automate the Fix a Failing Pipeline flow at scale – from dogfooding on internal GitLab projects through to safe, controlled rollout for customers, solving real infrastructure and scalability challenges.
• Build the instrumentation and observability layer that makes agentic CI trustworthy — trigger volume dashboards, retry rates, cost safeguards — so we can measure what’s working, catch what isn’t, and iterate with confidence.
• Harden the CI pipeline execution infrastructure that these agents depend on: database access patterns, background processing, and job orchestration built to handle the additional load that AI-driven automation introduces at enterprise scale.

What you’ll do:

• Design, build, and operate backend features that make GitLab CI fast, reliable, and easy to use at scale.
• Implement AI-powered and agentic CI capabilities that integrate with GitLab’s Duo Agent Platform.
• Instrument, monitor, and improve CI systems using data, observability, and safe rollout practices.
• Write secure, well-tested Ruby on Rails code in our monolith, improving existing features while reducing technical debt.
• Collaborate cross-functionally with Product, UX, and Infrastructure, mentoring others and raising engineering standards across the Verify stage.

What you’ll bring:

• Strong Ruby on Rails backend experience in a large, production codebase.
• In-depth experience building and operating AI-powered backend features in production.
• A data- and observability-driven approach to diagnosing issues, improving reliability, and validating impact.
• Clear written and verbal communication, with a collaborative, mentoring mindset in a remote, async environment.
• Hands-on experience building, running, and debugging high-traffic production systems, ideally in CI, workflow orchestration, or adjacent infrastructure-heavy domains.Nice to have
• Experience with AI agents or agentic frameworks (for example, LangChain or similar technologies) and building agentic workflows in production environments.
• Strong PostgreSQL skills, including data modeling, query tuning, and scaling large tables through proactive performance investigation and remediation.

We're looking for a hands-on GenAI Team Leader to build and lead our GenAI engineering team. You'll drive execution of our conversational AI and agentic AI roadmap, managing a team of talented engineers while remaining hands-on yourself. This role requires both exceptional leadership skills and the ability to roll up your sleeves and solve complex technical problems. 

This role is a hybrid position. You must be in our London office two days a week. 

Your Impact: 

• Lead, mentor, and grow a team of 5-8 GenAI engineers, fostering a culture of technical excellence, innovation, and delivery 
• Drive end-to-end execution of conversational AI features that enable users to interact with Anaplan models through natural language 
• Oversee the development of agentic AI systems that can autonomously analyze data, generate insights, and execute planning workflows 
• Own the team's delivery roadmap, working closely with product management to prioritize features and manage technical trade-offs 
• Establish engineering best practices for GenAI development, including testing strategies, evaluation frameworks, and deployment patterns 
• Lead sprint planning, technical design reviews, and retrospectives to ensure consistent delivery velocity and quality 
• Collaborate with AI Solutions Architects to translate architectural vision into executable engineering plans 
• Build and maintain CI/CD pipelines for GenAI applications, including automated testing and prompt regression suites 
• Partner with platform teams to ensure AI features integrate seamlessly with Anaplan's core infrastructure 
• Manage technical debt, refactoring initiatives, and platform improvements while maintaining feature delivery momentum 
• Recruit and onboard top engineering talent, conducting technical interviews and building a diverse, high-performing team 
• Communicate progress, risks, and technical decisions to senior leadership and cross-functional stakeholders 

Your Qualifications

• Software engineering experience with experience leading engineering teams 
• Strong hands-on experience building and deploying GenAI applications in production 
• Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns 
• Experience with agentic frameworks and autonomous agent architectures 
• Proficiency in Python and modern software development practices (testing, code review, CI/CD) 
• Proven track record of delivering complex technical projects on time with high quality 
• Strong project management skills with experience using Agile/Scrum methodologies 
• Excellent communication and stakeholder management abilities 
• Demonstrated ability to mentor engineers and build cohesive, productive teams 
• Bachelor's degree in computer science or related field 

