AI Delivery Enablement Lead

Atos is hiring an AI Delivery Enablement Lead. Level rates it ; you can apply on Atos.

Level's read on this job

Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
The posting mentions RAG among its tools and skills.
Level classes it as a lead role.
Atos has 609 other open roles on Level.
Posted within the past two weeks.

AI in this role

rag

Who we are.

We are a team of passionate experts with a clear ambition: applying digital technology to advance what matters for our clients and society.

Together we create reliable and responsive digital foundations for the world’s businesses, institutions, and communities.

Learn more on Advancing what matters .

About the Role

Atos is hiring an AI Delivery Enablement Lead to own the institutional memory, intake, costing, and enablement layer of the Belgium AI delivery practice. The role creates and maintains the knowledge bases that every AI project draws on, runs project intake and planning governance, owns the financial and costing model for AI work, builds the case-study library, upskills delivery teams, and tracks the KPIs that prove the practice is working.

Key Responsibilities

Create and maintain the AI knowledge base, including ADRs, pattern playbooks, prompt libraries, evaluation-failure catalogues, decision logs, and searchable indexing.
Run structured AI project intake, capturing scope, risk class, budget, model choice, and engagement gate.
Maintain planning governance, including templates, dependency maps, and gate-review cadence.
Build and maintain AI costing and financial models covering token economics, inference cost, training cost, GPU spend, license fees, and FinOps controls.
Develop the AI case-study library and capture architecture, cost profile, evaluation evidence, and lessons learned from shipped engagements.
Upskill delivery teams through onboarding paths, workshops, pairing sessions, and office hours.
Define, track, and report AI KPIs related to adoption, reuse, gate coverage, time-to-productive-first-PR, project-level margin contribution, and risk-register posture.
Partner with the AI Governance and Platform Lead and the Lead AI Engineer to keep the knowledge base aligned with current governance, model, and data realities.

Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, Information Management, or a related field, or equivalent senior experience.
5+ years in a role combining technical depth with documentation, enablement, or programme management.
2+ years in or adjacent to AI, ML, or data engineering.
Strong technical writing skills and experience building knowledge bases, internal wikis, or developer documentation.
Experience with project intake or governance processes for technical work.
Comfort with financial modelling, cost build-ups, sensitivity analysis, and scenario modelling.
Strong data analysis skills using SQL, spreadsheets, and at least one BI tool. Python for analysis is a plus.
Strong facilitation skills for workshops and enablement sessions.

Preferred Qualifications

Experience with FinOps for AI workloads, including token economics, semantic caching, model right-sizing, and batch-versus-real-time trade-offs.
Familiarity with EU AI Act, ISO/IEC 42001, DORA, NIS2, and GDPR documentation requirements.
Experience with adult learning design, case-study or pattern libraries, and documentation-as-code tooling such as Docusaurus, MkDocs, Backstage, or Notion-as-system-of-record.
Public writing or talks on AI delivery, knowledge management, or engineering enablement.

Technical Skills

Knowledge base and documentation tools: Confluence, Notion, Backstage, Docusaurus, MkDocs, or similar, including search and retrieval design.
Project and governance tools: Jira, Asana, Linear, or equivalent, including stage-gate and gate-review processes.
Financial modelling and AI FinOps: advanced Excel or Google Sheets, AI cost modelling, token-cost calculators, and FinOps-for-AI principles.
Data and analytics: SQL, spreadsheets, and at least one BI tool such as Power BI, Looker, Tableau, or Metabase; Python for analysis is a plus.
AI and ML literacy: understanding of LLM application architecture, RAG, agent platforms, and evaluation.
Enablement tools: learning platforms, workshop design tools, and scalable pairing models.

If you're ready to embark on this exciting adventure with us, sign in on jobs.atos.net.

Learn more about us:

At Atos, we embrace diversity as the ultimate engine of ingenuity for our clients, and we constantly strive to create a culture where people feel supported and encouraged. Read more about our commitment here .

Whether it is fighting climate change, promoting digital inclusion, or ensuring trust in data management – tech for good sits at the core of our identity. With numerous global recognitions for our ESG practices, we are committed to building a better future for all by harnessing the power of technology. Learn more here

How we rate this

AI Delivery Enablement Lead at Atos rates 63 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

AI Delivery Enablement Lead is an open job at Atos.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Timisoara.
The job was posted on October 14, 2026.
Seniority: lead.
Applications are handled by Atos. Apply on Atos

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAG

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: RAG. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

Want an expert to read your CV for this job?

Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.

Get a free CV review Check your resume with the ATS resume checker

Get new AI jobs (Works on AI ●●●○ or higher) by email

One email a week with the new AI jobs (Works on AI ●●●○ or higher), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.

Free. One email a week. Unsubscribe in one click.