At a Glance
- Tasks: Join our Cloud Reliability Engineering team to architect and manage AI/ML cloud solutions.
- Company: DoiT is a global tech company helping businesses leverage the cloud for growth and innovation.
- Benefits: Enjoy unlimited vacation, flexible working options, health insurance, and a professional development stipend.
- Why this job: Make an impact while growing your skills in a supportive, inclusive environment with diverse perspectives.
- Qualifications: 4+ years of experience in cloud-based AI/ML solutions and AWS certifications required.
- Other info: Work remotely with a global team and embrace entrepreneurial spirit while having fun!
The predicted salary is between 48000 - 84000 £ per year.
Location: Our Senior Cloud Architect will be an integral part of our Cloud Reliability Engineering team in the UK, Ireland, Estonia, Netherlands, Sweden and Spain. The role is also available to contractors in other Eastern European locations / Portugal.
Who We Are: DoiT is a global technology company that works with cloud-driven organizations to leverage the cloud to drive business growth and innovation. We combine data, technology, and human expertise to ensure our customers operate in a well-architected and scalable state - from planning to production. Delivering DoiT Cloud Intelligence, the only solution that integrates advanced technology with human intelligence, we help our customers solve complex multicloud problems and drive efficiency. With decades of multicloud experience, we have specializations in Kubernetes, GenAI, CloudOps, and more. An award-winning strategic partner of AWS, Google Cloud, and Microsoft Azure, we work alongside more than 4,000 customers worldwide.
The Opportunity: As a Senior Cloud Architect, you will be part of our global CRE team, working with rapidly growing companies in EMEA and around the world. This role offers you the chance to:
- Apply your hands-on experience & skills in a consultative manner to address our customers’ strategic and tactical needs around cloud technologies.
- Grow your technical and interpersonal skills by addressing customer challenges in your daily work and leveraging dedicated time allocated by the company for learning new technologies and engaging in internal initiatives.
- Strengthen your personal brand through thought leadership activities such as blogging, public speaking, and participation in technology events.
Qualifications Experience Requirement:
- Minimum of 4+ years of experience in architecting, deploying, and managing cloud-based AI/ML solutions.
- Core AWS Expertise: Expertise in architecting, developing, and troubleshooting large production-grade distributed systems on AWS, and selecting the appropriate tools to address business problems at the correct scale. Advanced proficiency in AWS, with a focus on Generative AI and machine learning services. Certified AWS Solutions Architect Professional and/or AWS Machine Learning Specialty.
- Proven track record of architecting, deploying, and optimizing complex cloud solutions for AI-driven workloads.
- Generative AI and Cutting-Edge Technologies: Expertise in Amazon Bedrock for deploying foundation models and managing scalable GenAI workloads. Proficiency in fine-tuning and deploying Large Language Models (LLMs) and multimodal AI using Amazon SageMaker JumpStart and Hugging Face on AWS.
- Experience leveraging Amazon Q (formerly AWS CodeWhisperer) Business and Developer for AI-powered coding productivity and automation.
- Machine Learning Frameworks and Pipelines: In-depth knowledge of Amazon SageMaker, including Pipelines, Model Monitor, Data Wrangler, and SageMaker Clarify for bias detection and interpretability. Skilled in distributed model training with multi-GPU clusters and optimization for high-performance inference.
- Data Engineering and AI Workflow Optimization: Proficient in building data pipelines with Amazon S3, AWS Glue, Lake Formation, and Redshift for AI and ML workloads. Experienced in optimizing data preparation for large-scale AI model training and inference workflows.
- AI Integration and Deployment: Expertise in building end-to-end AI pipelines using AWS Lambda, Step Functions, and API Gateway for real-time AI inference and automation. Familiarity with containerized AI deployments using Amazon EKS and AWS Fargate.
- DevOps and MLOps Expertise: Hands-on experience with CI/CD pipelines for AI/ML workflows using AWS CodePipeline, CodeBuild, and SageMaker Pipelines. Proficiency in monitoring and maintaining AI systems with Amazon CloudWatch and SageMaker Model Monitor.
- AI Governance and Security: Strong understanding of AI governance, incorporating IAM, AWS Key Management Service (KMS), and compliance frameworks. Knowledgeable in AI ethics, bias detection, and accountability using tools like SageMaker Clarify.
- Emerging AI Trends: Up-to-date on Generative AI advancements such as RLHF (Reinforcement Learning with Human Feedback), foundation model fine-tuning, and hybrid AI architectures. Familiarity with integrating open-source tools like Hugging Face Transformers and AWS-native solutions.