 Preferred Qualifications 

• Experience leading teams in fast-growing startups or enterprise software companies 
• Knowledge of financial planning, analytics, or business intelligence domains 
• Experience with RAG systems, vector databases, and semantic search 
• Familiarity with model fine-tuning, evaluation, and continuous improvement workflows 
• Background in distributed systems, microservices, or cloud-native architectures 
• Experience with TypeScript/React for full-stack AI applications 
• Track record of improving engineering velocity and team productivity metrics  

What Makes This Role Exciting 

• Lead a greenfield team building transformative AI capabilities from the ground up 
• Work on cutting-edge conversational and agentic AI technologies 
• Shape engineering culture and practices for Anaplan's AI organization 
• Join during a transformative phase as Anaplan embeds AI throughout its platform 

#LI-SP1

We're seeking a versatile Senior GenAI Engineer who can work across the full stack of GenAI applications, from model integration and prompt engineering to building intuitive user interfaces. You'll build production-ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills. 

Your Impact  

• Develop end-to-end GenAI features, including backend API services, model integration, model monitoring, evaluations, and deployments 
• Integrate and optimize LLMs for specific use cases in business planning, including prompt engineering and RAG implementation 
• Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language 
• Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics 
• Design and develop APIs that expose AI capabilities to Anaplan's platform and third-party integrations 
• Optimize model inference pipelines for performance, cost, and scalability in production environments 
• Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour 
• Collaborate with data scientists to productionize ML models and forecasting algorithms 
• Write comprehensive tests, including unit tests, integration tests, and prompt regression suites 
• Participate in code reviews, technical design discussions, and knowledge-sharing sessions 
• Stay current with GenAI research and tools, evaluating new models and techniques for potential adoption 

 Your Qualifications 

• Software engineering experience with a focus on ML/AI systems 
• Strong programming skills in Python, including experience with ML frameworks (PyTorch, TensorFlow, Transformers) 
• Experience building and deploying LLM-powered applications in production 
• Proficiency in front-end development with React, TypeScript, and modern web technologies 
• Understanding of RESTful API design, microservices architecture, and cloud infrastructure 
• Experience with prompt engineering, RAG systems 
• Strong foundation in ML fundamentals, including NLP, time-series analysis, or recommender systems 
• Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines 
• Excellent problem-solving skills and attention to detail 
• Bachelor's degree in computer science, Machine Learning, or related field 

Preferred Qualifications 

• Experience with GenAI frameworks (LangChain, LlamaIndex, Haystack, or similar) 
• Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models 
• Experience with model serving frameworks (vLLM, TensorRT, Ray) 
• Background in forecasting, planning, or analytics applications 
• Familiarity with Anaplan or similar enterprise planning platforms 
• Experience with A/B testing and experimentation frameworks for AI features 
• Contributions to open-source ML projects or research publications 
• Experience with model observability tools (LangSmith, W&B, MLflow) 

 What Makes This Role Exciting 

• Lead a greenfield team building transformative AI capabilities from the ground up 
• Work on cutting-edge conversational and agentic AI technologies 
• Build user-facing AI features that directly impact how businesses plan and make decisions 
• Experiment with the latest GenAI models and techniques 
• Collaborate with talented engineers, data scientists, and product designers 
• Solve unique challenges at the intersection of AI and enterprise software 
• Grow your skills in both ML engineering and full-stack development 

#LI-SP1

We're seeking a versatile Senior GenAI Engineer who can work across the full stack of GenAI applications, from model integration and prompt engineering to building intuitive user interfaces. You'll build production-ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills. 

This role is flexible in scope, and we welcome candidates at all experience levels. This role is a hybrid position and will require you to be in our Manchester office twice a week. 

