Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy. Because our technology is purpose-built for restaurants, by restaurant people - and increasingly shaped by AI in both what we build and how we build - restaurants can trust that we'll deliver on their needs for today while investing in the experiences that will power their restaurant of the future.

AI Foundations is Toast's internal platform team for AI. We build the infrastructure, governance, and developer tooling that makes AI a reliable, scalable force multiplier across the entire product development lifecycle. Our products include the LLM Proxy, AI Key Management, Observability pipelines, the Claude Plugin Marketplace, and autonomous agents that participate directly in the software development lifecycle.

As a Senior Software Engineer on this team, you'll be hands-on building full-stack across the systems other Toast engineers depend on every day: the LLM proxy, agentic workflows, and the plugin marketplace that brings AI-native development practices to teams across the company.

A day in the life (Responsibilities)

• Design, build, and ship features across AI platform infrastructure, including the LLM proxy, AI key management, and observability pipelines
• Develop and extend autonomous agents that participate in the SDLC, such as the AI Review GitHub App and Developer Platform MCP integrations
• Build on and contribute to the internal plugin marketplace, developing plugins that encode Toast's architectural standards and quality practices into AI assistant behavior
• Implement MCP (Model Context Protocol) services and service templates that make it faster and easier for teams across Toast to build AI-powered workflows
• Contribute full-stack across backend services and frontend or developer-facing interfaces as needed
• Write high-quality, well-tested code and participate in design and code reviews
• Partner closely with product management to shape feature requirements, contribute to roadmap discussions, and translate product vision into reliable technical solutions

What you'll need to thrive (Requirements)

• 5+ years of experience designing and implementing scalable software systems, with a full-stack background spanning backend services and frontend or developer-facing interfaces
• Demonstrated experience building, deploying, or operating LLM-powered agents or AI-assisted developer tooling
• Familiarity with AI coding assistants (e.g., Claude Code, Cursor, GitHub Copilot) and an interest in extending them through custom plugins, skills, or hooks
• Experience with MCP (Model Context Protocol), tool use patterns, or agentic frameworks
• Working knowledge of prompt engineering and how LLM behavior responds to context and instructions
• Strong foundation in modern backend (Java, Kotlin, or similar) and frontend (TypeScript, React, or similar) technologies
• Experience with distributed systems, REST APIs, and cloud-native infrastructure
• Strong customer empathy and a drive to make developers' lives better through reliable, well-designed platform solutions

What will make you stand out

• Familiarity with A2A (Agent-to-Agent) protocols and multi-agent orchestration patterns
• Experience with machine learning concepts, model evaluation, or ML infrastructure
• Experience building developer experience platforms, internal tooling, or API gateways
• Familiarity with observability tooling for AI/LLM systems (e.g., Langfuse, DataDog)

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy 
We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.

Because our technology is purpose-built for restaurants, by restaurant people - and increasingly shaped by AI in both what we build and how we build - restaurants can trust that we'll deliver on their needs for today while investing in the experiences that will power their restaurant of the future.

An AI pod is Toast's AI-native engineering team, a focused pod of specialists who tackle complex, high-impact problems across Toast's product and platform landscape using AI-first approaches.

As a Principal Software Engineer, you'll work full-stack across ambitious, cross-cutting initiatives, bringing deep technical expertise and architectural judgment to some of the hardest problems at Toast.

A day in the life (Responsibilities)

• Lead full-stack design and delivery of AI-native solutions that address complex, cross-functional problems across Toast
• Drive technical architecture for pod initiatives, from backend services and APIs to frontend and developer-facing interfaces
• Build and integrate LLM-powered agents, tools, and workflows that bring AI capabilities directly into product and platform contexts
• Set and uphold engineering standards within the pod: code quality, system design, testing, and operational practices
• Mentor engineers through design reviews, code reviews, and pairing
• Partner with stakeholders across Toast engineering to define problem scope, align on approach, and deliver outcomes
• Serve as a technical voice in cross-team architecture discussions, connecting pod work to broader Toast engineering patterns

