At a Glance
- Tasks: Design and deploy cutting-edge AI solutions using AWS technologies.
- Company: Join a forward-thinking tech consultancy focused on innovative AI.
- Benefits: Competitive day-rate, remote work, and continuous learning opportunities.
- Other info: Collaborative culture with opportunities for career growth.
- Why this job: Make a real impact by building enterprise-scale AI systems.
- Qualifications: Experience in AI applications, AWS, and strong Python skills required.
The predicted salary is between 63000 - 77000 £ per year.
Join a technology consultancy delivering cutting-edge AI solutions for enterprise clients. This is an opportunity to build production-grade agentic AI systems using the latest AWS technologies, helping organisations turn AI ambition into real-world business outcomes.
Role Overview
Location: Fully Remote
Day-Rate: Competitive - Outside IR35
Industry: Technology / AI & Cloud Consulting
What You’ll Be Doing
- Design, build and deploy production-ready agentic AI solutions using Amazon Bedrock and the wider AWS ecosystem.
- Develop multi-agent architectures, orchestration frameworks and intelligent workflows that solve complex business challenges.
- Build and maintain Model Context Protocol (MCP) servers to enable seamless integration across AI platforms.
- Design scalable Retrieval-Augmented Generation (RAG) solutions, managing knowledge bases, vector stores and document ingestion pipelines.
- Integrate Large Language Models into enterprise applications through prompt engineering, tool calling and context management.
- Build secure, scalable AI back-end services using AWS Lambda, DynamoDB, S3 and other serverless technologies.
- Implement monitoring, tracing and observability to ensure AI applications are reliable, performant and production-ready.
- Work closely with engineering, product and client teams to shape AI architectures and contribute to technical strategy.
- Support the delivery of innovative AI capabilities from concept through to production deployment.
Main Skills Needed
- Proven experience delivering production-grade AI applications using Amazon Bedrock.
- Strong background designing and implementing agentic AI and multi-agent systems.
- Hands-on experience building or integrating MCP (Model Context Protocol) servers.
- Experience developing RAG architectures, knowledge bases and vector search solutions.
- Strong Python development skills within AI and cloud environments.
- Solid understanding of AWS services, particularly Lambda, DynamoDB and S3.
- Experience integrating LLMs using prompt engineering, context management and function calling techniques.
- Knowledge of observability, monitoring and tracing tools such as CloudWatch.
- Strong software engineering principles with a focus on scalable, maintainable production systems.
- AWS certifications, particularly AI/ML Speciality, would be advantageous.
What’s in It for You
- Work on genuinely innovative AI projects using some of the latest technologies in the AWS ecosystem.
- Build enterprise-scale AI solutions that move beyond proof of concept into real production environments.
- Collaborate with experienced engineers, architects and AI specialists on challenging client engagements.
- Influence technical direction while working at the forefront of agentic AI and cloud engineering.
- Continuous learning opportunities with access to emerging AI technologies and best practices.
- Hybrid working and a collaborative, engineering-first culture.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
AI / ML Specialist employer: Addition+
Addition is an exceptional employer that fosters a dynamic work culture in the heart of London, where innovation meets collaboration. With a strong emphasis on professional development, employees are encouraged to grow their skills and advance their careers while enjoying competitive salaries and flexible working arrangements. Joining Addition means being part of a forward-thinking team dedicated to making a meaningful impact in the cyber security landscape.
StudySmarter Expert Advice🤫
We think this is how you could land AI / ML Specialist
✨Get Involved in Data Science Meetups
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We think you need these skills to ace AI / ML Specialist
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Addition+, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Addition+. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Addition+
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Addition+!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
