Customer Engineer

A WORLD-CHANGING COMPANY Meticulous is accelerating the pace of software development. We’ve built the world’s first fully autonomous and exhaustive testing platform for frontend codebases - a capability that has never existed before and that we believe is key to unlocking the full potential of code generation. The demand for Meticulous has been strong. Companies like Dropbox, Wiz, and Notion often choose Meticulous as one of the most valuable tools in their engineering stack, and frequently recommend us to others. Our team of twelve has built this by combining deep technical focus with a high bar for quality, drawing experience from companies such as Uber, Google, Dropbox, GitHub, Meta, and Palantir. You can learn more about the company in this video here. THE ROLE As one of the first Forward Deployed Engineers at Meticulous, you’ll help shape how we work with customers and how leading engineering teams adopt our technology. This role is a mix of software engineering and customer-facing problem solving. You’ll work closely with engineering teams at companies like Notion, Dropbox, Wealthsimple, Outtake, and LaunchDarkly to understand how their systems work and help them successfully deploy Meticulous. Some days you’ll be writing and debugging code; other days you’ll be discussing technical decisions, trade-offs, and best practices with customer engineers. You won’t be expected to know everything on day one. You’ll be supported by experienced engineers on the team, but you’ll also be given real ownership and responsibility early on. CORE RESPONSIBILITIES This role spans both engineering and customer success. You’ll take ownership of customer deployments and do what’s needed to make Meticulous successful for them, including: * Work with customers to deploy Meticulous at scale. Partner with customer engineering teams to understand their architecture, design implementation approaches that fit their systems, and work alongside them to ship reliable solutions. * Improve the product based on real-world usage. Debug issues that block deployments, investigate problems that reach into core parts of the system, and help ship improvements or features that make the product work better for both the customer you’re focused on and Meticulous overall. * Build strong customer relationships. Communicate regularly with engineers and engineering leaders, help guide rollouts, and collect feedback to ensure customers are successful and supported. * Influence product direction. Use what you learn from working with customers to help inform what we build next. For smaller improvements, you’ll often implement them directly; for larger changes, you’ll work closely with the core engineering team to scope and deliver them. * Help define best practices. As the Forward Deployed Engineering function grows, you’ll contribute to documentation, tooling, and processes that make each new deployment smoother than the last. WHAT WE’RE LOOKING FOR * Strong technical foundation. A degree in computer science, engineering, or a related technical field, with solid fundamentals in programming and systems. * High ownership and motivation. You’re comfortable taking responsibility, figuring things out, and moving projects forward even when things are ambiguous. * Entrepreneurial spirit. You’ve spent time building things outside of structured coursework such as working on a startup, founding or contributing to an open-source projects, or shipping personal projects end-to-end. * Clear communicator. You can explain technical ideas clearly, ask good questions, and enjoy working directly with other engineers. * Willingness to travel. Around 25% travel to customer sites, primarily in the US. WHAT YOU’LL GAIN * Learn by building a new function. You’ll be part of shaping an entirely new role at Meticulous, with clear opportunities to grow in responsibility and influence as the team expands. * Exceptional growth and mentorship. We intentionally keep the team small and highly experienced. You’ll work closely with engineers who have led large teams and built complex systems at top technology companies. The environment is fast-paced, collaborative, and focused on learning quickly from each other. Beyond core engineering growth, you’ll spend significant time working with engineering leaders at fast-growing startups and established tech companies. This gives you exposure to a wide range of technologies, architectures, workflows, and engineering cultures - experience that normally takes many years and multiple jobs to accumulate. * Expand your network. Our investors and advisors include leaders from Vercel, GitHub, Segment, YC, Adobe, and Dropbox. Through the role, you’ll also work directly with engineering teams across many top technology companies, building relationships early in your career that can compound for years. * Solve novel technical problems. You’ll work on challenging problems at the intersection of browser technology, testing infrastructure, and large-scale systems - areas that few engineers encounter early in their careers. * World-class compensation. Base salary £80k–£140k plus significant equity, competitive with top technology companies and startups. LIFE AT METICULOUS We believe autonomous testing will eventually enable the automation of much of software development. You’ll be working at the forefront of this shift, alongside the companies that are adopting these tools first. This role is on-site at our office in Moorgate. We’ve found that the level of collaboration, learning, and iteration required to succeed works best when the team is together in person.

ABOUT US: At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI. In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice: * Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog [https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think]) * Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog [https://fireworks.ai/blog/open-source-agents-frontier-advisors]) * The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) [https://fireworks.ai/blog/fine-tuning-bottlenecks] The Role AI Field Engineers at Fireworks are the technical tip of the spear. You embed with our most ambitious customers and technology partners to turn complex AI problems into production systems, fast. The role sits at the intersection of engineering, product, and customer delivery. You are hands-on-keyboard building POCs, MVPs, and production integrations, while also holding your own in executive-level conversations about architecture, strategy, and business outcomes. You spend most of your time building. You ship code, run benchmarks, debug production issues, and architect deployments. But you also lead discovery conversations, align stakeholders, and translate customer pain points into product improvements that compress the feedback loop from field to roadmap. This is a role for engineers who are comfortable on-site with customers, building the relationships and trust that happen in person, not just over a call. The Segment As a Field Engineer in the Enterprise track you will work with large organizations and digital-native companies adopting GenAI across the business. These engagements span more stakeholders and longer cycles, so you will manage executive relationships and align teams while staying hands-on in the code. The emphasis is on pairing strong technical delivery with the executive presence to earn trust across an org: discovery, solution design, POC execution, and the path to production at enterprise scale. What You'll Work On Technical Delivery and Deployment * Build end-to-end POCs and MVPs alongside customer engineering teams, working inside their codebases, infrastructure, and constraints. * For customers whose core product is built on GenAI, architect the inference foundations that capability depends on, and size deployments so they can scale in their market without infrastructure becoming the bottleneck. * Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, and tune deployments to hit those targets * Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns across workloads. Model Strategy and Fine-Tuning * Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation methodology. * Build and run fine-tuning pipelines directly with customers, navigating trade-offs between model families, compute cost, and quality targets. * Design and implement evaluation frameworks that measure production-quality metrics, not just benchmark scores. Customer Engagement and Stakeholder Management * Many of our customers exist because of GenAI. Help them bake frontier model capabilities into their core offering and turn that into a durable competitive edge. * Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions. * Own the technical relationship from first engagement through production deployment. Earn trust with ML engineers and VPs in the same meeting. * Spend time on-site with customers. Build trust and momentum in person, embedding with their teams where the work happens. Product Feedback and Platform Improvement * Identify recurring customer pain points and translate them into concrete product proposals, working directly with engineering and product to ship fixes and features. * Codify repeatable deployment patterns and contribute them back to internal tooling, documentation, and the platform itself. * Feed customer signals (deployment patterns, failure modes, feature gaps) back into the product roadmap with specificity and urgency. What We're Looking For Minimum Qualifications * 5+ years in a hands-on, customer-facing technical role: Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder. * Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else's production environment. * Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering. * Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus). * Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure. * Exceptional communication: able to run a sharp discovery call, present to a VP, and debug a latency issue with an ML engineer in the same afternoon. Preferred Qualifications * 10+ years in technical field or engineering roles. * Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and tuning deployments for real workloads. * Experience operating as a technical authority inside a customer's environment building within their infrastructure, navigating their constraints, and shipping code that runs in their production systems. * Track record taking GenAI POCs from prototype to production-scale deployments. * Experience with hyperscaler AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex). * Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains. WHY FIREWORKS AI? * Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. * Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. * Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. * Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.