Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowPosted 6 hours agoWe saw it 8 min after it went up

Senior Customer AI Engineer - Token Factory

Jobgether3,600 open roles

Where
Germany
Work mode
Remote
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowSenior Customer AI Engineer - Token FactoryJobgether · Germany

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Jobgether's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

8.5% of postings close within 7 days. Measured by our own scanner across the market. Jobgether postings stay open a median of 6 days.

Share of postings closed within
  1. 1.8%1 day
  2. 4.0%3 days
  3. 8.5%7 days
  4. 15.4%14 days
  5. 34.1%30 days
This job: posted 6 hours ago

Jobgether median: 6 days open

The posting

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior Customer AI Engineer – Token Factory based in Germany.

Join an innovative AI infrastructure environment focused on helping businesses bring advanced AI applications from experimentation to reliable production at scale. In this role, you will bridge engineering, delivery, and customer success, ensuring AI workloads perform efficiently and reliably in real-world environments. You will guide customers through the transition from proof of concept to production while optimizing performance, scalability, cost, and system reliability. Working closely with customer engineering teams and internal product and infrastructure specialists, you will troubleshoot complex challenges and deliver practical technical solutions. You will also play a key role in managing production incidents and identifying opportunities for continuous improvement. This is an opportunity to combine deep technical expertise, customer collaboration, and end-to-end ownership while contributing to the evolution of modern AI infrastructure.

Accountabilities

  • Lead the transition from proof of concept to production Own the customer journey from initial proof of concept (PoC) through production deployment and ongoing scaling. Ensure customer AI workloads are deployed successfully, remain stable, and scale to meet evolving business requirements. Accelerate time-to-production and time-to-value by identifying and addressing technical obstacles throughout implementation. Optimize AI workload performance and reliability Develop a thorough understanding of customer architectures, AI use cases, and infrastructure requirements. Monitor and improve inference performance, including latency, throughput, resource utilization, and cost efficiency. Identify performance bottlenecks, investigate root causes, and implement practical solutions to improve system reliability and scalability. Apply best practices for inference frameworks and AI infrastructure to support efficient production workloads. Serve as a trusted technical partner Work directly with customer engineering teams, machine learning specialists, and other technical stakeholders to ensure successful AI deployments. Provide guidance on implementation best practices, performance optimization, troubleshooting, and production readiness. Translate complex technical challenges into clear recommendations and actionable solutions. Collaborate with Solution Architects and internal engineering teams to align customer requirements with platform capabilities. Coordinate production incidents and technical risks Act as a primary technical point of contact for production-related issues and deployment challenges. Coordinate incident investigation and resolution with internal Product, Infrastructure, and Engineering teams. Communicate clearly with customers during high-pressure situations, providing timely updates and driving issues toward resolution. Identify potential risks proactively and implement measures to minimize disruption to customer workloads. Drive continuous improvement and customer outcomes Identify opportunities to optimize existing deployments, improve customer outcomes, and expand the effective use of AI infrastructure. Gather structured feedback from real-world customer deployments and communicate insights to Product and Infrastructure teams. Contribute to improvements in platform capabilities, deployment practices, and operational processes. Help develop scalable approaches that improve the overall customer experience and support long-term adoption. Requirements: Practical experience with AI inference frameworks such as vLLM, TensorRT, or similar technologies, with an understanding of their application in production environments. Strong understanding of cloud infrastructure, distributed systems, or high-load applications, including the technical challenges associated with scalable production deployments. Familiarity with AI and machine learning workloads, particularly large language models (LLMs), model inference, and the infrastructure required to serve them efficiently. Proven ability to troubleshoot complex technical issues, investigate system behavior, identify performance bottlenecks, and develop effective solutions. Experience working directly with technical customers, such as software engineers, machine learning teams, or infrastructure specialists. Excellent communication skills, with the ability to explain complex technical concepts clearly and adapt communication to different audiences. A strong sense of ownership and accountability, with a focus on delivering measurable outcomes rather than simply completing assigned tasks. Ability to manage multiple customer engagements, competing priorities, and technical challenges in a fast-moving environment. A structured, proactive, and solution-oriented mindset, with the confidence to investigate problems independently and coordinate the right resources when needed. Strong collaboration skills and the ability to work effectively with customer engineering teams, Solution Architects, Product teams, and Infrastructure specialists. The following experience is considered an advantage: Hands-on experience with GPU workloads, AI infrastructure, or large-scale model inference environments. Previous experience in solutions engineering, site reliability engineering (SRE), or technical support within business-to-business (B2B) technology environments. Experience helping customers deploy, optimize, and maintain complex cloud-based or AI-powered applications in production. Benefits: Competitive compensation: An attractive compensation package aligned with your expertise and experience. Career growth: Opportunities to develop your technical expertise and progress professionally in a rapidly evolving AI infrastructure environment. Continuous learning: Exposure to advanced AI technologies, inference frameworks, and real-world production challenges. Remote work flexibility: Work remotely from within Europe, with the opportunity to manage your work effectively and independently. Ownership and autonomy: Take responsibility for customer outcomes and influence technical decisions that directly affect production success. Collaborative culture: Work alongside talented engineers and specialists in an international, innovative, and fast-moving environment. Meaningful technical impact: Help businesses move AI applications into production and improve the performance, reliability, and cost efficiency of their workloads. Cross-functional collaboration: Partner with customer engineering teams and internal specialists across product development, infrastructure, and AI engineering. Opportunity to shape AI infrastructure: Contribute insights from real-world customer deployments to improve platform capabilities and support the future of AI.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1

From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against Jobgether's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on Jobgether's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    Jobgether's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.