Be the true you
You will be establishing and scaling prompt engineering as an IT capability that safely powers GenAI enabled solutions across the enterprise.
At Deloitte.
Benefits
- You’ll receive a profit-sharing bonus. On top of your fixed salary.
- Continuous professional growth. Join our development program.
- A work-from-home office setup allowance to make sure you have everything you need for an ergonomically designed workstation and internet allowance.
- Work part-time (32 hours a week) or full-time (40 hours a week).
- Flexible working hours, you are in charge of your own calendar.
- 26 days of paid annual leave, and the opportunity to purchase additional leave.
- The option to exchange three national holidays for three non-national holidays.
- A good mobility scheme: the choice of various options such as a lease car, travel by public transport, a cash option or a combination of these.
- A laptop and iPhone. The iPhone can be for personal use.
- A good pension scheme with a personal contribution of only 2%. For a comfortable future.
- An opportunity to take part in our collective health insurance scheme.
- An opportunity to benefit from tax-efficient facilities such as fitness, a bicycle scheme or the opportunity to lease a bicycle.
- The opportunity to use 55 hours of babysitting service per calendar year, if your child is 12 years old or younger.
- An opportunity to benefit from tax-efficient facilities, such as company fitness and a bicycle scheme.
- A flexible budget, which you can use to make choices in flexible benefits, for example: purchasing extra leave days or financing a bicycle plan.
- Six weeks of fully paid birth leave for traditional households and rainbow families.
Be the true you
Naturally you constantly discover new ways to solve difficult problems and you are keen to discover and learn new things each day. But most importantly, be the true you. The one and only you. With your personal strengths, view of the world and unique personality. You need the following qualifications for the position of Prompt Engineer:
- 5+ years in software engineering, with 2+ years in prompt engineering with proven expertise on patterns like Chain-of-Thought, Tree-of-Thought, self-consistence, prompt chaining and multi-model prompting;
- proven expertise in prompt strategies and techniques, RAG, embeddings and vector stores;
- excellent communication skills with an ability to steer, influence and convince senior leadership, particularly non-technologists;
- deep understanding of Microsoft’s ecosystem including Azure Cognitive Services, Semantic Kernel, Azure DevOps, GitHub, M365, AI Foundry, Power Platform and CoPilot Studio
What impact will you make?
You will lead large language model patterns, tooling, platforms, guardrails and integrate those into our DevSecOps, IT Service Management processes and ways of working. You will be driving GenAI adoption within the (personal) productivity domain, as well as enabling technology teams to integrate and utilize GenAI solutions. You will design the technology foundation bridging between (legacy) infrastructure and large language models, setting principles on interoperability, integration and orchestration.
For this role we do not offer visa sponsorship and/or relocation.
How do you do this?
- design task‑specific prompts and chains; apply prompt patterns and design Retrieval-Augmented Generation (RAG) logic for RAG scenarios;
- integrate Large Language Model (LLM) flows with enterprise APIs via function‑calling, agents, and workflow extensions, ensuring observability (logs, traces, monitoring);
- embed GDPR principles (data minimization, purpose limitation), access controls and DLP controls;
- align with EU AI Act obligations for high‑risk systems where applicable (data governance, transparency, human oversight);
- implement and adhere to Deloitte global standards, policies and guardrails assuring internal compliancy;
- engage with business and technology teams to prioritize use cases, track ROI and drive adoption;
- coordinate with cloud providers and model vendors, evaluate new capabilities and define enterprise feature enablement;
- evaluate and prioritize pre-built agents as part of the wider ecosystem of AI platforms and solutions.
- define and implement LLM Operations for continuous monitoring of model health, latency tracking, cost and response quality.