Your Impact  

• Develop end-to-end GenAI features, including backend API services, model integration, model monitoring, evaluations, and deployments 
• Integrate and optimize LLMs for specific use cases in business planning, including prompt engineering and RAG implementation 
• Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language 
• Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics 
• Design and develop APIs that expose AI capabilities to Anaplan's platform and third-party integrations 
• Optimize model inference pipelines for performance, cost, and scalability in production environments 
• Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour 
• Collaborate with data scientists to productionize ML models and forecasting algorithms 
• Write comprehensive tests, including unit tests, integration tests, and prompt regression suites 
• Participate in code reviews, technical design discussions, and knowledge-sharing sessions 
• Stay current with GenAI research and tools, evaluating new models and techniques for potential adoption 

 Your Qualifications 

• Software engineering experience with a focus on ML/AI systems 
• Strong programming skills in Python, including experience with ML frameworks (PyTorch, TensorFlow, Transformers) 
• Experience building and deploying LLM-powered applications in production 
• Proficiency in front-end development with React, TypeScript, and modern web technologies 
• Understanding of RESTful API design, microservices architecture, and cloud infrastructure 
• Experience with prompt engineering, RAG systems 
• Strong foundation in ML fundamentals, including NLP, time-series analysis, or recommender systems 
• Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines 
• Excellent problem-solving skills and attention to detail 
• Bachelor's degree in computer science, Machine Learning, or related field 

Preferred Qualifications 

• Experience with GenAI frameworks (LangChain, LlamaIndex, Haystack, or similar) 
• Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models 
• Experience with model serving frameworks (vLLM, TensorRT, Ray) 
• Background in forecasting, planning, or analytics applications 
• Familiarity with Anaplan or similar enterprise planning platforms 
• Experience with A/B testing and experimentation frameworks for AI features 
• Contributions to open-source ML projects or research publications 
• Experience with model observability tools (LangSmith, W&B, MLflow) 

 What Makes This Role Exciting 

• Lead a greenfield team building transformative AI capabilities from the ground up 
• Work on cutting-edge conversational and agentic AI technologies 
• Build user-facing AI features that directly impact how businesses plan and make decisions 
• Experiment with the latest GenAI models and techniques 
• Collaborate with talented engineers, data scientists, and product designers 
• Solve unique challenges at the intersection of AI and enterprise software 
• Grow your skills in both ML engineering and full-stack development 

#LI-SP1

We seek a AI Software Engineer to join our AI infrastructure team. This team owns and operates a core service that runs AI-powered agents and their associated infrastructure, ensuring reliability, scalability, and ease of use for internal and external stakeholders. You’ll work across backend systems, front-end integration, and AI/ML workflows, with opportunities to expand your expertise in prompt engineering, Retrieval-Augmented Generation (RAG), and large language model (LLM) interactions.

Your Impact

• Design, build, and maintain services and infrastructure that manage AI-powered agents.
• Develop backend services in Python, with comprehensively tested and self-documented APIs.
• Work with Agentic AI frameworks and implement prompt engineering best practices to build scalable foundational platform.
• Work with relational databases (MySQL) to store, query, and optimize structured data.
• Collaborate with product and research teams to refine and implement the product roadmap.
• Support front-end teams using React/JS components and wrappers for AI-driven experiences.
• Learn, apply, and optimize RAG systems, including vector databases, embeddings, and document chunking strategies.
• Build a practical understanding of how large language models (LLMs) work and deepen expertise in effective interactions with LLMs for agent orchestration.
• Monitor, debug, and optimize system performance, ensuring high reliability in production environments.

Your Qualifications 

• Strong proficiency and experience working with Python-based services
• Hands-on experience with relational databases (MySQL or similar).
• Familiarity with React and ability to support front-end AI integrations.
• Basic understanding of large language models and eagerness to expand knowledge.
• Demonstrated interest or experience in prompt engineering and working with LLMs.
• Strong problem-solving, debugging, and collaboration skills.

Nice-to-Have

• Prior experience with vector databases (Pinecone, Weaviate, FAISS, etc.).
• Knowledge of retrieval-augmented generation (RAG) pipelines.
• Experience with AI/ML infrastructure or agent frameworks.
• Familiarity with cloud environments (AWS, GCP, Azure) and containerized deployments (Docker, Kubernetes).

