production engineer

<div>
 This role is with one of Dex's trusted partner companies. We work closely with their teams to truly understand their culture, goals, and what they're looking for, so we can match you with the right opportunity and give you context about the role before you commit to a process.
 
 
 
 If you're interested sign up to Dex to apply.
 
 
 
 Dex is an AI recruiter agent that helps you run your job search. Tell Dex your stack, seniority, and what you want to build. We will manage your applications and surface other opportunities that are a fit.
 
 
 
 The role
 
 
 
 This company is building a privacy-first perception engine, turning existing cameras and sensors into real-time operational intelligence without facial recognition or hardware swaps. They're tackling a petabyte-scale data infrastructure challenge: ingesting and processing real-time feeds from thousands of customer sites. This isn't a typical SaaS reliability surface; think financial market data aggregation, but for the physical world.
 
 
 You'll be the founding engineer for a new Resilience function, owning the availability, performance, and scalability of this unique platform. This is a greenfield opportunity to apply a software engineering mindset to operations, designing systems from scratch. It's not about running a ticket queue; it's about building the infrastructure that makes petabyte-scale real-time data reliable.
 
 
 
 The work
 
 
 
 <ul>
 <li>
 Design, build, and operate a centralized, petabyte-scale data ingestion pipeline, solving novel reliability challenges akin to financial market data.
 </li>
 <li>
 Architect and implement production Kubernetes clusters and GitOps workflows from scratch, ensuring high availability and scalability.
 </li>
 <li>
 Automate manual operations work across deployment, monitoring, and incident response, embedding a software engineering approach into infrastructure.
 </li>
 <li>
 Define and manage SLOs/SLIs for critical systems, leading root cause analyses that result in tangible preventative changes.
 </li>
 <li>
 Establish and champion documentation standards (runbooks, post-mortems, system docs) as a core engineering deliverable.
 
 
 </li>
 </ul>
 
 What You Bring
 
 
 
 <ul>
 <li>
 You've built at least one production Kubernetes cluster from scratch, not just operated an existing one.
 </li>
 <li>
 You're fluent with GitOps workflows in production and have strong opinions on their optimal setup and operation.
 </li>
 <li>
 You write code to automate operations work across deployment, monitoring, and incident response.
 </li>
 <li>
 You've defined and managed SLOs/SLIs for production systems and led RCAs that resulted in preventative changes.
 </li>
 <li>
 You are eligible to work in the UK and ideally based in London.
 
 
 </li>
 </ul>
 
 Why apply through Dex
 
 
 
 This is a rare, high-impact role that won't be widely advertised. Apply through Dex to get properly briefed on the company and role, skip the cold application process, and get matched to other similar, unlisted opportunities. We help you cut through the noise and find the roles that truly fit.
 
 
 If you're interested, sign up to Dex to apply - https://jobs.meetdex.ai/jobs/3dc041c8-3c13-4de2-b049-f756ab2bfdb0
 
 
 
 As part of the recruitment process at Dex, we process your personal data in accordance with our Privacy Notice for Job Applicants. This notice explains how and why your data is collected and used, and how you can contact us if you have any concerns.
 
 
 
 We review applications on a rolling basis, so early applicants are encouraged.
</div>

Site Reliability Engineer (up to £130k)

Soros Fund Management

<div>
 
 Company Overview
 
 
 
 Soros Fund Management LLC (SFM) is a global asset manager and family office founded by George Soros in 1970. With $28 billion in assets under management (AUM), SFM serves as the principal asset manager for the Open Society Foundations, one of the world&rsquo;s largest charitable foundations dedicated to advancing justice, human rights, and democracy.
 
 
 Distinct from other investment platforms, SFM thrives on agility, acting decisively when conviction is high and exercising patience when it&rsquo;s not. With permanent capital, a select group of major clients, and an unconstrained mandate, we invest opportunistically with a long-term view in a wide range of strategies and asset classes, including public and private equity and credit, fixed income, foreign exchange, and alternative assets. Our teams operate with autonomy, while cross-team collaboration strengthens our conviction and empowers us to capitalize on market dislocations.
 
 
 At SFM, we foster an ownership mindset, encouraging professionals to challenge the status quo, innovate, and take initiative. We prioritize development, enabling team members to push beyond their roles, voice bold ideas, and contribute to our long-term success. This culture of continuous growth and constructive debate fuels innovation and drives efficiencies.
 