What you'll need to thrive (Requirements)

• 10+ years of experience designing and delivering scalable software systems, with a strong full-stack background spanning backend services and frontend or developer-facing interfaces
• Demonstrated experience leading technical architecture for a platform, product, or engineering team
• Experience building, deploying, or operating LLM-powered agents or AI platform infrastructure
• Familiarity with AI coding assistants (e.g., Claude Code, Cursor, GitHub Copilot) and experience extending them through custom plugins, skills, or hooks
• Experience with MCP (Model Context Protocol), tool use patterns, or similar agentic integration frameworks
• Strong prompt engineering skills and intuition for how LLM behavior responds to context and instructions
• Strong foundation in modern backend (Java, Kotlin, or similar) and frontend (TypeScript, React, or similar) technologies
• A bias towards action and comfort operating in ambiguous, rapidly evolving problem spaces

What will help you stand out

• Familiarity with A2A (Agent-to-Agent) protocols and multi-agent orchestration patterns
• Experience with machine learning concepts, model evaluation, or ML infrastructure
• Experience building developer experience platforms or internal tooling
• Familiarity with observability tooling for AI/LLM systems (e.g., Langfuse, DataDog)

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy 
We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

#LI-Hybrid
#BI-Hybrid

What's the opportunity?

Fin is the #1 AI agent for customer service. It resolves over 1M customer conversations every week, and we're just getting started. We're on the cutting edge of defining how AI agents should work — inventing paradigms that didn't exist six months ago and discovering entirely new problem spaces every time we push the technology further.

This role sits at the heart of the Service Agent pillar — 12 teams and growing, building every capability that makes Fin work. You'll partner at the strategic pillar level: broad context across work streams, deep technical understanding of how Fin operates end-to-end, and the autonomy to decide where you need to go next. When we need a new work stream spun up from scratch — a brand new team, an ambiguous problem space, aggressive timelines — you're the person who makes that happen.

The competitive landscape is intense. Fast-moving AI-native startups are coming hard for this space, shipping aggressively and going after the same deals we are. We need someone who thrives under that pressure, who can maintain technical excellence while moving at startup speed within a company that has the resources and customer base to make that speed count.

What will you do?

• Partner at the strategic pillar level. You'll have broad context across work streams and use that to inform technical strategy and investment priorities. What should we care about? Where should we invest? Where do you need to step in? These are your decisions.
• Spin up 0-to-1 work streams. Bring together engineers who've never worked as a team, disambiguate the problem space, build momentum under aggressive timelines, set high expectations, and drive execution.
• Execute on the most ambiguous, highest-stakes problems. You're hands-on. You write code, you ship features, you're deep in the weeds. We've seen too many Principal Engineers who are brilliant but too far from execution to be effective here.
• Lead experimental work at the AI frontier. Run your own A/B tests, do prompt engineering, build evals, and calibrate accuracy, cost, and latency for LLM-powered features. Much of what we're building are new paradigms for customer-facing software.
• Shape long-term technical strategy through execution. Your hands-on work informs the architecture. You're simultaneously building and thinking about what needs to change about how we build products — data models, system design, the shift from GUI-first to agent-first interfaces.
• Work across the full stack in an AI-first development environment. Every engineer has Claude Code with unlimited tokens and a sophisticated ecosystem of MCP servers, skills, and shared context. You'll push the boundaries of what's possible with AI-assisted development and help shape how the entire engineering org works.
• Raise the bar for the people around you. Give direct, actionable feedback that changes outcomes. We don't need someone who mentors juniors on the basics — we need someone who can accelerate and grow the senior and staff engineers around them.

What are we looking for?

The core requirement: engineering depth and product thinking. We need someone who combines deep engineering ability with strong product and design instincts — not one or the other. We don't want engineers who are technically brilliant but disconnected from the product. And we don't want product-minded engineers who have great instincts but can't execute at the level this work demands. You need to be able to both build complex systems AND identify the right problems to solve. This is the single most important dimension we evaluate on.

