At a Glance
- Tasks: Help customers succeed by creating innovative tech solutions and guiding them through implementation.
- Company: Join a leading tech company focused on Generative AI and Google Cloud solutions.
- Benefits: Enjoy remote work flexibility, professional development, and a Macbook laptop.
- Why this job: Be part of a dynamic team driving innovation in AI while building strong customer relationships.
- Qualifications: Bachelor's degree in Computer Science or related field; 3+ years in a technical customer-facing role.
- Other info: Opportunity to work with cutting-edge technologies and make a real impact in the industry.
The predicted salary is between 36000 - 60000 £ per year.
As a Customer Engineer, you will be a key player in driving our customers' success by translating their business needs into innovative and effective technical solutions. You will partner with sales teams to understand customer challenges, design and present compelling solutions, and guide customers through the implementation and adoption of our products and services, with a focus on Generative AI solutions on Google Cloud. This role requires a blend of technical depth, business acumen, and strong communication skills, with a specialization in applying Generative AI technologies to solve complex business problems.
A Customer Engineer needs a blend of strong technical skills in cloud-native technologies, including AI/ML, and excellent communication and problem-solving abilities to assist customers with their cloud solutions.
Core Focus:- Google Cloud Platform (GCP) Expertise
- Cloud-Native Proficiency: Kubernetes, containers, and serverless architectures.
- GCP Service Mastery: Deep knowledge of core GCP services (Compute Engine, Storage, SQL, BigQuery, etc.), with a strong emphasis on Vertex AI and other AI/ML offerings.
- Vertex AI: Expertise in building, deploying, and scaling machine learning models with Vertex AI, including AutoML, custom training, and pre-trained models.
- Understanding of Vertex AI's role in enabling generative AI solutions.
- GCP AI/ML Services: Knowledge of other relevant Google Cloud AI/ML services and APIs (e.g., Natural Language API, Vision API).
- Infrastructure Automation: IaC with Terraform or Cloud Deployment Manager.
- Cloud Solution Design: Building scalable, secure, and resilient cloud architectures, including designing AI/ML infrastructure.
- Data Handling: Big data analytics, warehousing, and ETL/ELT processes, with a focus on leveraging data for AI/ML.
- Network & Security: Comprehensive understanding of cloud networking and security principles, including security best practices for AI/ML workloads.
- Database Management: Experience with SQL and NoSQL databases, including database solutions for AI/ML applications (e.g., vector databases).
- Customer Engagement: Partner with sales teams to identify and qualify business opportunities and understand key customer technical objections, with a focus on Generative AI opportunities.
- Develop strategies to overcome technical blockers and drive solution adoption, specifically for Generative AI solutions.
- Build and maintain strong relationships with key technical stakeholders and executive leaders at customer organizations, with an emphasis on understanding their Generative AI needs.
- Solution Design & Architecture: Analyze customer business and technical requirements to design comprehensive solutions that address their needs, with a focus on Generative AI use cases.
- Develop and present solution architectures, including diagrams, documentation, and best practices, with a focus on integrating Generative AI components.
- Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to successfully implement solutions, including Generative AI solutions.
- Technical Leadership: Provide deep technical expertise to support customer engagements, including technology advocacy, product and solution briefings, and proofs-of-concept, with a focus on Google Cloud's Generative AI capabilities.
- Guide customers through assessments of their existing environments and provide recommendations for modernization and optimization, including incorporating Generative AI.
- Stay up-to-date on industry trends and emerging technologies, especially in Generative AI, and drive innovation and best practices.
- Collaboration: Work closely with product management and engineering teams to prioritize customer needs and influence product development, including requirements for Generative AI products and services.
- Collaborate with internal teams and partners to ensure successful solution delivery and customer satisfaction, including Generative AI solutions.
- Share knowledge and best practices with the broader team and contribute to the development of internal tools and processes, including those related to Generative AI.