 
 Our impact is measured by both the returns we generate and the values we uphold, from environmental stewardship to social responsibility. Operating as a unified team across geographies and mandates, we remain committed to our mission, ensuring a meaningful, lasting impact.
 
 
 Headquartered in New York City with offices in Greenwich, Garden City, London, and Dublin, SFM employs 200 professionals.
 
 
 
 Team Overview
 
 
 
 Reports To: Head of Cloud SRE &amp; DevOps Engineering
 
 
 Other Key Relationships: Cybersecurity analysts, Software Development engineers
 
 
 
 Job Overview
 
 
 
 We are seeking a mid-to-senior level engineer to join our Cloud SRE &amp; DevOps Engineering team in London, focused on building, operating, and evolving the cloud infrastructure and delivery platforms that support our trading and investment systems.
 
 
 This role sits at the intersection of Cloud Engineering, SRE, DevOps, Platform Engineering, and Production Engineering, and is designed for individuals who take ownership of systems running in production. You will be responsible for designing and operating resilient, scalable environments across AWS and Kubernetes, while enabling engineering teams through modern DevOps and GitOps practices.
 
 
 The position reflects a strong Site Reliability Engineering (SRE) mentality, with emphasis on reliability, observability, automation, and operational excellence. You will play a key role in advancing the firm&rsquo;s cloud transformation strategy, ensuring systems are built for performance, stability, and scale.
 
 
 This is a hands-on role requiring deep technical expertise, accountability for production systems, and a mindset oriented toward continuous improvement, risk management, and engineering efficiency. The role also contributes to evolving platform capabilities supporting AI and data-driven workloads.
 
 
 You will work closely with software engineering, cybersecurity, and data teams to deliver secure, scalable, and high-performing systems, while improving developer experience and platform maturity across the organization.
 
 
 
 Major Responsibilities
 
 
 
 Cloud Infrastructure &amp; Kubernetes
 
 
 Design, build, and operate scalable AWS-based infrastructure supporting trading systems
 
 
 Work across hybrid or multi-cloud environments (AWS and Azure)
 
 
 Manage and optimize Kubernetes environments (EKS), ensuring resilience, scalability, and performance
 
 
 Utilize Kubernetes ecosystem tooling (e.g., Helm) to support application deployment and lifecycle management
 
 
 Develop reusable infrastructure using Terraform and infrastructure as code principles
 
 
 Database Cloud Management &amp; Administration
 
 
 Manage the automated delivery of Snowflake configurations through CICD pipelines
 
 
 Help administration of Microsft SQLServer, Snowflake and AWS Aurora
 
 
 CI/CD &amp; DevOps Practices
 
 
 Design and maintain CI/CD pipelines using tools such as GitHub Actions
 
 
 Promote Git-based workflows and support GitOps practices (e.g., ArgoCD)
 
 
 Improve deployment reliability, consistency, and engineering velocity
 
 
 Production Engineering &amp; Reliability
 
 
 Own and operate business-critical production systems with a strong focus on uptime, performance, and risk mitigation
 
 
 Troubleshoot and resolve complex issues across distributed systems, cloud infrastructure, and Kubernetes environments
 
 
 Implement and enhance monitoring, logging, and alerting using tools such as Datadog, AWS CloudWatch, Geneos, and LogicMonitor
 
 
 Apply cloud security best practices, including IAM, secrets management, and vulnerability scanning
 
 
 Support and optimize relational database systems (e.g., PostgreSQL, MySQL, SQL Server, Aurora), ensuring performance and high availability
 
 
 Contribute to backup, recovery, and resilience strategies across infrastructure and data layers
 
 
 Drive improvements aligned with SRE principles, including reliability, observability, and operational maturity
 
 
 Developer Enablement
 
 
 
 Improve Developer Experience Through Automation, Standardization, And Self-service Capabilities
 
 
 
 Partner with engineering teams to streamline development and deployment workflows
 
 
 AI &amp; Emerging Workloads
 
 
 Support infrastructure for AI/ML and data-driven workloads, including scalable compute and data processing patterns
 
 
 Enable deployment patterns for modern, data-intensive applications
 
 
 Evaluate emerging technologies relevant to AI-enabled platforms
 
 
 