Beyond that:

• Operated at real scale and has builder energy. You've likely spent time at companies operating at significant scale — the kind of environment where you've seen what large-scale distributed systems actually look like in production. But you also have startup DNA: urgency, resourcefulness, a bias toward building over discussing.
• AI fluency. You're actively experimenting with AI-assisted development, pushing the boundaries of what's possible, and forming opinions about how it changes the way teams build software. This matters more than any specific stack experience.
• Deep technical depth with breadth. You can go deep into the weeds on at least one technical domain, but you also navigate complex multi-team systems with ease. In conversation, you move fluidly from business context to technical strategy to implementation details.
• Communication as a superpower. You can explain to leadership why a technical investment matters, align multiple teams around a complex project, and then walk an engineer through the gnarly implementation details. This role lives and dies on your ability to communicate across every level.
• Extreme autonomy. You partner with the Engineering Director on where you think the pillar needs to go next. You identify problems, form convictions, and act on them. If you're the kind of engineer who waits to be told what to work on, this isn't the right role.
• Critical thinking about the business. You understand what Intercom is optimizing for and translate that into technical decisions. Which work streams need investment? Where are we falling behind? What should we defund to go harder somewhere else? You think at this level naturally.
• At least ~10+ years of experience, with significant time as a technical leader driving complex projects across multiple teams and stakeholders.
• Stack agnostic. We use Ruby on Rails, React (migrating from Ember), and AWS. But AI tools increasingly abstract the stack — what matters is your ability to learn, build, and operate effectively with tools like Claude Code. If you're great with a high-level programming language and fluent with AI-assisted development, you'll be productive fast.

Why Intercom, why now?

Fin is #1 — and the race is heating up. We built the leading AI agent for customer service, but fast-moving AI-native startups are coming for this space. This is one of the most consequential competitive moments in tech history, and the engineering decisions made in the next 12 months will determine who wins.

A rare pivot that actually worked. Intercom has been building for 15 years — deep product, massive customer base, strong revenue. But unlike most legacy SaaS companies, we made a successful pivot to AI. While most of SaaS trends down, Intercom trends up. We recently raised $250M to go even further even faster..

AI-first engineering culture. Every engineer gets Claude Code with unlimited Opus 4.6 tokens and 1M context. We're investing heavily in the platform capabilities — MCP servers, skills, shared tooling — that make AI-assisted development genuinely transformative. You'll be at the sharp edge of figuring out what this means for how teams work.

The sweet spot. Big enough to have real resources, customers, and revenue. Small enough that you have genuine agency. Bold enough to make decisions that most companies of this size wouldn't. You come to Intercom if you want the impact of a startup with the backing of a company that's been winning for 15 years.

Benefits

We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us! 

• Competitive salary and equity in a fast-growing start-up
• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
• Regular compensation reviews - we reward great work!
• Pension scheme & match up to 4%
• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
• Flexible paid time off policy
• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
• If you’re cycling, we’ve got you covered on the Cycle-to-Work Scheme. With secure bike storage too 
• MacBooks are our standard, but we also offer Windows for certain roles when needed.

#LI-Hybrid

Your Role:

Tenable's cloud-based exposure management platform helps organizations see, understand, and reduce cyber risk across their entire attack surface. Our SRE teams keep that platform reliable, scalable, and secure — and we're building the next generation of tooling to do it smarter.
 

This role sits within our SRE Infrastructure Management organization on a focused team dedicated to reducing operational toil through AI-powered automation. You'll build intelligent systems that replace manual workflows — from incident diagnostics to infrastructure provisioning to upgrade automation — using LLMs, agentic architectures, and deep SRE domain knowledge.
 

This isn't an operations role with some AI on the side. You'll spend most of your time writing production code: designing and building agentic workflows, integrating across observability and infrastructure platforms, and measuring the impact of what you ship against real toil data.

