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- Tasks: Lead AI exploration, development, and integration to enhance customer experiences.
- Company: Join a tech-forward financial services organisation on a transformative journey.
- Benefits: Enjoy hybrid working, competitive salary, and opportunities for professional growth.
- Why this job: Be the first AI Engineer, shaping innovative solutions in a collaborative environment.
- Qualifications: Experience in AI/ML model development, strong Python skills, and a relevant degree required.
- Other info: No financial services experience needed; just a passion for AI innovation!
The predicted salary is between 36000 - 60000 £ per year.
My client is embarking on a transformative journey and is seeking their first AI Engineer to lead the exploration, development, and integration of artificial intelligence solutions across the business. This is a rare greenfield opportunity to define how AI can drive automation, efficiency, and enhanced customer experiences in a fast-moving financial services environment.
As the AI Engineer, you will be responsible for identifying high-impact use cases, building proof-of-concepts, and deploying scalable AI models. You’ll work closely with stakeholders across technology, operations, data, and compliance to ensure AI initiatives are innovative, responsible, and aligned with strategic goals.
Key Responsibilities:- Research and prototype AI/ML models to address business challenges (e.g., process automation, predictive analytics, customer service optimisation)
- Develop and deploy machine learning models using modern tools (e.g., Python, TensorFlow, PyTorch, Scikit-learn)
- Collaborate with data engineers to prepare and manage training datasets
- Integrate AI solutions with existing applications and infrastructure
- Partner with stakeholders to understand requirements, identify opportunities, and communicate results clearly
- Stay current with AI trends, tools, and ethical considerations in applied machine learning
- Lay the groundwork for a scalable AI strategy and help build internal capability
- Proven experience developing and deploying AI/ML models in a commercial setting
- Strong programming skills in Python and familiarity with ML libraries and frameworks
- Solid understanding of statistical modelling, natural language processing (NLP), and/or deep learning
- Experience working with structured and unstructured data sources
- Familiarity with MLOps practices and tools (e.g., model versioning, CI/CD for ML, cloud deployment)
- Excellent communication and stakeholder engagement skills
- Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field
- Experience in financial services is a plus but not required
- Be the AI pioneer in a tech-forward, ambitious organisation
- Shape the roadmap and vision for how AI is used across the business
- Work in a collaborative environment that values innovation and experimentation
- Hybrid working with flexibility and strong leadership support
- Competitive salary and opportunities for professional growth
Interested in being the first to lead AI innovation at my client’s organisation? Apply now and help shape the future.
Contact Detail:
Adria Solutions Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer
✨Tip Number 1
Familiarise yourself with the latest AI trends and tools relevant to the financial services sector. This will not only help you understand the landscape but also allow you to engage in meaningful conversations with stakeholders during interviews.
✨Tip Number 2
Build a portfolio showcasing your AI/ML projects, especially those that demonstrate your ability to solve real business problems. Highlight any proof-of-concept work or models you've developed, as this will set you apart from other candidates.
✨Tip Number 3
Network with professionals in the AI and financial services fields. Attend industry meetups, webinars, or conferences to connect with potential colleagues and learn about the challenges they face, which can inform your approach during interviews.
✨Tip Number 4
Prepare to discuss how you would approach integrating AI solutions within existing infrastructures. Think about specific examples where you've successfully collaborated with cross-functional teams, as this will demonstrate your stakeholder engagement skills.
We think you need these skills to ace AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AI/ML models, programming skills in Python, and familiarity with relevant libraries. Use specific examples from your past work to demonstrate your capabilities.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background aligns with their needs, particularly in developing and deploying AI solutions. Mention any relevant projects or achievements.
Showcase Relevant Skills: Clearly outline your technical skills related to AI and machine learning, such as experience with TensorFlow, PyTorch, or Scikit-learn. Highlight your understanding of statistical modelling and natural language processing.
Prepare for Potential Questions: Anticipate questions related to AI trends, ethical considerations, and your approach to stakeholder engagement. Be ready to discuss how you would identify high-impact use cases and integrate AI solutions within the organisation.
How to prepare for a job interview at Adria Solutions Ltd
✨Showcase Your AI Knowledge
Make sure to brush up on the latest trends and technologies in AI and machine learning. Be prepared to discuss specific models you've worked with, such as TensorFlow or PyTorch, and how they can be applied to solve business challenges.
✨Demonstrate Problem-Solving Skills
Prepare examples of high-impact use cases you've identified in previous roles. Discuss how you approached these challenges, the solutions you developed, and the results achieved to showcase your ability to drive innovation.
✨Communicate Clearly with Stakeholders
Since collaboration is key in this role, practice explaining complex AI concepts in simple terms. Be ready to discuss how you would engage with different stakeholders to understand their needs and communicate your findings effectively.
✨Highlight Your Programming Proficiency
Be ready to demonstrate your programming skills, particularly in Python. You might be asked to solve a coding problem or discuss your experience with machine learning libraries, so ensure you're comfortable discussing your technical expertise.