 What We&rsquo;re Looking For
 
 
 
 Core Technical Expertise
 
 
 Strong hands-on experience with AWS in production environments
 
 
 Experience working in hybrid or multi-cloud environments (AWS and Azure)
 
 
 Deep experience with Kubernetes and containerized systems (Docker, EKS)
 
 
 Strong familiarity with Kubernetes tooling, including Helm
 
 
 
 Proven Experience With Infrastructure As Code (Terraform Preferred)
 
 
 
 Strong experience building and managing CI/CD pipelines (GitHub Actions or similar)
 
 
 Proficiency in Python, Shell, or PowerShell for automation
 
 
 Production &amp; Systems Engineering
 
 
 Strong understanding of distributed systems, networking, and cloud architecture
 
 
 Experience operating and supporting production systems with high availability and performance requirements
 
 
 Experience diagnosing and resolving complex production incidents in distributed environments
 
 
 Experience supporting relational databases (e.g., PostgreSQL, MySQL, SQL Server, Aurora) in cloud environments
 
 
 Monitoring &amp; Observability
 
 
 Hands-on experience with observability tools such as Datadog, AWS CloudWatch, Geneos, or LogicMonitor (or comparable enterprise monitoring platforms), including designing metrics, alerts, and dashboards for production systems
 
 
 DevOps &amp; Engineering Practices
 
 
 Strong grounding in DevOps methodologies, including automation, continuous delivery, and infrastructure standardization
 
 
 Experience working with Git-based workflows and modern software engineering practices
 
 
 Ability to balance speed, stability, and risk in production environments
 
 
 Professional Attributes
 
 
 Strong analytical and troubleshooting skills
 
 
 Ability to operate effectively in high-performance, time-sensitive environments
 
 
 Clear communication across technical and non-technical stakeholders
 
 
 Ownership mindset with accountability for critical systems
 
 
 
 Nice To Have
 
 
 
 AI &amp; Data
 
 
 Experience supporting AI/ML workloads or data platforms
 
 
 Familiarity with LLM APIs, vector databases, or GPU-based environments
 
 
 Exposure to modern data platforms such as Databricks, Google BigQuery, or Amazon Redshift
 
 
 Financial Services
 
 
 Experience supporting trading or investment systems
 
 
 Understanding of trading workflows (OMS, order entry, trade booking), market data, or FIX protocol
 
 
 
 What We Value
 
 
 
 Bachelor's degree in Engineering, Computer Science, Information Systems, or equivalent experience.
 
 
 Hands-on experience with cloud platforms such as AWS, Azure, and Snowflake, with a solid understanding of IaaS, PaaS, and SaaS in hybrid environments.
 
 
 Experience in cloud infrastructure or server-side development, with a fundamental understanding of containerization and Kubernetes.
 
 
 Proficiency in programming languages like PowerShell and Python, with experience in DevOps tools such as Terraform, Docker, and Kubernetes.
 
 
 Deep understanding of CI/CD tools (e.g., Octopus, Bamboo, Azure DevOps, Git Actions) and configuration management.
 
 
 Expertise in automation scripting, infrastructure as code (IaC), and immutable infrastructure using tools like AWS CloudFormation or Terraform.
 
 
 Familiarity with observability frameworks (DataDog, OpenSearch, and LogicMonitor).
 
 
 Familiarity with networking, storage, and database concepts.
 
 
 Ability to craft clear, effective communications for both technical and non-technical audiences.
 
 
 Strong analytical and troubleshooting skills, attention to detail, ability to multitask, and work effectively in a fast-paced environment.
 
 
 Proficiency in writing scripts using Python, PowerShell, Bash, and experience with technologies like Docker, Lambda functions, and Kubernetes.
 
 
 Hands-on experience with Terraform, Packer, Git, and Jira is considered a plus.
 
 
 Integration with JIRA and GitHub is a plus
 
 
 Experience in designing, developing, and implementing ETL/ELT processes using Snowflake and related technologies.
 
 
 In addition to a base salary, the successful candidate will also be eligible to receive a discretionary year-end bonus.
 
 
 
 In all respects, candidates need to reflect the following SFM core values:
 
 
 
 
 Integrity // Teamwork // Smart risk-taking // Owner&rsquo;s Mindset // Humility
 
 
 
 
 Discover how SFM continues to drive impactful investments and supports the global mission of the Open Society Foundations.
 