Your Opportunity:

• Design and build AI-powered agentic workflows that automate complex SRE operations — incident investigation, infrastructure provisioning, deployment reliability, and more.
• Improve the accuracy, reliability, and observability of agent pipelines through evaluation frameworks, prompt engineering, retrieval strategies, and structured output validation.
• Build developer tools and internal platforms — CLI tools, IDE plugins, and workflow automation — that engineers across the organization use daily.
• Build tooling that connects across the SRE tech stack — Kubernetes, Terraform, Helm, CI/CD pipelines, observability platforms, and cloud infrastructure APIs.
• Work on a focused team where everyone writes code, owns what they ship, and drives prioritization from measured toil data.
• Participate in SRE on-call rotation — we use on-call as a direct input into what we build, not just a firefighting duty.
• Collaborate with SRE teams across the organization to identify automation opportunities and deliver tooling that gives engineers hours back.

What Success Looks Like:

• Within your first few months, you've shipped an agentic workflow that automates a real SRE toil category — and engineers are using it.
• Within 6 months, you're independently designing and building AI-powered pipelines, contributing to the team's evaluation and accuracy practices, and your work is driving measurable toil reduction.
• Within a year, you've become a go-to contributor on the team — shaping the roadmap, mentoring others on AI + SRE patterns, and building systems that scale the team's impact across engineering.

What You'll Need:

And Ideally:

We’re building a new team building to bring the power of Datadog to developers within AI-focused Developer workflows such as AI agents like Cursor, Claude code, GitHub Copilot and Datadog’s native AI agents.

We’re looking for product-minded engineers who are excited about developer tools, SDLC improvements and AI in general to help us quickly define and ship features and tools that make all Datadog customers 10x developers.

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

What You’ll Do: 

• Work on agents, prompts, evals, MCPs and direct agent tools from ideation to productization, for allowing Datadog to help companies and developers to maximize the benefit of their integration with Datadog
• Help conceptualize and build innovative User flows and experiences within Datadog’s user space and different extensions 
• Prototype and see what works well in the real world, iterate closely with our users, and then ship
• Follow the latest research on LLM prompt optimization, agents, and code editing.
• Support other Datadog product teams to help them build and productionize their developer-focused AI Workflows. For example, you’ll work with the Live Debugger team to create an agentic production debugging experience, delivering on the vision of  “one click to reproduce” for production errors.

Who You Are: 

• You’re a backend engineer with at least 5 years of professional experience who values code simplicity and performance. You’ve shipped software that uses LLMs to production
• You are passionate about Generative AI and its ability to help software engineers be more productive
• You have relevant experience with Large Language Models, large-scale systems and data sets, machine learning, or adjacent fields
• You are a great community ambassador and can drive hard technical conversations towards a pragmatic solution
• You want to work in a fast, high-growth startup environment that respects its engineers and customers
• You have experience writing classic or AI oriented developer tools(such as IDEs, static code analysis, SDLC tools etc).
• You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent experience

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

Benefits and Growth: 

• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• Intradepartmental mentor and buddy program for in-house networking
• An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)
• Access to Inclusion Talks, our Internal panel discussions
• Free, global mental health benefits for employees and dependents age 6+
• Competitive global benefits

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

#LI-Hybrid

About the role:

Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments.  We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.

The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.

Strong candidates may also have experience with:

• High-performance, large-scale distributed systems
• Implementing and deploying machine learning systems at scale
• Load balancing, request routing, or traffic management systems
• LLM inference optimization, batching, and caching strategies
• Kubernetes and cloud infrastructure (AWS, GCP)
• Python or Rust

You may be a good fit if you:

• Have significant software engineering experience, particularly with distributed systems
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Want to learn more about machine learning systems and infrastructure
• Thrive in environments where technical excellence directly drives both business results and research breakthroughs
• Care about the societal impacts of your work

Representative projects across the org:

• Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
• Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
• Building production-grade deployment pipelines for releasing new models to millions of users
• Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
• Contributing to new inference features (e.g., structured sampling, prompt caching)
• Supporting inference for new model architectures
• Analyzing observability data to tune performance based on real-world production workloads
• Managing multi-region deployments and geographic routing for global customers

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

About the Role

We’re looking for a Junior Security Operations Engineer who is AI-Forward to help scale and modernize our SecOps program. This is a hands-on, builder role for someone who will design and ship the security tooling that powers our triage, investigations, and response workflows.

