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- Tasks: Design and build AI-driven solutions using Azure tools, focusing on advanced analytics and machine learning.
- Company: Bytes is a leading IT solutions provider, dedicated to modernising infrastructures for SMEs and corporations.
- Benefits: Enjoy continuous training, a collaborative culture, and a range of wellbeing perks.
- Why this job: Join a dynamic team where innovation meets inclusivity, making a real impact in the tech world.
- Qualifications: 5+ years in data and AI engineering with strong Azure expertise and programming skills in Python or SQL.
- Other info: Ideal for tech-savvy individuals eager to advance their careers in a supportive environment.
The predicted salary is between 48000 - 84000 £ per year.
Bytes is a top provider of premium IT solutions and services, working with SMEs, corporations, and public sector organizations to modernize and digitally transform their IT infrastructures. Founded in 1982, Bytes has experienced significant growth, now employing over 750 people across seven locations in the UK and Ireland, with a turnover surpassing £1.8 billion in 2023. At Bytes, we nurture talented individuals to achieve remarkable outcomes and are dedicated to supporting our employees through continuous training, guidance, and development to help you advance and fulfil your career goals. We foster a culture of innovation, collaboration, recognition and inclusivity and offer a wide range of benefits to support staff wellbeing.
PURPOSE OF JOB: We’re looking for an experienced Azure Data & AI Engineer with a strong focus on advanced analytics, machine learning, and applied AI - particularly Generative AI. This role will suit a technically capable professional who combines real-world AI/ML solution delivery experience with a solid understanding of the Azure ecosystem.
The ideal candidate will bring hands-on expertise in designing and building AI-driven solutions using Azure-native tools and frameworks such as Azure OpenAI, Prompt Flow, Semantic Kernel, Azure AI SDKs (including azure-ai-projects, azure-ai-inference), and open-source frameworks like LangChain. Familiarity with traditional Azure AI services (e.g. Document Intelligence, Vision, Language, and Speech) is expected, alongside a developer-oriented mindset (code-first) and experience with integrating AI workloads into secure, scalable Azure environments.
The role requires deep platform knowledge - especially across Azure security, identity and networking (e.g., IAMs, Private Endpoints), resource management (e.g., Storage Accounts, Azure Key Vault), and telemetry via Application Insights or Log Analytics.
KEY RESPONSIBILITIES:
- Have 5+ years of technical consulting or a similar chronology of demonstrable success in coding and deploying Data and AI models onto Azure environments.
- At least one year using Azure Fabric.
- Create scalable and reliable data pipelines for data processing, transformation, and storage.
- Establish and enforce data governance policies and be ‘hands-on’ in exploratory data analysis to identify and measure quality gaps that are a block to Data and AI implementation.
- Implement robust security measures to protect sensitive data within Azure environments.
- Integrate AI and machine learning models into data pipelines and applications.
- Develop and deploy AI solutions using Azure Machine Learning services.
- Have a knowledge of top ML libraries scalable across multiple CPUs and GPUs, such as TensorFlow, PyTorch, Keras, OpenAI, XGBoost, and have used these in a commercial setting.
- Troubleshoot and resolve issues related to data processing and AI model performance.
- Collaborate with cross-functional teams to understand data requirements.
- Be able to troubleshoot clients' Data and AI code scripts and make quality, performance, and efficiency recommendations.
INDIVIDUAL RESPONSIBILITIES:
- Ability to independently analyse and solve complex data and AI engineering challenges.
- Stay updated on the latest Azure data and AI technologies and best practices.
- Proactively identify opportunities to enhance skills and knowledge.
- Effectively communicate technical concepts to both technical and non-technical stakeholders.
- Collaborate with team members to share insights and contribute to a knowledge-sharing culture.
QUALIFICATIONS, EXPERIENCE, & SKILLS:
- Professional Qualifications: Relevant Azure certifications such as DP-100 and AI-102 - DESIRABLE
- Years of Experience: 5+ years working with production data workloads in Azure - ESSENTIAL
- Other Requirements: Proficiency in Azure data services (Azure Data Factory, Azure Databricks, Azure Synapse Analytics, etc.) - ESSENTIAL
- Experience with AI development using Azure Machine Learning - ESSENTIAL
- Strong programming skills in languages such as Python, SQL, or C# - ESSENTIAL
CORE COMPETENCIES & SKILLS:
- Expertise in designing and implementing data models and data warehousing solutions.
- Knowledge of machine learning algorithms and experience in deploying models in production.
- In-depth understanding of Azure services and capabilities related to data and AI.
- Ability to analyse complex problems and develop innovative, scalable solutions.
- Proven ability to work effectively in a collaborative, cross-functional team environment.
Data & AI Engineer employer: Bytes Software Services
Contact Detail:
Bytes Software Services Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data & AI Engineer
✨Tip Number 1
Familiarise yourself with the specific Azure tools mentioned in the job description, such as Azure OpenAI and Azure Machine Learning services. Having hands-on experience or projects that showcase your skills with these tools can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the data and AI field, especially those who work with Azure. Attend relevant meetups, webinars, or conferences to connect with potential colleagues or mentors who can provide insights into Bytes' culture and expectations.
✨Tip Number 3
Stay updated on the latest trends in AI and machine learning, particularly around Generative AI. Being able to discuss recent advancements or case studies during interviews can demonstrate your passion and commitment to the field.
✨Tip Number 4
Prepare to discuss your previous experiences in detail, especially any challenges you've faced in deploying AI solutions on Azure. Use the STAR method (Situation, Task, Action, Result) to structure your responses and highlight your problem-solving skills.
We think you need these skills to ace Data & AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in Azure Data and AI engineering. Focus on specific projects where you've implemented machine learning solutions or worked with Azure-native tools, as this will resonate with Bytes' requirements.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data and AI engineering. Mention your familiarity with Azure services and how your skills align with Bytes' mission to modernise IT infrastructures. Be sure to include examples of your hands-on experience with AI-driven solutions.
Showcase Relevant Projects: If you have a portfolio or GitHub repository, include links to projects that demonstrate your expertise in building AI models and data pipelines using Azure. This practical evidence can set you apart from other candidates.
Highlight Continuous Learning: Bytes values continuous training and development. Mention any recent courses, certifications, or workshops you've completed related to Azure, machine learning, or data engineering. This shows your commitment to staying updated in the field.
How to prepare for a job interview at Bytes Software Services
✨Showcase Your Azure Expertise
Make sure to highlight your hands-on experience with Azure services, especially those mentioned in the job description. Be prepared to discuss specific projects where you've implemented Azure-native tools and frameworks, as this will demonstrate your technical capability.
✨Demonstrate Problem-Solving Skills
Prepare examples of complex data and AI engineering challenges you've faced and how you resolved them. This will show your analytical skills and ability to think critically under pressure, which is crucial for the role.
✨Communicate Clearly
Practice explaining technical concepts in a way that non-technical stakeholders can understand. This is important as the role requires collaboration with cross-functional teams, and clear communication can set you apart from other candidates.
✨Stay Updated on Trends
Research the latest trends in Azure data and AI technologies. Being knowledgeable about current advancements will not only impress your interviewers but also show your commitment to continuous learning and professional development.
