Ai Engineer/Agentic Workflow Platform
Pubblicato il 18-10-2026 - Ntt Data Europe & Latam in Emilia-Romagna
Who We AreWe are looking for a hands-on AI Engineer to help improve and scale an internal platform that enables engineering teams to ship faster and safer using AI-powered workflows.
Tutti i potenziali candidati sono invitati a leggere con attenzione i seguenti dettagli prima di inviare la propria candidatura.
This role is focused on practical AI engineering, not AI research and not pure platform architecture.
You will work on agentic workflows, prompt engineering, evaluation pipelines, GitHub-based automation, and developer tooling that helps teams adopt AI agents consistently across repositories.
You will join an existing initiative that already has working foundations in place.
The immediate need is to strengthen, stabilise, and mature the current implementation through hands?on engineering, especially in agent development, testing, evaluation, and workflow reliability.
This is an excellent fit for someone who already uses AI coding agents as part of their daily workflow and knows how to turn AI capabilities into reliable engineering tooling.
What You'll Be DoingBuild and improve AI workflows across repositories
Design agent workflows for docs, testing, code quality, reviews, and security
Create effective prompts and multi?step interactions
Improve reliability and usability of agents
Use AI coding tools (e.g., Copilot, Cursor) to accelerate delivery
Design evaluation pipelines for prompts and agents
Build datasets with edge and adversarial cases
Add automated regression and behavior checks
Use code?based and LLM?based evaluators
Define quality gates before production
Build reusable templates and onboarding tools
Develop CLI/scripts for easy adoption
Maintain workflow catalog and integrations
Write clear docs and guides
Enable self?service usage
Maintain GitHub Actions and CI/CD patterns
Ensure secure design (least privilege, secrets, OIDC)
Improve security controls and automation safety
Mitigate risks (prompt injection, data leaks)
Keep changes testable and production?safe
What You'll Bring AlongBSc/MSc in Computer Science or related field
Minimum 3-6+ years as a Platform Engineer
Strong hands?on experience with Python for scripting, automation, evaluation tooling, or integrations
Practical experience building with LLMs, prompts, AI agents, or agentic workflows in real engineering or production contexts
Daily use of AI coding assistants or coding agents such as Copilot, Cursor, Kiro, Windsurf, Claude Code, or similar
Experience designing, testing, and iterating prompts for reliable task execution
Experience building evaluation or testing approaches for non?deterministic AI outputs
Strong experience with GitHub Actions or equivalent CI/CD tooling, including reusable workflows and pipeline?as?code patterns
Experience working with YAML, Markdown, JSON, and configuration?driven systems
Good understanding of authentication, authorisation, secrets handling, xysqume and least?privilege access patterns
Ability to write clear technical documentation for developers
Strong hands?on engineering mindset with the ability to improve existing implementations quickly and pragmatically
Preferred / Nice to Have
Experience with AI evaluation frameworks such as promptfoo, DeepEval, RAGAS, Azure AI Evaluation SDK, or similar
Experience with agentic frameworks such as LangChain, AutoGen, CrewAI, OpenAI Assistants API, or similar
Background in internal developer platforms, developer tooling, or developer experience engineering
Experience with docs?as?code and static documentation sites
Familiarity with infrastructure?as?code tools such as Terraform, Bicep, Pulumi, or CDK
Understanding of software supply chain security, dependency scanning, action pinning, and SBOM concepts
Awareness of AI safety concerns such as prompt injection, adversarial testing, and OWASP Top 10 for LLM
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