You’ll report to the Technical Operations Director and work alongside our GRC lead to improve our vulnerability intake, threat response, darkweb posture, and internal security tooling. A core part of this role is building AI-assisted security tooling: triage agents that pre-classify bug bounty reports, investigation copilots that pull context from logs and SIEM data, response workflows that draft remediation steps and track them to closure. You’ll spend as much time wiring up that tooling as you will reproducing vulnerabilities and working incidents.

This role suits someone who thrives in a lean, high-impact environment, has strong opinions on where humans add value versus where tooling should take over, and wants to shape how a modern security team operates.

What You’ll Do

Triage & Vulnerability Management

• Review incoming vulnerability reports from our bug bounty intake; reproduce and document valid issues for engineering teams.
• Build the tooling that improves signal-to-noise: automate duplicate detection, spam filtering, and abuse flagging so humans only touch what’s worth touching.
• Act on DAST findings: coordinate remediation, verify fixes, and re-test.
• Track remediation timelines for critical vulnerabilities and keep stakeholders honest on SLAs.

Threat Response & Monitoring

• Monitor and respond to EDR and cloud security alerts; investigate, contain, and document.
• Analyze darkweb findings and credential exposures; shape our darkweb monitoring practices and tooling over time.
• Improve detection coverage: tune noisy rules, close gaps, and enrich alerts with context so responders spend time on decisions, not data gathering.
• Help configure and tune DLP, SIEM, and AI security tooling.

Security Tooling (core to this role)

• Build AI-assisted triage tooling that pre-classifies bug bounty reports, flags duplicates, and routes real issues to the right engineering team with reproduction context attached.
• Build investigation tooling: LLM-backed copilots and Slack bots that pull alert context, correlate signals across sources, and surface what actually matters.
• Build response tooling: workflows that draft remediation steps, generate evidence artifacts, and track issues to closure across the teams that own them.
• Evaluate emerging AI security tooling and bring what’s genuinely useful into the stack; retire what isn’t.
• Apply a security-minded lens to our own AI usage: prompt injection, data exfiltration, model misuse, and the guardrails that go around them.

Compliance & Cross-Functional

• Support audit evidence collection for SOC 2, ISO 27001, and PCI DSS.
• Partner with ITOps to verify patches, endpoint coverage, and access hygiene.

You May Be a Good Fit If You Have

• Previous experience in a SecOps, Security Analyst, or Threat Response role.
• Proven ability to understand and reproduce technical vulnerabilities. You can read a bug report and tell whether it’s real.
• Experience with bug bounty triage (HackerOne, Bugcrowd, or similar).
• Hands-on exposure to SIEM, EDR, and DLP tools in production environments.
• A genuine, demonstrated interest in applying AI/LLMs to security work: side projects, internal tooling, prompt engineering, agent frameworks, anything that shows you’ve actually built with this stuff.
• Scripting and automation skills in Python, Bash, or similar. You reach for code before you reach for a checklist.
• Comfort working autonomously across time zones and asynchronously.
• Strong written communication. You can turn a messy investigation into a clear, defensible writeup.

Bonus Points For

• Experience building LLM agents, RAG pipelines, or Slack bots backed by OpenAI / Anthropic / open-source models.
• Detection engineering experience (Sigma rules, custom Falcon queries, Grafana/Loki dashboards).
• Cloud security depth in AWS or GCP (IAM, workload posture, cloud-native logging).
• Prior work in regulated environments (SOC 2, ISO 27001, PCI DSS) from the practitioner side.
• Exposure to AI/ML security concerns such as prompt injection, model evals, and data leakage through LLMs.
• Public contributions: blog posts, CVEs, open-source tools, CTF writeups.