</div>

Cloud SRE & DevOps Engineer

Granola

<div>Product Engineer (Transcription) &mdash; Granola
Location: London 
 
Hey! We're team Granola
We're looking for an engineer who loves audio and transcription, and loves building products in a fast-paced, iterative environment.
In this role, you will make Granola the best desktop transcription app that exists. You'll be talking directly with users to understand their transcription problems. You will be part of the founding team and help unlock Granola for the next 100x users.
In this role, you will:<ul><li>
Own and build our transcription features end-to-end. Things like:<ul><li>
Audio capture on macOS and Windows</li><li>
Echo cancellation</li><li>
Connections to transcription providers/models</li><li>
Local transcription models</li><li>
Diarisation/attribution</li><li>
Transcription UI/UX on our desktop app</li><li>
Logging and evals so we know whether all this is working/improving!</li></ul></li><li>
Feel every transcription papercut, because you&rsquo;ll be using Granola for every meeting!</li><li>
Optimise the application for speed, scale, and reliability</li><li>
Interact with users to understand their problems and design solutions</li><li>
Collaborate with a cross-functional team of engineers, product managers, designers, and other members of the team to create a cutting-edge product</li></ul>
Your background looks something like:<ul><li>
Experience with audio capture, real-time media pipelines</li><li>
Engineering experience at tech and product-driven companies</li><li>
Proficiency with TypeScript, Node.js, and React, and ideally Electron</li><li>
Comfortable dropping into native code and OS audio APIs (CoreAudio, WASAPI, &hellip;) when needed, even if you're not a low-level specialist</li><li>
Experience with speech-to-text models/providers</li></ul>
As a person, you&hellip;<ul><li>
Are first and foremost a builder.</li><li>
Are excited to work in-person from our office in London (most of the time)</li><li>
Love working in a startup environment (you either have experience working in a startup or are really drawn to the zero-to-one phase)</li><li>
Value working with people who are kind, ambitious, and pragmatic</li><li>
Have an interest in AI/ML (direct experience not required)</li><li>
Thrive in a fast-paced environment with evolving requirements and priorities 
About the opportunity
We are living in the most exciting time for tool builders since Engelbart's demo in 1968. We want to assemble the best crew to build this future together, here in London. Our compensation philosophy is to pay slightly above market on salary and above market on equity.
We do our best work in person, and so our team spends time together five days per week in our new, bright, and spacious office at Old Street. We are happy to offer relocation assistance to candidates who'll be moving to London to join us.
Lastly, we think amazing talent comes from all kinds of life journeys and experiences. If what is written above speaks to you, whether you look like a fit on paper or not, please reach out.</li></ul></div>

Product Engineer (Transcription)

Polymodal

<div>
 
 
 Every role at Polymodal is dual: founding platform builder first, with a ML research and signal intelligence edge that shapes the platform.
 
 
 
 
 
 
 As agents take on more execution, the platform needs models that understand behavior, predict action, and improve from its own data. You'll build the signal intelligence that makes the platform adaptive.
 
 
 
 
 
 Stack: Python/Rust, classifiers, eval pipelines, tiny predictive models, local / edge inference, inference routing, and world models for action prediction.
 
 
 What you'll own
 <ul>
 <li>
 Turn behavioral data into fast, tiny, useful models.
 </li>
 <li>
 Build and ship ML classifiers over agent and host telemetry.
 </li>
 <li>
 Build training/eval pipelines on our own data.
 </li>
 <li>
 Package models as production services (API, batch, edge).
 </li>
 <li>
 Optimize inference cost and latency: quantization, distillation, batching, caching.
 </li>
 <li>
 Partner with data engineering to turn raw signal into model-ready features.
 
 </li>
 </ul>
 About you
 <ul>
 <li>
 You care about models that survive production, not just notebooks or benchmarks.
 </li>
 <li>
 You turn messy behavioral data into hypotheses, evals, and shipped systems.
 </li>
 <li>
 You move fast without losing scientific honesty.
 </li>
 <li>
 You work well where research, product, and systems blur.
 
