{"id":2606166,"url":"https://alion.io/job/link-group-agentic-ai-engineer","title":"Agentic AI Engineer","company":{"id":880,"name":"Link Group","domain":"linkgroup.co","url":"https://alion.io/company/link-group","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":"Recruitify","truth_index":{"grade":"A","score":85,"open_postings":109,"ghost_share":0,"stale_share":0.606,"repost_share":0,"time_to_fill_p50_days":48,"computed_at":"2026-10-15T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Poland"],"countries":["PL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":60000,"max_usd":110000,"period":"year","method":"role_country_seniority_unknown","sample_n":268},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Context Engineering","optional":false},{"name":"Edge AI","optional":false},{"name":"Git","optional":false},{"name":"LLM","optional":false},{"name":"LLMOps","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-15T08:07:31Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-15T20:48:48Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"US Time zone\nKey Responsibilities\nAgentic Systems & Tool Design: Architect, build, and optimize autonomous AI agents, tool integration frameworks, skills, and multi-step agentic workflows.\n Context Engineering & RAG: Design and refine advanced Retrieval-Augmented Generation (RAG) pipelines, system prompts, and context-window strategies for maximum accuracy and efficiency.\nAI Research & Innovation: Stay at the forefront of cutting-edge AI/LLM research and translate emerging methodologies into practical product enhancements.\nModel Evaluation & Error Analysis: Conduct systematic model selection, benchmarks, and granular error analysis to continuously improve output quality and mitigate hallucinations.\nLLMOps & Observability: Deploy, monitor, and maintain LLM applications in production; 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