At a Glance
- Tasks: Deploy and scale AI platforms within client teams, driving real business outcomes.
- Company: Join a leading tech firm revolutionising AI deployment in enterprises.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Be part of a dynamic team defining the future of AI engineering.
- Why this job: Make a tangible impact on AI solutions in diverse industries while shaping the future of technology.
- Qualifications: Experience with cloud-native systems and AI platforms; strong problem-solving skills.
The predicted salary is between 80000 - 100000 £ per year.
This is not a consulting role. It is not a project delivery role. It is not a research position. A Forward Deployed AI Engineer is a production engineer who works embedded inside a client's enterprise, shoulder to shoulder with their teams, to make complex AI platforms work in real, messy organizational environments.
You own outcomes: time-to-value, adoption, reliability, and scalability. Not delivery milestones. Outcomes. The market is beginning to understand what leading technology companies have demonstrated: AI products fail not because the models are weak but because deployment is broken. The gap between a successful AI pilot and an AI capability that scales is bridged by engineers who can translate platform capability into measurable business value inside a real enterprise environment. That is this role. Forward Deployed AI Engineers form the execution spine of our Reinvention Deployment Engineering pods. We are building the largest FDE capability in the services industry. The engineers who join at this stage will define what the role looks like at scale and will have access to the hardest enterprise AI problems in the market across every industry.
Key Responsibilities
- Embed directly with client engineering and business teams to deploy, scale, and operationalize AI platforms - Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, or Palantir - inside enterprise environments.
- Own production outcomes end-to-end: time-to-value, reliability, adoption velocity, and scalability, with business metrics attached - not just delivery milestones.
- Move from ambiguous business problem to working production system through rapid experimentation: days to prototype, weeks to production-ready.
- Design and govern AI architectures across the full enterprise stack: identity, data, security, governance, platform layer, and workflow integration.
- Translate technical architecture into business impact for client CTO, CFO, and CISO; shape use case roadmaps, ROI backlogs, and AI adoption strategy.
- Build reusable patterns, playbooks, and accelerators that the client owns after you leave - enabling the client team to run it without you.
- Lead design workshops, proofs of concept, architecture walkthroughs, and code-with sessions with client engineering and leadership teams.
- Codify patterns and delivery learnings that scale across engagements and contribute to the growth of the FDE practice.
Basic Qualifications
- Engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).
- Deep expertise in designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments.
- Experience with AI platforms - OpenAI, Claude, Vertex AI, plus open-source models - including building abstraction layers to manage multi-provider pipelines.
- Experience deploying to production, CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging.
- Demonstrated end-to-end delivery ownership in a client-embedded environment; internal projects, vendor labs, or team-only deployments do not qualify.
- Proven ability to articulate business value: can quantify the impact of deployments in terms a CFO would recognize and act on.
- Experience presenting to and building trust with senior client stakeholders, CTO, CFO, or CISO level.
- Non-linear profiles are expected and welcomed; assessment is based on demonstrated deployment experience and outcome ownership, not CV pattern matching.
Locations
- London
- Berlin
- Madrid
- Paris
Equal Employment Opportunity Statement
All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process. Accenture is committed to providing veteran employment opportunities to our service men and women. Please read Accenture’s Recruiting and Hiring Statement for more information on how we process your data during the Recruiting and Hiring process.
Forward Deployed AI Engineer employer: WeAreTechWomen
As a Forward Deployed AI Engineer at our company, you will be part of a pioneering team that is redefining the deployment of AI solutions within enterprise environments. Our collaborative work culture fosters innovation and empowers you to take ownership of impactful outcomes, while our commitment to employee growth ensures you have access to the most challenging AI problems across various industries. Located in vibrant cities like London, you'll enjoy a dynamic work environment that values diversity and encourages professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Forward Deployed AI Engineer
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at WeAreTechWomen or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to WeAreTechWomen.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like WeAreTechWomen.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like WeAreTechWomen that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Forward Deployed AI Engineer
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 WeAreTechWomen.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at WeAreTechWomen 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 WeAreTechWomen
✨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 WeAreTechWomen 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.