 </li>
 </ul>
 Must-haves
 <ul>
 <li>
 You use AI as part of your own research and engineering loop, not as a side tool.
 </li>
 <li>
 You have shipped ML into production and owned it end to end.
 </li>
 <li>
 Strong in Python/Rust and a modern ML framework (PyTorch or TensorFlow).
 </li>
 <li>
 Background in anomaly detection, sequence, or behavioral modeling.
 </li>
 <li>
 Experience with edge, embedded, or low-latency inference.
 
 </li>
 </ul>
 Nice-to-haves
 <ul>
 <li>
 Experience with small-model training, distillation, or quantization.
 </li>
 <li>
 Publications, notable GitHub work, or hard side projects.
 
 </li>
 </ul>
 About Polymodal
 
 Polymodal is a funded pre-seed company building the operating layer for agent-executed organizations. We closed our pre-seed in May 2026, backed by Lunar Ventures, Wind Capital, Volve Capital, and early-stage angels. We are early enough for every hire to shape the company, and real enough that the work must survive customers, scale, security, and trust.
 
 
 Co-founders &amp; team
 
 You'll build directly with Joep (3x founder, cybersecurity), Sean (former CISO at Slack/Reddit/Bumble), Edo (2x founder in AR/XR and multi-agent systems), and Atul (founder, cybersecurity). We are future-facing, execution-focused, daring, and human.
 
 
 Our offer
 <ul>
 <li>
 Competitive salary and meaningful early equity, so you share real ownership.
 </li>
 <li>
 A chance to define a new category while product, architecture, and company are still malleable.
 </li>
 </ul>
 
 
 
</div>

Machine Learning Research Engineer

Accenture

<div><h2 class="jobSectionHeader">Description</h2>
You build the systems that actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. The difference between an AI Engineer and what we are looking for is straightforward: you have shipped a multi-agent system in production, you have owned the eval harness, and you know what happens when your agent fails at 2am because you have lived it.
As an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI systems across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements.
This sits at the heart of the AI engineering talent market, demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme.<h2 class="jobSectionHeader">
Key Responsibilities</h2><ul><li>
Design and build production-grade agentic systems end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability</li><li>
Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning against real quality targets</li><li>
Integrate and abstract across multiple LLM providers &mdash; OpenAI, Anthropic, Vertex AI, and open-source models &mdash; with fallback routing, token, cost, and latency management</li><li>
Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring</li><li>
Embed directly with client engineering teams to design, prototype, and deploy agentic solutions &mdash; workshops, proofs of concept, code-with sessions, and architecture walkthroughs</li><li>
Build reusable patterns, accelerators, and playbooks that scale beyond the individual client engagement and enable the next one to start faster</li><li>
Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness; present findings and recommendations to client stakeholders in business terms</li></ul></div>
 
<div><h2 class="jobSectionHeader">Basic Qualifications</h2><ul><li>
5+ years of software engineering experience in production environments</li><li>
Minimum 1 year of hands-on experience designing and deploying agentic AI solutions in a production environment &mdash; non-negotiable</li><li>
Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent &mdash; at production depth, not tutorial level</li><li>
Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs</li><li>
RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering</li><li>
LLMOps fundamentals: eval harness design, prompt versioning, and production observability</li><li>
Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm)</li><li>
Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience</li><li>
Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure</li></ul></div>

AI Native SW Engineering Specialist

THRivve by intelletec

<div>
 
 
 Expert AI Engineer &ndash; GenAI | Series B Fintech | London (Hybrid)
 
 
 
 
 
 
 We&rsquo;re hiring an Expert AI Engineer to help build a next-generation GenAI product used by top-tier banks, hedge funds, and asset managers. This is a high-impact role on a brand-new AI product&mdash;turning massive financial datasets into real-time, explainable insights using LLMs.
 
 
 You&rsquo;ll own architecture, ship production-grade AI systems, and work directly on a product already gaining serious traction with enterprise clients.
 
