At a Glance
- Tasks: Lead the design and delivery of innovative AI solutions for global clients.
- Company: Join a Fortune 500 company shaping the future of work with cutting-edge AI technology.
- Benefits: Enjoy competitive pay, flexible work options, and a supportive culture focused on growth.
- Other info: Collaborative environment with opportunities for career advancement and personal development.
- Why this job: Make a real impact by deploying AI solutions that transform businesses and enhance teamwork.
- Qualifications: 5+ years in software implementation and hands-on AI experience required.
The predicted salary is between 63000 - 77000 £ per year.
Your work days are brighter here. We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. Our culture is rooted in integrity, empathy, and shared enthusiasm. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive.
About the Team
The AI Practice team is part of Workday’s Professional Services organization and is responsible for the technical realization of Workday AI for our customers. Our technical consultants work across architecture, integrations, data, and configuration to ensure that Native AI Agents, the Workday Agent Platform, and Sana are deployed in a performant, secure, and scalable way.
About the Role
As a Senior AI Deployment Engineer, you will be the lead technical architect responsible for designing and overseeing the delivery of end‑to‑end AI solutions for Workday’s most complex global customers. You will work across Native AI Agents, the Workday Agent Platform, external LLMs, and Sana to define how data flows, integrations, and configurations come together to produce trustworthy, high‑impact AI experiences. You will lead technical workstreams, advise C‑suite and technical stakeholders, and collaborate closely with Product and Engineering to shape how Workday AI is deployed at scale.
Key Responsibilities
- Solution Design: Architect end‑to‑end AI solutions across the Workday ecosystem, including data flows, integration patterns, and technical controls that connect Native Agents, custom agents on the Workday Agent Platform, and Sana’s knowledge and content capabilities.
- Strategic Advisory: Act as a trusted technical advisor to C‑suite and senior technical leaders, translating AI architecture choices into clear business value, risk considerations, and long‑term digital transformation roadmaps.
- Technical Leadership: Lead technical delivery for AI workstreams, providing oversight for configuration, integrations, data preparation, privacy and security controls, and model‑related tuning within the Workday environment.
- Innovation & Feedback: Partner closely with Workday Product and Engineering teams to share real‑world insights from customer deployments, informing the evolution of the Agent Platform, AI tooling, and Sana integration capabilities.
- Ecosystem Integration: Design and validate patterns for how Workday AI interacts with third‑party systems and external LLMs, ensuring data integrity, security, and adherence to Workday’s Ethical AI principles.
About You
Basic Qualifications
- Senior Level: 5+ years of experience in enterprise software implementation, technical architecture, and technical consulting (e.g., Workday, HCM/FIN, or similar platforms), including leading complex, multi‑system initiatives.
- 1+ years of hands‑on experience with enterprise AI/ML or intelligent automation deployments (e.g., LLM‑based solutions, RAG architectures, or AI‑driven workflows).
- Principal Level: 8+ years of experience in enterprise software implementation, technical architecture, and technical consulting (e.g., Workday, HCM/FIN, or similar platforms), including leading complex, multi‑system initiatives.
- 2+ years of hands‑on experience with enterprise AI/ML or intelligent automation deployments (e.g., LLM‑based solutions, RAG architectures, or AI‑driven workflows).
Other Qualifications
- Strong background in technical architecture, with experience designing data flows, integration patterns, and security models across SaaS ecosystems and external services.
- Deep familiarity with the Workday ecosystem (HCM and/or Financials), including core configuration concepts, integration frameworks, and security models, or equivalent experience with similar enterprise platforms.
- Practical experience with AI concepts such as LLMs, retrieval‑augmented generation (RAG), prompt design, and orchestration layers, and how these can be applied in an enterprise context.
- Experience in professional services or consulting, leading technical delivery for high‑stakes customer programs and collaborating closely with engagement managers, functional consultants, and customer IT teams.
- Excellent communication skills, with the ability to explain complex AI and architectural topics to non‑technical stakeholders while engaging deeply with developers, data engineers, and product teams.
- Demonstrated decision‑making and work management skills: prioritizing technical tradeoffs, managing technical risk, and organizing complex work across multiple parallel workstreams.
- Experience driving process improvements in technical delivery practices (e.g., establishing reference architectures, reusable patterns, or automation that improves consistency and quality).
- Strong alignment with Workday’s Ethical AI principles, with a focus on designing solutions that are transparent, fair, secure, and compliant with data privacy requirements.
Sr. AI Deployment Engineer in London employer: Workday
At Workday, we pride ourselves on fostering a vibrant work culture that champions integrity, empathy, and collaboration. As a GTM Manager, you'll not only have the opportunity to drive transformative AI solutions but also benefit from a supportive environment that prioritises your growth and development. With a commitment to innovation and a focus on meaningful work, you'll be part of a team that values your contributions and encourages you to take bold risks in shaping the future of work.
StudySmarter Expert Advice🤫
We think this is how you could land Sr. AI Deployment Engineer in London
✨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 Workday 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 Workday.
✨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 Workday.
✨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 Workday 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 Sr. AI Deployment Engineer in London
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 Workday.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Workday 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 Workday
✨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 Workday 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.
