Senior AI Consultant

Senior AI Consultant

Bristol Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Design and deploy AI applications using AWS, integrate APIs, and build intelligent systems.
  • Company: Snap Analytics is a high-growth consultancy transforming data into actionable insights for enterprise clients.
  • Benefits: Enjoy hybrid work, competitive salary, mentorship, and a culture of innovation and continuous learning.
  • Why this job: Shape the future of AI tools, collaborate with experts, and drive real business impact.
  • Qualifications: Experience with AWS, API integration, Python, and a passion for scalable AI solutions required.
  • Other info: Join a diverse team dedicated to solving complex data challenges globally.

The predicted salary is between 60000 - 80000 £ per year.

Join to apply for the Senior AI Consultant role at Snap Analytics Get AI-powered advice on this job and more exclusive features. We’re looking for a skilled and inquisitive AI Engineer to join our small but growing AI & Advanced Analytics team at Snap Analytics. In this role, you’ll be at the heart of building intelligent applications powered by cutting-edge AI models and cloud-native infrastructure. You’ll work on innovative projects that harness the power of LLMs, API integrations, and real-time data pipelines to solve real-world business problems for enterprise clients. You’ll be part of a collaborative and forward-thinking team, with mentorship from experienced professionals while having the autonomy to drive technical design and experimentation. If you’re passionate about creating scalable, intelligent systems using the latest in AWS, vector databases, and AI orchestration, we’d love to hear from you. Application Deadline: June 13, 2025 Department: Delivery Employment Type: Full Time Location: Bristol, UK Workplace type: Hybrid Compensation: £70,000 – £90,000 / year Reporting To: Calvin Fuss What you\’ll be doing… Designing and deploying AI applications using AWS Bedrock and serverless architecture You’ll take ownership of designing scalable, secure, and cost-effective AI-driven applications that leverage tools like Lambda, DynamoDB, and Redshift. Integrating APIs from LLM providers and other external data services You\’ll connect a variety of APIs (including Claude, OpenAI and others) to enable dynamic conversational agents and intelligent automation. Building Retrieval-Augmented Generation pipelines You\’ll design smart knowledge retrieval systems using vector databases to enhance the relevance and accuracy of AI model outputs. Writing clean, production-ready Python code You’ll use Python to build and orchestrate AI workflows, integrate APIs, manage data pipelines, and support cloud-native deployments. Your code will be critical in ensuring reliability, scalability, and performance across all AI systems. Developing and maintaining vector-based data storage and indexing systems You’ll build robust pipelines to ensure fast and reliable access to large, unstructured datasets for use by AI applications. Diagnosing and mitigating hallucinations in language models By analysing model responses and post-conversation data, you’ll help ensure outputs are grounded, verifiable, and aligned with business expectations. Collaborating across teams You’ll work closely with data scientists, product managers, and engineers to ensure AI solutions are robust, explainable, and production ready. Applying MLOps and CI/CD best practices You’ll contribute to scalable ML workflows that ensure fast iteration, effective monitoring, and smooth deployment of AI features. Working with additional tools and platforms (bonus) Familiarity with Claude, Anzo or AWS Redshift is a plus – and you’ll have the opportunity to deepen your expertise on the job. What you\’ll need to succeed… Experience working with cloud infrastructure, especially AWS services like Bedrock, Lambda, and serverless stacks. Proficiency in API development and integration, particularly in connecting LLM APIs to external systems. Strong understanding of retrieval-augmented generation (RAG) frameworks and vector databases. Proficiency in Python for developing scalable data and AI solutions, including experience with data processing libraries, API interaction, and structuring clean, maintainable code in a production environment. Familiarity with large language models, prompt engineering, and agent orchestration. The ability to analyse post-interaction data and optimise AI behaviour over time. A structured, problem-solving mindset with a focus on scalability and performance. A desire to collaborate in a cross-functional environment, sharing ideas and learning as part of a team. Bonus points for experience with Claude, AWS Redshift, or graph-based systems like Anzo. So, what\’s in it for you? The chance to shape the next generation of AI-powered enterprise tools with real business impact. Autonomy to experiment with new technologies and deploy scalable applications in production. Exposure to advanced AWS tools and mentorship from experienced AI and cloud professionals. A culture of innovation and continuous learning, where your growth is supported. A collaborative, inclusive, and impact-driven environment where your ideas are valued. About Snap Analytics We\’re a high-growth data analytics consultancy on a mission to help enterprise businesses unlock the full potential of their data. With offices in the UK, India, and South Africa, we specialise in cutting-edge cloud analytics solutions, transforming complex data challenges into actionable business insights. We partner with some of the biggest brands worldwide to modernise their data platforms, enabling smarter decision-making through Snowflake, Databricks, Matillion, and other cloud technologies. Our approach is customer-first, innovation-driven, and results-focused, delivering impactful solutions with speed and precision. At Snap, we’re not just consultants—we’re problem-solvers, engineers, and strategists who thrive on tackling complex data challenges. Our culture is built on collaboration, continuous learning, and pushing boundaries, ensuring our people grow just as fast as our business. Join us and be part of a team that’s shaping the future of data analytics! #J-18808-Ljbffr