^{Enterprises trust our conversational AI platform to automate millions of customer interactions every day. Your mission is to define the strategy and lead the product group responsible for the end-to-end Enterprise experience across Building, Supervising, and Multichannel Execution. This includes the foundational tooling for creating, configuring, and optimizing LLM-powered agents (Building Experience), the interface and controls for human supervisors and quality assurance teams (Supervisor Experience), and the market-leading experience across all text surfaces like Webchat, WhatsApp, Email, and SMS (Chat/Multichannel Experience). We are looking for an ROI focused and strategic Group PM to own the product success of these three critical pillars, driving market adoption, platform stability, and establishing a unified, world-class experience for our largest customers.}

^{You will lead, mentor, and align multiple product, design, and engineering teams, translating frontier Agentic AI into intuitive, trustworthy, and scalable enterprise solutions that solve core workflow challenges for Builders and Supervisors while ensuring seamless end-user experiences. If you are motivated by driving organizational alignment, solving complex, at-scale platform problems, and transforming product vision into commercial reality, we want to meet you.}

^{Key Responsibilities}

• ^{Define and Lead the Enterprise Platform Vision and Portfolio Strategy. Establish a winning product strategy and unified architecture across the three core areas: Building Experience, Supervisor Experience, and Chat/Multichannel Experience. Define, monitor, and report on key business and product success indicators, driving continuous improvement across the entire portfolio to maximize ROI for our enterprise clients.}

• ^{Own and Deliver the End-to-End Roadmap. Oversee the entire product lifecycle for the platform portfolio - from discovery and strategic prioritization to iterative development, launch, and optimization. Ensure all product initiatives are aligned with the overarching Enterprise business strategy.}

• ^{Drive Organisational Alignment and Thought Leadership. Serve as the principal bridge between executive strategy, complex customer needs, and technical execution across multiple product teams. Champion new technical breakthroughs to challenge and redefine the future of conversational AI platforms and workflows in the enterprise space.}

• ^{Product Ownership for Three Pillars:}

• ^{Building Experience: Define the features and tools that enable internal teams and customers to rapidly create, configure, test, and deploy high-quality, LLM-powered agents at scale.}

• ^{Supervisor Experience: Lead the development of tooling for human oversight, reporting, quality assurance, and intervention workflows to ensure compliance and maintain service quality.}

• ^{Chat/Multichannel Experience: Guide the strategy for extending and unifying the agent experience across all text surfaces (Webchat, WhatsApp, Email, SMS, etc.).}

• ^{Integrate and Optimize Core AI Technology. Direct product requirements and evaluation frameworks to ensure our underlying LLM, RAG, and tool-calling pipelines are optimized for all platform components, driving consistency, quality, and performance at an enterprise scale.}

• ^{Lead Go-to-Market Strategy for Enterprise. Direct Go-to-Market collaboration, including the coordination of beta programs, launch kits, and pricing/packaging, to drive rapid rollout and platform adoption.}

• ^{Develop and Mentor Product Talent. Provide leadership, guidance, and mentorship to a team of Product Managers, fostering a high-performing, data-driven culture focused on maximum business impact.}

^Requirements

• ^{8+ years of Product Management experience, with a minimum of 3 years managing, mentoring, and leading a team of Product Managers across different product lines.}

• ^{Proven experience driving the product lifecycle for multiple, interconnected B2B or Enterprise SaaS products at scale.}

• ^{Exceptional ability to use qualitative customer insights and quantitative business data to define, validate, and evolve a portfolio-level product strategy.}

• ^{Demonstrated track record of being ROI-driven, maximising the impact of resources across multiple teams to bring the most value for customers and the business.}

• ^{Superior communication skills, with the ability to articulate complex strategies and results to executive leadership, technical teams, and external customers.}

• ^{Strong technical background. A Bachelor’s or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience in software development and products.}

^{Preferred Requirements}

• ^{Experience working on a global B2B or Enterprise SaaS product with a significant international footprint.}