Engagement & Logistics

• Full-time contract.
• Remote-first and async-friendly. We have hubs in San Francisco, Denver, Dublin, and Amsterdam. If you’re near one, we’d love to see you in the office regularly; if you’re elsewhere in the world, that works too.
• Potential to extend or convert based on fit.
• Reports to the Technical Operations Director; works closely with the GRC lead and IT Operations.

How We Work

We’re a lean, high-trust team. We value people who ship, who can operate independently, and who treat security as an engineering problem rather than a checklist. If you’re someone who sees a repetitive task and immediately thinks “this should be a script, or better yet, an agent,” you’ll fit in here.

To Apply

Tell us about a time you used AI, automation, or custom tooling to meaningfully change how a security workflow ran. What was manual before, what it looked like after, and what you learned. Links to code, writeups, or demos are welcome.

What’s the opportunity?

Intercom is the AI Customer Agent company. Our AI agent, Fin, is transforming customer experience for businesses, and we believe that the same AI transformation should power our R&D organization.

At Intercom, shipping is our heartbeat. We are hiring a Senior Engineer for Builder Tools: the AI Developer Experience Enablement team. This is the team that makes shipping delightful, fast, and low-toil for hundreds of engineers and agents.

Your mission is to help turn Intercom’s entire R&D organization into an AI-first engineering machine. We’ve made incredible progress, 90%+ of our code is already written by Claude, but that volume creates entirely new scaling and orchestration challenges. You will work across our codebases, developer environments, and internal tooling to make AI a trustworthy, everyday accelerant.

You will ship tangible solutions every day that work, prove their value, and scale. You’ll focus on developer enablement: operationalizing AI for real-world engineering effectiveness and eliminating drag so all of R&D can do their best work.

Learn how we ship 250 versions of Intercom per day, discover our engineering culture at intercom.engineering, and explore our engineering values.

What you’ll do?

• Build AI-driven automation agents that remove routine work with human-in-the-loop review, prioritize impact, prototype fast, and iterate until the automation transforms engineering.
• Make AI-assisted workflows the default in our developer environments: ship integrations, preconfigured workspaces, and developer agents that engineers want to use.
• Improve our codebases for AI: refactor, document, and introduce standards so agents and code suggestions are more accurate and reliable. Partner with repo owners to trial changes and measure outcomes.
• Instrument and measure everything: define success metrics, track adoption and impact, and use telemetry to guide improvements.
• Balance practicality and safety: design systems that consider cost, observability, privacy, and guardrails so AI features are dependable and trustworthy.
• Evangelise and enable adoption: work with engineering leads and internal champions, create playbooks and demos, and help teams get real benefit from the tooling.
• Ship production-grade services: own design, implementation, tests, and operational runbooks and agent skills.

What skills do I need?

We don’t expect perfection. If you have most of this and you’re excited, we want to hear from you. We can shape the position for the right person.

• Multiple years building and supporting high-performing systems, ideally in a SaaS, platform, or internal tooling context. You've introduced new tools or workflows that actually got adopted and made a difference.
• Practical AI toolchain experience: hands-on with LLMs, agents or code-assistants, model APIs, or prompt engineering. Demonstrated strong curiosity and a track record of learning these quickly.
• Deep knowledge of at least one major programming language (Ruby, Python, JavaScript, etc.). Experience restructuring, documenting, and modernizing large codebases is a massive plus.
• Developer experience obsession: you think in terms of developer time saved, reliable defaults, and usable workflows. You’ve shipped CI/CD, dev environment automation, code-quality tools, or similar.
• You align stakeholders, share best practices, make engineering trade-offs visible, and listen to your internal customers before acting.
• Bias to action and pragmatism: you iterate fast, unblock yourself and others, and stop or pivot when things do not deliver value.

Why join us?

You’ll be at the heart of Intercom’s shift to AI-first engineering. We’re giving engineers superpowers, shipping solutions that get real traction, and building a foundation for world-class developer productivity. You’ll work alongside kind, driven colleagues and have the autonomy to make a company-wide impact.