- Knowledge of Multi-Cloud AI Tools: Good knowledge and understanding of Google Cloud AI tools such as Vertex AI, Cloud AutoML, and BigQuery ML, enabling effective integration in multi-cloud environments.
- Mentoring and Enablement Skills: Proven ability to mentor team members and enable cross-functional collaboration to foster technical growth and innovation. Skilled in creating knowledge-sharing platforms and hands-on workshops to enhance team capabilities.
Bonus Points:
- Passion for technology, with a demonstrated ability to quickly learn and stay up to date with industry trends.
- Data certification is a major advantage (e.g., Stanford, Coursera, Udacity, MIT, eCornell, or any Data certification with AWS/GCP).
- BA/BS degree in Computer Science, Mathematics, Economics, or a related technical field, or equivalent practical experience.
Be your truest self. Work on your terms. Make a difference. We are home to a global team of incredible talent who work remotely and have the flexibility to have a schedule that balances your work and home life. We embrace and support leveling up your skills professionally and personally.
What does being a Do’er mean? We’re all about being entrepreneurial, pursuing knowledge and having fun!
Unlimited Vacation, Flexible Working Options, Health Insurance, Employee Stock Option Plan, Professional Development Stipend.
DoiT unites as Many Do’ers, One Team, where diversity is more than a goal—it’s our strength. We actively cultivate an inclusive, equitable workplace, recognizing that each unique perspective enhances our innovation. By celebrating differences, we create an environment where every individual feels valued, contributing to our collective success.
Senior Cloud Architect, ML/AI (Romania) New Remote EMEA employer: Doit Intl
Contact Detail:
Doit Intl Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Cloud Architect, ML/AI (Romania) New Remote EMEA
✨Tip Number 1
Network with professionals in the cloud and AI/ML space. Attend relevant meetups, webinars, or conferences to connect with industry experts and learn about potential job openings at DoiT. Engaging with the community can provide valuable insights and recommendations.
✨Tip Number 2
Showcase your expertise by contributing to open-source projects or writing articles on platforms like Medium or LinkedIn. This not only demonstrates your knowledge but also helps you build a personal brand that aligns with DoiT's focus on thought leadership.
✨Tip Number 3
Stay updated on the latest trends in Generative AI and cloud technologies. Follow industry leaders on social media and subscribe to relevant newsletters to ensure you're well-informed, which will help you stand out during interviews.
✨Tip Number 4
Prepare for technical interviews by practising problem-solving scenarios related to cloud architecture and AI/ML solutions. Use platforms like LeetCode or HackerRank to sharpen your skills and be ready to demonstrate your capabilities effectively.
We think you need these skills to ace Senior Cloud Architect, ML/AI (Romania) New Remote EMEA
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in architecting and deploying AI/ML solutions, particularly on AWS. Use specific examples that demonstrate your expertise in Generative AI and cloud technologies relevant to the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for cloud technologies and how your skills align with DoiT's mission. Mention any relevant certifications, such as AWS Solutions Architect Professional, and how they enhance your ability to contribute to the team.
Showcase Your Thought Leadership: If you have experience in blogging or public speaking about cloud technologies, mention it in your application. This demonstrates your commitment to thought leadership and aligns with DoiT's values of innovation and knowledge sharing.
Highlight Mentoring Experience: If you've mentored others in cloud technologies or AI/ML, be sure to include this in your application. DoiT values collaboration and technical growth, so showcasing your ability to enable others will strengthen your application.
How to prepare for a job interview at Doit Intl
✨Showcase Your Cloud Expertise
Make sure to highlight your hands-on experience with AWS, especially in architecting and deploying AI/ML solutions. Be prepared to discuss specific projects where you've successfully implemented cloud technologies, focusing on the tools and services you used.
✨Demonstrate Problem-Solving Skills
During the interview, be ready to tackle hypothetical scenarios or case studies related to cloud architecture. This will allow you to showcase your analytical thinking and how you approach complex problems, particularly in a multicloud environment.
✨Emphasise Continuous Learning
DoiT values personal and professional development, so share examples of how you've kept up with emerging technologies in AI and cloud computing. Mention any relevant certifications or courses you've completed, especially those related to AWS or machine learning.
✨Prepare for Technical Questions
Expect in-depth technical questions about AWS services, Generative AI, and MLOps practices. Brush up on your knowledge of tools like Amazon SageMaker, AWS Lambda, and CI/CD pipelines, and be ready to explain your thought process clearly.