Technical Account Manager (TAM)

Fluidstack
London
1 week ago
Create job alert

About Fluidstack Fluidstack is the AI Cloud Platform.We build GPU supercomputers for top AI labs, governments, andenterprises. Our customers include Mistral, Poolside, Black ForestLabs, Meta, and more. Our team is small, highly motivated, andfocused on providing a world-class supercomputing experience. Weput our customers first in everything we do, working hard to notjust win the sale, but to win repeated business and customerreferrals. We hold ourselves and each other to high standards. Weexpect you to care deeply about the work you do, the products youbuild, and the experience our customers have in every interactionwith us. You must work hard, take ownership from inception todelivery, and approach every problem with an open mind and apositive attitude. We value effectiveness, competence, and a growthmindset. Overview: We are seeking a skilled Technical AccountManager (TAM) to serve as a trusted advisor and strategic partnerto our diverse customer base. In this role, you will be responsiblefor building and maintaining strong, long-lasting customerrelationships, managing support requests, designing proactivetriage systems, and ensuring seamless communication between ourcompany and our clients. You will work closely withcross-functional teams to deliver exceptional technical guidance,optimize customer experiences, and drive successful outcomes. Ifyou are passionate about Artificial Intelligence, cloudinfrastructure and customer success, this is an opportunity to makea significant impact. Focus 1. Act as the primary point of contactand advocate for assigned customers in a geographic region,obsessing over their needs and ensuring their success with ourcloud platform. 2. Oversee and prioritize incoming supportrequests, collaborating with technical support and engineeringteams to ensure timely resolution. Provide hands-on assistance totroubleshoot issues, escalating complex cases as needed whilekeeping customers informed throughout the process. 3. Partner withcustomers to plan and execute onboarding, data migration, andongoing operational improvements. 4. Conduct regular businessreviews with customers to assess performance, identifyopportunities for improvement, and align solutions with theirevolving needs. Deliver clear, concise, and impactfulcommunications to customers and internal stakeholders. Translatecomplex technical concepts into actionable insights, ensuringalignment and understanding. 5. Stay ahead of industry trends andemerging technologies to proactively recommend innovative solutionsto customers. 6. Represent the voice of the customer internally,providing feedback to improve products, services, and supportprocesses. Qualifications: - Bachelor’s degree in Computer Science,Information Technology, Engineering, or a related field (orequivalent experience). - 3+ years of experience in acustomer-facing technical role, such as Technical Account Manager,Solutions Architect, or Cloud Support Engineer. - Strongunderstanding of cloud architecture, DevOps practices, and toolssuch as Docker, Kubernetes, SLURM, CI/CD pipelines, orInfrastructure as Code (e.g., Terraform, CloudFormation). -Exceptional communication and interpersonal skills, with theability to explain complex technical concepts to both technical andnon-technical stakeholders. - Experience with project management,cloud migration, or enterprise support is a plus. - Demonstratedability to manage complex support requests, anticipate customerneeds, and develop innovative support systems to enhance servicedelivery. Must be able to manage multiple priorities in afast-paced environment while maintaining a customer-first mindset.- Comfortable working extended hours in an on-call format whenrequired (Europe/U.S. time zones). Exceptional candidates have oneor more of the following experiences: - Startup Experience: Workedat an early-stage company (pre-Series A or Series A). - SystemDesign Expertise: Designed and implemented end-to-end systems(e.g., software, support, infrastructure, workflows) from theground up, with demonstrable impact on business or technicaloutcomes. - Role Scaling Experience: Successfully expanded thescope of your responsibilities in a previous position, growing yourimpact through increased ownership, team collaboration, or systemexpansion (e.g., scaled a prototype to production, grew a processto serve 10x users). - Problem-Solving Mindset: Strong ability tobreak down complex challenges, devise practical solutions, anditerate quickly based on feedback or data. - Hands-on experiencewith cloud platforms, including AWS (e.g., EC2, Sagemaker, Bedrock,S3, Lambda), Google Cloud (e.g., Compute Engine, Vertex, GKE,BigQuery), Azure (e.g., Virtual Machines, Azure OpenAI) etc. -Proficiency in scripting or programming (e.g., Python, Java, orPowerShell). Benefits - Competitive total compensation package(cash + equity). - Retirement or pension plan, in line with localnorms. - Health, dental, and vision insurance. - Generous PTOpolicy, in line with local norms. - Fluidstack is remote first, buthas offices in key hubs. For all other locations, we provide accessto WeWork. #J-18808-Ljbffr

Related Jobs

View all jobs

Account Manager

Account Manager

Strategic Customer Success Manager

Customer Success Engineer – German Speaking

Staff Software Engineer - Analytics fmd

Customer Success Lead (Gaming)

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

AI Jobs for Non‑Technical Professionals: Where Do You Fit In?

Your Seat at the AI Table Artificial Intelligence (AI) has left the lab and entered boardrooms, high‑street banks, hospitals and marketing agencies across the United Kingdom. Yet a stubborn myth lingers: “AI careers are only for coders and PhDs.” If you can’t write TensorFlow, surely you have no place in the conversation—right? Wrong. According to PwC’s UK AI Jobs Barometer 2024, vacancies mentioning AI rose 61 % year‑on‑year, but only 35 % of those adverts required advanced programming skills (pwc.co.uk). The Department for Culture, Media & Sport (DCMS) likewise reports that Britain’s fastest‑growing AI employers are “actively recruiting non‑technical talent to scale responsibly” (gov.uk). Put simply, the nation needs communicators, strategists, ethicists, marketers and project leaders every bit as urgently as it needs machine‑learning engineers. This 2,500‑word guide shows where you fit in—and how to land an AI role without touching a line of Python.

ElevenLabs AI Jobs in 2025: Your Complete UK Guide to Crafting Human‑Level Voice Technology

"Make any voice sound infinitely human." That tagline catapulted ElevenLabs from hack‑day prototype to unicorn‑status voice‑AI platform in under three years. The London‑ and New York‑based start‑up’s text‑to‑speech, dubbing and voice‑cloning APIs now serve publishers, film studios, ed‑tech giants and accessibility apps across 45 languages. After an $80 m Series B round in January 2024—which pushed valuation above $1 bn—ElevenLabs is scaling fast, doubling revenue every quarter and hiring aggressively. If you’re an ML engineer who dreams in spectrograms, an audio‑DSP wizard or a product storyteller who can translate jargon into creative workflows, this guide explains how to land an ElevenLabs AI job in 2025.

AI vs. Data Science vs. Machine Learning Jobs: Which Path Should You Choose?

In recent years, the fields of Artificial Intelligence (AI), Data Science, and Machine Learning (ML) have experienced explosive growth. Spurred by the increase in data availability, advances in computing power, and the demand for intelligent decision-making, organisations of all sizes are investing heavily in these areas. If you’ve been exploring AI jobs on www.artificialintelligencejobs.co.uk, you’ve likely noticed that employers use terms like “AI,” “Data Science,” and “Machine Learning”—often interchangeably. While they are closely related, there are nuanced differences between these fields. Understanding these distinctions is key if you’re trying to decide which path suits you best. This comprehensive guide will help you differentiate among AI, Data Science, and Machine Learning. We will discuss the key skills for each, typical job roles, salary ranges, and provide real-world examples of professionals working in these fields. By the end, you should have a clearer idea of where your strengths and passions might fit, helping you take the next step towards securing your ideal role in the world of data-driven innovation.