• ^{Previous experience as a Group PM or Director-level product leader.}

• ^{Experience defining, measuring, and moving quantitative success metrics for sophisticated conversational AI, contact center, or B2B ML/AI platform solutions.}

• ^{Familiarity with enterprise-grade platform components, including contact center/CRM integrations, supervisor and analytics tooling, and core conversational AI/NLP technologies.}

^Benefits

^{💰 Participation in the company’s employee share options plan}

^{🏝 Tenure-Based PTO: You will receive 25 holidays when you join and will gain an additional 1 day after 2 years of service, then 1 day each year until capped at 32 holidays}

^{🏡 Flexible working from home policy}

^{🌎 Work from outside of the UK for up to 6 months each year}

^{🫂TELUS Health EAP 24/7 - offers you and your chosen family confidential, judgment-free support for any work, health, or life challenge}

^{🧡 Enhanced parental leave}

^{🚲 Bike2Work scheme}

^{📚 Annual learning and development allowance}

^{🏡 We’re all about making WFH work for you - that’s why we offer a one-off WFH allowance when you join. Offering perks like noise-cancelling headphones or a comfortable desk chair to boost your comfort and focus!}

^{👨‍👩‍👧 Company-funded fertility and family-forming programmes}

^{🌸 Menopause care programme with Maven}

^{🏥 Private healthcare and dental cover, discounts on gym members and relaxation apps, and access to a range of mental health programs}

^{🌎 Sabbatical Program: 5-week paid sabbatical available after 5 years of employment}

The Community You Will Be Part Of: 

Airbnb, a leader in travel and hospitality, is on a mission to create a world where anyone can belong anywhere. We offer unique accommodations and experiences, crafted and curated by locals. As we expand into new marketplaces for in-person experiences and services, we are on the lookout for driven and innovative individuals to help shape our growth trajectory.

The Difference You Will Make:

This Advanced Analytics role will develop and lead initiatives focused on ensuring we have the right international growth strategy. They will lead measurement, build tools, and develop insights leveraging a wide range of internal and external data sources to ensure the business is making the right decisions for both strategic direction and tactical execution.

The ideal candidate is someone with a strong data and analytics background. This person is curious, engaged, positive, and detail- and solutions-oriented. The world— and thus our industry— is changing quickly so the ideal candidate will be comfortable with responding promptly and changing course as needed when priorities and reporting needs shift. 

This role will be expected to be highly collaborative, and work regularly with multiple stakeholders and cross functional partners across Regional Teams, Policy, Supply, Finance, Data Science, Operations, Engineering, and Marketing.

The right candidate will already be recognized as a leader in the data and analytics field at this level, with a proven track record of using a range of strategies and disciplines to solve complex and ambiguous measurement problems for business teams. This person will also use their considerable experience with data and insights storytelling to influence large-scale strategic programs, and  be adept at leveraging AI technologies to accelerate and raise their craft.

You must be comfortable working in a global company, delivering counsel and guidance to senior leadership across the team and organization. The successful candidate will have solid experience creating internal advocacy and influencing multiple senior audiences on hard to communicate topics.

The Team You Will Join: 

The Global Markets & Policy Advanced Analytics team is building the data infrastructure, measurement systems, and self-service tools that will power Airbnb's international growth in 2026 and beyond. This is a greenfield opportunity to shape how global teams make nimbler decisions, moving from HQ-dependent reporting cycles to fast, local, data-driven action.

This role will partner directly with Global Markets regional teams combined with Finance and Supply to surface local insights, build scalable tooling, and drive measurable impact on core business metrics. The ideal candidate brings deep technical rigor, strong business instincts, and a bias toward proactively building things—not just analyzing them.

