{"id":2632139,"url":"https://alion.io/job/altibbi-ai-engineer","title":"AI Engineer","company":{"id":48703,"name":"Altibbi","domain":"altibbi.com","url":"https://alion.io/company/altibbi","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"ZenATS","truth_index":{"grade":"B","score":75,"open_postings":4,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Amman, Jordan"],"countries":["JO"],"hiring_countries":[],"hiring_countries_total":0,"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":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude Code","optional":false},{"name":"Copilot","optional":false},{"name":"Cursor","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"gRPC","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Docker","optional":true},{"name":"Knowledge Graph","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangSmith","optional":true},{"name":"Milvus","optional":true},{"name":"Multimodal AI","optional":true},{"name":"Pinecone","optional":true},{"name":"Qdrant","optional":true}],"status":"live","first_seen_at":"2026-09-16T12:06:46Z","employer_posted_date":"2026-09-16","last_verified_at":"2026-10-17T08:46:34Z","board_verified":true,"closed_at":null,"days_open":30,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":30},"description":"AI Engineer\nExperience: 3-7 Years\nDepartment: AI / LLM Product Engineering\nLocation: Amman, Jordan\nReporting To: Head of AI\nEmployment Type: Full-time\nWork Type: On-site\nAbout the Role\nWe are looking for an experienced AI Engineer to design, build, deploy, and scale AI-powered product capabilities. The ideal candidate has hands-on experience with modern AI/LLM systems, agentic workflows, Retrieval-Augmented Generation (RAG), and AI-assisted software development.\nYou will work closely with our Engineering, Product, Data, and AI teams to turn AI concepts and prototypes into reliable, scalable, and production-ready solutions.\nKey Responsibilities\nAI Systems Integration: Build and integrate AI/LLM capabilities using cloud platforms and services such as AWS Bedrock and Azure OpenAI.\n\nAgentic Workflows & Orchestration: Design and implement agentic and LLM-driven features using LangGraph, LangChain, or equivalent frameworks.\n\nRAG & Retrieval Pipelines: Develop RAG pipelines, vector embeddings, retrieval and grounding mechanisms, prompt engineering, and tool/function-calling workflows.\n\nProduction Engineering: Transform AI prototypes and experimental concepts into scalable, secure, maintainable, and well-tested production systems.\n\nAI-Assisted Development: Leverage modern development tools such as GitHub Copilot, Claude Code, Cursor, or equivalent tools while ensuring generated code meets quality, security, and performance standards.\n\nCross-Functional Collaboration: Partner with Product Managers, Data Engineers, Software Engineers, and AI Researchers to solve complex technical challenges.\n\nQuality & Evaluation: Evaluate and improve AI models and workflows using relevant quality, reliability, latency, and performance metrics.\n\nQualifications & Requirements\nExperience: 3-7 years of professional experience in AI Engineering, Machine Learning Engineering, or Software Engineering with strong hands-on AI/ML experience.\n\nAI/LLM Expertise: Practical experience developing AI/LLM-powered applications, intelligent features, prompt engineering, tool/function calling, and LLM orchestration.\n\nAI Frameworks: Hands-on experience with LangGraph, LangChain, or comparable AI orchestration frameworks.\n\nProgramming: Strong Python skills with solid software engineering fundamentals, including OOP, design patterns, and clean code practices.\n\nProduction Engineering: Experience working with REST/gRPC APIs, data processing, debugging, unit and integration testing, CI/CD, and Git.\n\nProblem Solving: Strong analytical and problem-solving skills, with the ability to work independently and effectively within distributed, cross-functional teams.\n\nGood to Have\nHands-on experience with AWS or Azure.\nExperience with vector databases such as Milvus, Pinecone, or Qdrant.\nKnowledge of knowledge graphs and retrieval systems.\nExposure to multimodal AI.\nExperience with Docker, Kubernetes, and modern CI/CD practices.\nExperience with AI evaluation and observability frameworks such as LangSmith or Phoenix.\nFamiliarity with LLM monitoring and production AI observability.\nOpen-source contributions, technical publications, or a strong portfolio of AI 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