At a Glance
- Tasks: Develop and optimise AI agents for cybersecurity, enhancing detection and response capabilities.
- Company: Join Accenture, a global leader in professional services and innovation.
- Benefits: Enjoy a competitive salary, hybrid working, and opportunities for professional growth.
- Other info: Collaborative culture that values diversity and offers excellent career advancement.
- Why this job: Make a real impact in cybersecurity using cutting-edge AI technologies.
- Qualifications: 2+ years in AI/ML engineering with hands-on experience in production environments.
The predicted salary is between 63000 - 77000 £ per year.
Archer is collaborating with Accenture to connect them with exceptional professionals for this role.
- Role title: AI & ML Engineer (Cybersecurity)
- Please
Note: Any offer of employment is subject to satisfactory BPSS and SC security clearance which requires 5 years continuous UK address history (typically including no periods of 30 consecutive days or more spent outside of the UK) at the point of application.
Responsible for developing and optimising AI agents and LLM-powered applications that drive the maturation of Accenture’s Security Operation Centre (SOC) offerings.
Working closely with security engineers and SOC analysts, the AI/ML Engineer will design, build, and operationalise AI-powered workflows that integrate with our security tooling, to accelerate detection and response.
We are at a critical inflection point within defensive cyber operations; the use of AI to counter the rapidly evolving threat landscape is the mission, and we are looking for innovative and passionate people to support this effort.
You will bring strong engineering rigour and a security-first mindset to everything you build.
Responsibilities
- LLM Configuration: Configure, evaluate, and tune large language models for security use cases; including prompt engineering, system prompt design, retrieval-augmented generation (RAG), and tool/function calling.
- Agent
Development: Design, build, and maintain AI agents and agentic workflows using platforms such as Azure AI Foundry, integrating with security toolsets such as SOAR, SIEM, and EDR.
- Secure Configuration: Implement safeguards to protect against adversarial inputs, including prompt injection and jailbreaks, ensuring AI systems meet robust security standards.
- System Architecture: Architect AI solutions that are modular, maintainable, and built to scale, adhering to secure development principles.
- Governance: Implement solutions in line with our AI governance framework, encompassing factors such as data handling, audit logging, human-in-the-loop controls, and regulatory compliance.
- Cost
Management: Monitor and optimise LLM API usage and infrastructure costs, implementing strategies such as caching, model tiering, and guardrails to ensure solutions are economically viable.
- Collaboration: Work closely with key stakeholders to understand operational pain points, prototype solutions, and iterate based on feedback.
- Documentation: Produce clear technical documentation to support effective ongoing management of developed capabilities.
- We Are Looking For The Following Skills And Experience
- 2+ years of experience within AI/ML engineering.
- Hands-on experience building and deploying AI agents or LLM-powered applications in production environments, and the implementation of appropriate observability and evaluation mechanisms.
- Practical experience with enterprise AI platforms, such as Azure AI Foundry, AWS Bedrock or Google Vertex AI.
- Strong understanding of LLM concepts and vector databases: context windows, temperature and sampling parameters, system prompts, tool/function calling.
- Experience of implementing RAG pipelines end-to-end, including data ingestion, chunking strategies, embedding model selection, and retrieval tuning.
- Experience of implementing parsing pipelines for tasks such as document processing / ingestion, including handling unstructured data.
- Demonstrable knowledge of AI security risks (familiarity with OWASP LLM Top 10), and how these can be mitigated.
- Experience working within enterprise governance frameworks.
- Proficiency in one or more languages (such as Python), and familiarity with common AI/ML libraries. Ability to build custom tools that can interact with, or be exposed to LLMs.
- Strong understanding of REST APIs, and the ability to integrate AI solutions with third-party platforms and internal tooling.
- Experience of deploying infrastructure-as-code is advantageous.
- Knowledge of typical enterprise security tooling (such as SOAR, SIEM and EDR) is advantageous.
- Collaborative and engaging approach to problem solving, and a willingness to work as part of the team.
- Passionate for diversity, recognising the innovation and competitive edge that comes from a diverse highly skilled team where equal opportunities are truly valued.
- A problem-solver, always seeking the best solution for the right outcome.
- Self-motivated, results-focussed, pragmatic with the ability to manage conflicting deadlines and prioritise.
- About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale.
We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries.
Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships.
We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability.
Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships.
We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.
- Visit us at
- Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences.
All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, sexual orientation, gender identity or expression, marital status, citizenship status or any other basis as protected by applicable law.
Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
AI/ML Engineer in Cheltenham employer: Archer
Archer is an exceptional employer located in the innovative hub of San Jose, California, where we are at the forefront of sustainable air mobility. Our collaborative work culture fosters diversity and creativity, providing employees with ample opportunities for professional growth and development in the aerospace industry. With a commitment to employee well-being and inclusivity, Archer offers a unique chance to contribute to groundbreaking technology while enjoying a supportive and dynamic workplace.
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We think this is how you could land AI/ML Engineer in Cheltenham
✨Join Local Tech Meetups
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✨Contribute to Open Source Projects
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We think you need these skills to ace AI/ML Engineer in Cheltenham
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Archer.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Archer and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Archer
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Archer uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.