{"id":2253762,"url":"https://alion.io/job/nttdata-ai-engineeragentic-workflow-platform","title":"AI Engineer/Agentic Workflow Platform","company":{"id":4401319,"name":"NTT DATA Romania","domain":"nttdata.ro","url":"https://alion.io/company/nttdata-ro","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Romania"],"countries":["RO"],"hiring_countries":["RO"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude Code","optional":false},{"name":"Copilot","optional":false},{"name":"Cursor","optional":false},{"name":"GitHub","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Least Privilege","optional":false},{"name":"LLM","optional":false},{"name":"Pipeline as Code","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Windsurf","optional":false},{"name":"AutoGen","optional":true},{"name":"Azure","optional":true},{"name":"Bicep","optional":true},{"name":"CrewAI","optional":true},{"name":"DeepEval","optional":true},{"name":"LangChain","optional":true},{"name":"OpenAI","optional":true},{"name":"OWASP Top 10","optional":true},{"name":"Promptfoo","optional":true},{"name":"Pulumi","optional":true},{"name":"SBOM","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-05T00:00:00Z","employer_posted_date":"2026-10-05","last_verified_at":"2026-10-11T19:33:33Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":6},"description":"Who we are\nWe 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.\nThis 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.\nYou 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.\nThis 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.\nWhat you'll be doing\nBuild and improve AI workflows across repositories\nDesign agent workflows for docs, testing, code quality, reviews, and security\nCreate effective prompts and multi-step interactions\nImprove reliability and usability of agents\nUse AI coding tools (e.g., Copilot, Cursor) to accelerate delivery\nDesign evaluation pipelines for prompts and agents\nBuild datasets with edge and adversarial cases\nAdd automated regression and behavior checks\nUse code-based and LLM-based evaluators\nDefine quality gates before production\nBuild reusable templates and onboarding tools\nDevelop CLI/scripts for easy adoption\nMaintain workflow catalog and integrations\nWrite clear docs and guides\nEnable self-service usage\nMaintain GitHub Actions and CI/CD patterns\nEnsure secure design (least privilege, secrets, OIDC)\nImprove security controls and automation safety\nMitigate risks (prompt injection, data leaks)\nKeep changes testable and production-safe\nWhat you'll bring along\nBSc/MSc in Computer Science or related field\nMinimum 3-6+ years as a Platform Engineer\nStrong hands-on experience with Python for scripting, automation, evaluation tooling, or integrations\nPractical experience building with LLMs, prompts, AI agents, or agentic workflows in real engineering or production contexts\nDaily use of AI coding assistants or coding agents such as Copilot, Cursor, Kiro, Windsurf, Claude Code, or similar\nExperience designing, testing, and iterating prompts for reliable task execution\nExperience building evaluation or testing approaches for non-deterministic AI outputs\nStrong experience with 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