A Typical Day:                    

• Build and maintain self-service analytics tools and dashboards that help country teams monitor performance and act on local signals                                    
• Partner with regional leads to translate business questions into clear analytical frameworks and actionable insights                                                    
• Support measurement for local marketing programs — campaign tracking, incrementality testing, and MMM contributions                                                     
• Analyze international market data to identify and size growth opportunities across supply, demand, and behavioral signals                                               
• Collaborate with Engineering, Marketing, and Research to deliver on data and tooling needs within shared roadmaps                                                       
• Provide analytical support for local growth levers (incentives, promotions, merchandising) including targeting and measurement                                                                                                                                         

Your Expertise:                                                                                                                                                                                                                                                                                                                                 

• 4+ years in data science, analytics, or business intelligence — marketplace, e-commerce, or global consumer tech preferred
• Expert SQL; proficiency in Python or R                                                                                                                             
• Hands-on experience with A/B testing, causal inference, and incrementality measurement                                                                                  
• Experience building self-service data products used by non-technical stakeholders                                                                                      
• Familiarity with international / multi-market analytics contexts                                                                                                        
• Strong data storytelling — able to communicate findings clearly to business and senior audiences                                                                        
• Collaborative, low-ego, and execution-oriented; you measure success by the decisions your work influences                                                               
• Comfortable with modern data stack tools (dbt, Airflow, Tableau, Looker, or equivalent)                                                                                                                                                                                          

Nice to Have:                                                                                                                                                             

• Supply/demand or geo-based analytics experience                                                                                                                         
• Growth marketing analytics (SEM, paid social, performance channels)
• Familiarity with MMM, attribution, or campaign measurement frameworks                                                                                                   
• Awareness of AI/LLM trends and implications for organic traffic and demand      

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

The Community You Will Be Part Of: 

Airbnb, a leader in travel and hospitality, is on a mission to create a world where anyone can belong anywhere. We offer unique accommodations and experiences, crafted and curated by locals. As we expand into new marketplaces for in-person experiences and services, we are on the lookout for driven and innovative individuals to help shape our growth trajectory.

The Difference You Will Make:

This Advanced Analytics role will develop and lead initiatives focused on ensuring we have the right international growth strategy. They will lead measurement, build tools, and develop insights leveraging a wide range of internal and external data sources to ensure the business is making the right decisions for both strategic direction and tactical execution.

The ideal candidate is someone with a strong data and analytics background. This person is curious, engaged, positive, and detail- and solutions-oriented. The world— and thus our industry— is changing quickly so the ideal candidate will be comfortable with responding promptly and changing course as needed when priorities and reporting needs shift. 

This role will be expected to be highly collaborative, and work regularly with multiple stakeholders and cross functional partners across Regional Teams, Policy, Supply, Finance, Data Science, Operations, Engineering, and Marketing.

The right candidate will already be recognized as a leader in the data and analytics field at this level, with a proven track record of using a range of strategies and disciplines to solve complex and ambiguous measurement problems for business teams. This person will also use their considerable experience with data and insights storytelling to influence large-scale strategic programs, and  be adept at leveraging AI technologies to accelerate and raise their craft.

You must be comfortable working in a global company, delivering counsel and guidance to senior leadership across the team and organization. The successful candidate will have solid experience creating internal advocacy and influencing multiple senior audiences on hard to communicate topics.

The Team You Will Join: 

The Global Markets & Policy Advanced Analytics team is building the data infrastructure, measurement systems, and self-service tools that will power Airbnb's international growth in 2026 and beyond. This is a greenfield opportunity to shape how global teams make nimbler decisions, moving from HQ-dependent reporting cycles to fast, local, data-driven action.

This role will partner directly with Global Markets regional teams combined with Finance and Supply to surface local insights, build scalable tooling, and drive measurable impact on core business metrics. The ideal candidate brings deep technical rigor, strong business instincts, and a bias toward proactively building things—not just analyzing them.