- Pre-sales Support: Participate in the technical aspects of Request for Proposals (RFPs), including those involving Generative AI solutions.
- Conduct product demonstrations and prototypes in customer environments, showcasing Google Cloud's Generative AI offerings.
- Experience in writing Statements of Work (SOWs) that clearly define project scope, deliverables, and timelines.
- Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience preferred.
- 3 + years of experience in a customer-facing technical role, such as solutions architect, sales engineer, or consultant.
- Strong understanding of cloud computing concepts, platforms, and services (preferably Google Cloud).
- Scripting: Proficiency in Python, Go, or Bash for automation.
- Problem-Solving: Strong troubleshooting and diagnostic abilities.
- Communication: Clear communication of complex technical information.
- Customer Service: Effective interaction and support for clients.
- DevOps Practices: Familiarity with DevOps principles and tools.
- Experience in migrating applications and services to cloud platforms.
- Experience with networking concepts such as software-defined networking, routing, virtual private networks, load balancers, and firewalls.
- Experience with security concepts such as encryption, identity management, access control, attack vectors, and penetration testing.
- Excellent presentation, communication, and interpersonal skills.
- Ability to travel to customer sites as needed.
- Medical, Dental, Vision
- PTO
- Pension
- Professional Development
- Macbook Laptop
- Remote work flexibility
Customer Engineer (UK) employer: WALT Labs
Contact Detail:
WALT Labs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Customer Engineer (UK)
✨Tip Number 1
Familiarise yourself with Google Cloud Platform (GCP) and its core services, especially Vertex AI. Understanding how to leverage these tools for Generative AI solutions will give you a significant edge during interviews.
✨Tip Number 2
Engage in networking within the cloud computing community. Attend meetups or webinars focused on GCP and Generative AI to connect with industry professionals who can provide insights and potentially refer you to opportunities.
✨Tip Number 3
Prepare to discuss real-world applications of Generative AI in business contexts. Be ready to share examples of how you've solved complex problems using AI/ML technologies, as this will demonstrate your practical experience and understanding.
✨Tip Number 4
Showcase your communication skills by practising how to explain technical concepts to non-technical stakeholders. This is crucial for a Customer Engineer role, where you'll need to bridge the gap between technology and business needs.
We think you need these skills to ace Customer Engineer (UK)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in cloud-native technologies, AI/ML, and customer-facing roles. Emphasise any specific projects or achievements related to Google Cloud Platform and Generative AI.
Craft a Compelling Cover Letter: In your cover letter, express your passion for technology and customer success. Discuss how your skills align with the responsibilities of the Customer Engineer role, particularly your experience with GCP and Generative AI solutions.
Showcase Technical Skills: Clearly outline your technical skills in your application. Mention your proficiency in Kubernetes, Terraform, and any relevant programming languages like Python or Go. Highlight your understanding of AI/ML services and how you've applied them in past roles.
Prepare for Technical Questions: Anticipate technical questions related to cloud architecture, AI/ML solutions, and customer engagement strategies. Be ready to discuss specific examples from your experience that demonstrate your problem-solving abilities and technical expertise.
How to prepare for a job interview at WALT Labs
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with Google Cloud Platform and Generative AI solutions. Highlight specific projects where you've successfully implemented cloud-native technologies, especially focusing on Vertex AI and other AI/ML services.
✨Understand Customer Needs
Demonstrate your ability to translate business needs into technical solutions. Prepare examples of how you've engaged with customers to identify their challenges and how you designed solutions that addressed those needs, particularly in the context of Generative AI.
✨Communicate Clearly and Effectively
Strong communication skills are crucial for this role. Practice explaining complex technical concepts in simple terms, as you'll need to present solutions to both technical and non-technical stakeholders.
✨Stay Updated on Industry Trends
Familiarise yourself with the latest developments in Generative AI and cloud technologies. Being knowledgeable about current trends will not only impress your interviewers but also show your commitment to continuous learning and innovation.