 
 
 
 
 
 Key points:
 
 
 <ul>
 <li>
 Build and scale LLM-powered features across large, complex datasets
 </li>
 <li>
 Design retrieval + reasoning systems for structured &amp; unstructured data
 </li>
 <li>
 Own end-to-end delivery of production AI applications
 </li>
 <li>
 Work closely with product + domain experts in a fast-moving team
 </li>
 </ul>
 
 
 
 
 
 What they want:
 
 
 <ul>
 <li>
 ~10+ years engineering experience
 </li>
 <li>
 Strong hands-on GenAI / LLM experience in production
 </li>
 <li>
 Solid backend skills (Python or similar)
 </li>
 <li>
 Proven ownership of complex systems
 </li>
 </ul>
 
 
 
 
 
 Package:
 
 
 <ul>
 <li>
 Up to &pound;130k base + equity
 </li>
 <li>
 London (Victoria) &ndash; Hybrid
 </li>
 </ul>
 
 
 
 
 High ownership, real-world impact, and a chance to shape how AI is used in global finance&mdash;drop me a message if you&rsquo;re interested.
 
</div>

Artificial Intelligence Engineer

LiveKit

<div><h2 class="jobSectionHeader">About LiveKit</h2>
LiveKit is building the infrastructure layer for the agentic era of computing. Our platform gives developers everything they need to build, test, deploy, scale, and observe AI agents in production. Founded in 2021, LiveKit powers voice and agentic AI applications for OpenAI, Salesforce, Spotify, Meta, and tens of thousands of other developers, collectively facilitating billions of calls each year.<h2 class="jobSectionHeader">
About This Role</h2>
This isn't one of those situations where we tack &quot;engineer&quot; onto the back of every role at LiveKit. No. We're actually looking for an engineer*. A rare type of engineer that cares about talking to and advocating for customers, helping unblock them by fixing bugs or writing up sample code, and providing customers with guidance, pointers and support.
We say rare because in our experience, most engineers aspire to architect large-scale systems or tackle deeply technical problems. Said differently, most engineers want to have influence over the technology they work on or with. There's nothing wrong with that &mdash; we love hardcore engineers, and there are many at LiveKit. But this time, we're looking for a new teammate that wants to have influence over our product and business.
If you'd be energized by seeing a developer or team flip a LiveKit integration from staging to production &mdash; secretly satisfied in knowing you helped make it possible &mdash; you are perfect for this.<h2 class="jobSectionHeader">
You'll Thrive Here If You:</h2><ul><li>
are an engineer at heart, and don't mind reading more code than you write</li><li>
are a natural teacher who finds joy in helping others learn and succeed</li><li>
can break down complex technical concepts in a way that's easily understood by others</li><li>
enjoy learning new programming languages quickly and prototyping</li><li>
care deeply about the developer experience and the success of the people building on our platform</li><li>
have excellent spoken and written English</li></ul><h2 class="jobSectionHeader">
What You'll Do</h2><ul><li>
Support and work directly with developers, teams, and companies building with LiveKit, both commercially and in the community</li><li>
Triage, file, and fix bugs, respond to support tickets, write sample and production-quality code, and update documentation and technical guides in service of customers</li><li>
Collaborate and support community efforts, specifically around technical issues</li><li>
Regularly meet with and follow up with LiveKit customers to ensure their continued success on the platform</li><li>
Partner closely with Sales, BD, and Partnerships teams on strategy and support them in customer conversations</li></ul><h2 class="jobSectionHeader">
Who You Are</h2><ul><li>
A practicing engineer with demonstrated ability to build, ship, and debug production software</li><li>
Comfortable working across an unfamiliar codebase to diagnose and resolve customer issues</li><li>
A clear written and verbal communicator who can adapt your message to technical and non-technical audiences</li><li>
Curious, fast-learning, and energized by ambiguity</li><li>
Customer-focused &mdash; you feel the difference between solving a ticket and solving the underlying problem</li></ul><h2 class="jobSectionHeader">
Nice to Have</h2><ul><li>
You've literally done this role before</li><li>
Experience working with a community of developers</li><li>
Contributions to open source</li><li>
You've built something with LiveKit</li><li>
You're multilingual &mdash; LiveKit has users around the world</li></ul><h2 class="jobSectionHeader">
Our Commitment to You</h2><ul><li>
An opportunity to build something truly impactful to the world</li><li>
Contribute to open source alongside world-class engineers</li><li>
Competitive salary and equity package</li><li>
Health, dental, and vision benefits</li><li>
Flexible vacation policy</li></ul>
LiveKit is an equal opportunity employer and does not discriminate on the basis of any characteristic protected by applicable law. If you require a reasonable accommodation during the application or interview process, please contact recruiting@livekit.io.
Compensation Range: &pound;145K - &pound;185K</div>

Developer Success Engineer

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