A Typical Day:                    

• Build and maintain self-service analytics tools and dashboards that help country teams monitor performance and act on local signals                                    
• Partner with regional leads to translate business questions into clear analytical frameworks and actionable insights                                                    
• Support measurement for local marketing programs — campaign tracking, incrementality testing, and MMM contributions                                                     
• Analyze international market data to identify and size growth opportunities across supply, demand, and behavioral signals                                               
• Collaborate with Engineering, Marketing, and Research to deliver on data and tooling needs within shared roadmaps                                                       
• Provide analytical support for local growth levers (incentives, promotions, merchandising) including targeting and measurement                                                                                                                                         

Your Expertise:                                                                                                                                                                                                                                                                                                                                 

• 4+ years in data science, analytics, or business intelligence — marketplace, e-commerce, or global consumer tech preferred
• Expert SQL; proficiency in Python or R                                                                                                                             
• Hands-on experience with A/B testing, causal inference, and incrementality measurement                                                                                  
• Experience building self-service data products used by non-technical stakeholders                                                                                      
• Familiarity with international / multi-market analytics contexts                                                                                                        
• Strong data storytelling — able to communicate findings clearly to business and senior audiences                                                                        
• Collaborative, low-ego, and execution-oriented; you measure success by the decisions your work influences                                                               
• Comfortable with modern data stack tools (dbt, Airflow, Tableau, Looker, or equivalent)                                                                                                                                                                                          

Nice to Have:                                                                                                                                                             

• Supply/demand or geo-based analytics experience                                                                                                                         
• Growth marketing analytics (SEM, paid social, performance channels)
• Familiarity with MMM, attribution, or campaign measurement frameworks                                                                                                   
• Awareness of AI/LLM trends and implications for organic traffic and demand      

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

What is The Role

Elastic is building Agent Builder, a conversational platform that connects production agents to real customer business data in Elasticsearch. As a Principal Engineer, you will set technical direction and drive the Kibana backend architecture for the agentic platform: streaming APIs, secure tool execution, session and memory persistence, retrieval and citations contracts, and evaluation telemetry. Your influence will extend beyond a single feature, shaping service boundaries, reliability posture, and standards that other solutions build on.

What You Will Be Doing

• Own the architecture for chat back-end services (Node/TypeScript), defining service boundaries, data contracts, and scalability targets
• Lead cross-team design reviews; author ADRs and RFCs that become reference standards for AI-chat and ingestion work.
• Build and harden event-driven pipelines that capture chat telemetry, evaluation traces, and LLM feedback loops; expose them via self-service analytics endpoints.
• Champion reliability—define error budgets, introduce testing strategy, and steer incident-response playbooks for conversational workloads.
• Mentor senior and Junior engineers; grow their system-design skills and foster a high-trust, low-ego culture.
• Partner with Product, Design, and Data Science to translate ambiguous goals (e.g., “multi-step reasoning with tool calling”) into incremental, testable action items.
• Represent Elastic in open-source AI communities (LangGraph/LangChain, MCP/A2A) through design proposals, blog posts, and conference talks.

What You Bring

• We appreciate articulate and “low ego” people who want to grow as part of a team.
• 10 + years building distributed, production SaaS services—at least 5 years leading large-scale Node/TypeScript or similar back-end stacks.
• Deep expertise in distributed systems fundamentals—shard routing, consensus, eventual consistency, back-pressure, and circuit-breaker patterns.
• Demonstrated success designing high-throughput, low-latency APIs (gRPC / REST / WebSocket)—including streaming responses and resumable sessions.
• Hands-on experience with observability: OpenTelemetry, log/metric pipelines, synthetic checks, and SLO dashboards.
• Exposure to LLM tooling (LangChain/LangGraph, OpenAI function calls, vector-search, RAG orchestration) and enthusiasm for advancing GenAI architectures.
• Clear, persuasive written communication—your ADRs and RFCs set the standard others emulate.
• Nice-to-have: contribution history to Kibana or other large SPAs; ability to prototype front-end dashboards when it unblocks back-end work.

If this sounds interesting, we would love to hear from you! Please include whatever info you believe is relevant: resume, GitHub profile, code samples, blog posts and writing samples, links to personal projects, etc.