Senior AI Consultant employer: Snap Analytics

Snap Analytics is an exceptional employer, offering a dynamic and inclusive work culture that fosters innovation and collaboration. As a Senior AI Consultant in Bristol, you'll enjoy the autonomy to drive impactful projects while receiving mentorship from seasoned professionals, ensuring your growth in the rapidly evolving field of AI. With a commitment to continuous learning and exposure to cutting-edge technologies, Snap Analytics empowers you to shape the future of data analytics in a supportive environment.
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Contact Detail:

Snap Analytics Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Senior AI Consultant

✨Tip Number 1

Familiarise yourself with AWS services, especially Bedrock and Lambda. Understanding these tools will not only help you in interviews but also demonstrate your readiness to hit the ground running in the role.

✨Tip Number 2

Showcase your experience with API integrations, particularly with LLM providers like OpenAI. Be prepared to discuss specific projects where you've successfully connected APIs to enhance functionality.

✨Tip Number 3

Brush up on retrieval-augmented generation (RAG) frameworks and vector databases. Being able to articulate how these technologies work and their applications will set you apart from other candidates.

✨Tip Number 4

Prepare to discuss your problem-solving approach and how you've optimised AI behaviour over time. Real-world examples of diagnosing and mitigating issues in language models will be particularly impressive.

We think you need these skills to ace Senior AI Consultant

AWS Bedrock
Serverless Architecture
API Development and Integration
Python Programming
Data Processing Libraries
Retrieval-Augmented Generation (RAG)
Vector Databases
Cloud Infrastructure Management
AI Workflow Orchestration
Data Pipeline Management
Post-Interaction Data Analysis
Problem-Solving Mindset
Collaboration in Cross-Functional Teams
Experience with Large Language Models
Prompt Engineering
MLOps Best Practices
CI/CD Implementation

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in AI, cloud infrastructure, and Python programming. Use keywords from the job description to demonstrate that you meet the specific requirements for the Senior AI Consultant role.

Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and your problem-solving mindset. Mention specific projects or experiences that align with the responsibilities listed in the job description, such as designing AI applications or integrating APIs.

Showcase Technical Skills: In your application, emphasise your proficiency with AWS services, API development, and retrieval-augmented generation frameworks. Provide examples of how you've used these skills in previous roles to solve real-world problems.

Highlight Collaborative Experience: Since the role involves working closely with cross-functional teams, include examples of past collaborations. Discuss how you contributed to team projects and what you learned from those experiences to show your ability to work in a collaborative environment.

How to prepare for a job interview at Snap Analytics

✨Showcase Your Technical Skills

Be prepared to discuss your experience with AWS services, particularly Bedrock and Lambda. Highlight specific projects where you've designed scalable AI applications or integrated APIs, as this will demonstrate your hands-on expertise.

✨Demonstrate Problem-Solving Abilities

Expect questions that assess your problem-solving mindset. Prepare examples of how you've tackled challenges in AI development, especially regarding hallucinations in language models or optimising AI behaviour over time.

✨Emphasise Collaboration Experience

Since the role involves working closely with cross-functional teams, share experiences where you've collaborated with data scientists, product managers, or engineers. This will show your ability to work effectively in a team-oriented environment.

✨Prepare for Technical Questions

Brush up on retrieval-augmented generation frameworks and vector databases. Be ready to explain these concepts clearly, as well as your approach to writing clean, production-ready Python code, which is crucial for the role.

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