Benefits

About the Role

We're looking for a curious, technically-minded problem solver — not someone to just close tickets.

You'll troubleshoot complex customer issues across voice, messaging, APIs, IoT, and AI products, digging into networking problems, debugging integrations, and analysing logs alongside engineering teams. But this role goes further: we're building an AI-first support model, and as you develop product expertise, you'll help shape it — building bots, automating workflows, and turning repetitive tasks into cron jobs. If you've ever spotted a repetitive task and actually built the fix for it, you'll fit right in. A background in software engineering, networking, or a related technical field (however you got there) is ideal — We care about what you can do, not where you learned it.

What You'll Do

• Troubleshoot: complex customer issues across networking, APIs, and communications products
• Investigate: using tools like Postman, cURL, Wireshark, Linux terminal and our internal tooling
• Collaborate: with customers, vendors, and engineering teams to resolve cases
• Automate: contribute to bot-building and workflow automation
• Document: solutions and improve self-service resources
• Learn: VoIP protocols, internal systems, and new technologies as the role evolves

Your Toolkit

• Troubleshooting: Postman, cURL, Wireshark, sngrep, Linux terminal
• Ticketing and Comms: Zendesk, Slack
• Collaboration: Google Workspace (Gmail, Calendar, Docs, Sheets, Meet)
• Automation: n8n, Zapier, OpenClaw (internal AI platform), scripting (Python, Bash, etc.)
• Version Control: GitHub
• Analytics: Metabase, Graylog, Jira

What We're Looking For

Must-Have

• Background in Computer Science, IT, networking, or equivalent hands-on experience
• Networking fundamentals: solid understanding of how the internet works, including DNS, routing, IP addressing, and HTTP/HTTPS
• API experience: comfortable with REST APIs, webhooks, and tools like Postman or cURL
• Linux terminal proficiency: comfortable navigating filesystems, reading logs, and running commands
• Problem-solving mindset: you dig into issues, ask good questions, and don't give up easily
• Communication skills: you'll need to be highly proficient in English, both written and verbal - owning customer communication and technical documentation from day one

Nice-to-Have

• Familiarity with scripting or programming (Python, Bash, JavaScript, or similar)
• Understanding of AI concepts such as RAG, MCPs, embeddings, and prompt engineering
• Experience using n8n, Zapier, Git/GitHub, or similar

You don’t need to tick every box -  if you’re keen to learn that's the box that matters most ! 

This role operates on Central Time (UTC-6), 9am–6pm Monday to Friday

About the role:

Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments.  We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.

The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.

As a Staff Software Engineer on our Inference team, you will work end to end, identifying and addressing key infrastructure blockers to serve Claude to millions of users while enabling breakthrough AI research. Strong candidates should have familiarity with performance optimization, distributed systems, large-scale service orchestration, and intelligent request routing. Familiarity with LLM inference optimization, batching strategies, and multi-accelerator deployments is highly encouraged but not strictly necessary.

Strong candidates may also have experience with:

• High-performance, large-scale distributed systems

• Implementing and deploying machine learning systems at scale

• Load balancing, request routing, or traffic management systems

• LLM inference optimization, batching, and caching strategies

• Kubernetes and cloud infrastructure (AWS, GCP)

• Python or Rust

You may be a good fit if you:

• Have significant software engineering experience, particularly with distributed systems

• Are results-oriented, with a bias towards flexibility and impact

• Pick up slack, even if it goes outside your job description

• Want to learn more about machine learning systems and infrastructure

• Thrive in environments where technical excellence directly drives both business results and research breakthroughs

• Care about the societal impacts of your work

Representative projects across the org:

• Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators

• Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads

• Building production-grade deployment pipelines for releasing new models to millions of users

• Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage

• Contributing to new inference features (e.g., structured sampling, prompt caching)

• Supporting inference for new model architectures

• Analyzing observability data to tune performance based on real-world production workloads

• Managing multi-region deployments and geographic routing for global customers

   

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