{"id":639285,"url":"https://alion.io/job/appsilon-applied-ai-engineer","title":"Applied AI Engineer","company":{"id":695078,"name":"appsilon","domain":"appsilon.com","url":"https://alion.io/company/appsilon","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Teamtailor","truth_index":{"grade":"B","score":75,"open_postings":3,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-28T05:59:10Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"inferred_company_offices","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Warsaw, Poland"],"countries":["PL"],"hiring_countries":["PL"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":56000,"max_usd":105000,"period":"year","method":"role_country_seniority_unknown","sample_n":267},"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":"Anthropic","optional":false},{"name":"AutoGen","optional":false},{"name":"Claude","optional":false},{"name":"CrewAI","optional":false},{"name":"Function Calling","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLMOps","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenAI Agents SDK","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"Kubernetes","optional":true},{"name":"Langfuse","optional":true},{"name":"LangSmith","optional":true},{"name":"pgvector","optional":true},{"name":"Pinecone","optional":true},{"name":"PyTorch","optional":true},{"name":"Qdrant","optional":true},{"name":"Scikit-learn","optional":true},{"name":"TensorFlow","optional":true},{"name":"Weaviate","optional":true}],"status":"live","first_seen_at":"2026-05-18T12:40:40Z","employer_posted_date":"2026-05-18","last_verified_at":"2026-10-07T05:06:45Z","board_verified":false,"closed_at":null,"days_open":163,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":162},"description":"Why do we need you?\nAt Appsilon, we empower global organizations to make smarter decisions with data. Our solutions help Fortune 500 companies discover new drugs, save lives, optimize operations, and unlock millions in value. To do this, we rely on robust, scalable, beautifully engineered data systems.\nWe're looking for an AI Engineer who combines strong engineering fundamentals with hands-on experience building and deploying AI agents and generative AI solutions - someone who can design agentic workflows that deliver real value in production.\nWhat you’ll do:\nBuild AI Agents with domain context for specialized tasks, including multi-step reasoning, tool use, and autonomous decision-making.\n\nDesign and implement agentic workflows - orchestrating LLMs, retrieval systems, and external tools into reliable, production-grade pipelines.\n\nIntegrate agents with client applications, APIs, and enterprise systems.\n\nEvaluate, iterate on, and optimize agent performance using structured testing, tracing, and observability.\n\nDeploy and maintain generative AI solutions in production environments (APIs, microservices, cloud architecture).\n\nDocument your work, follow best practices for LLMOps, and help shape AI development standards at Appsilon.\n\nWork closely with Data Engineers, Developers, and Analysts to integrate GenAI solutions into full-scale applications.\nWe’re looking for someone with:\n\nProven experience building and deploying AI agents or agentic systems in production (not just prototypes).\n\nDeep familiarity with LLM orchestration frameworks (e.g., LangChain, LangGraph, CrewAI, Autogen, Claude Agent SDK, or similar).\n\nStrong understanding of prompt engineering, retrieval-augmented generation (RAG), tool use, and function calling patterns.\n\nHands-on experience with LLM APIs (OpenAI, Anthropic, Google, open-source models) and managing their lifecycle in real-world applications.\n\nStrong programming skills in Python with experience building robust, maintainable backend services.\n\nAbility to evaluate and debug agent behavior - including tracing, logging, and structured evaluation of multi-step workflows.\n\nExcellent communication skills and a collaborative approach to teamwork.\n\nNice to have:\nExperience with cloud deployment (AWS, Azure, GCP) and containerization (Docker / Kubernetes).\n\nKnowledge of vector databases (Pinecone, Weaviate, Qdrant, pgvector) and embedding pipelines.\n\nFamiliarity with LLMOps and observability tools (LangSmith, Langfuse, Weights & Biases, etc.).\n\nBackground in classical ML (scikit-learn, PyTorch, TensorFlow) and understanding of the model training lifecycle.\n\nExperience working with large-scale or scientific datasets (biostatistics, genomics, pharma).\n\nUnderstanding of AI ethics, bias, and responsible AI principles.\n\nWhat we offer:\n100% remote work, flexible schedule, and a global team culture.\n\nCompetitive B2B compensation with transparent ranges.\n\nWork on impactful, real-world products used by enterprise clients and scientific industries.\n\nBudget and dedicated time for professional development (courses, certs, conferences).\n\nA chance to collaborate with a brilliant group of researchers and industry experts.\n\nModern equipment and tools for efficient development.\n\nSupportive environment with room for innovation, experimentation, and ownership.\n\nImportant note: To complete the hiring process, you need to have a valid government-issued ID (for Polish citizens) or a valid passport (for non-Polish citizens).\nRecruitment Process\nGeneral interview with the People Team.\n\nTechnical task (Codility test). \n\nTechnical interview\n\nFinal interview with the Head of Technology\n\nOffer.\n\nDoes this sound like a great opportunity for you?\nUse the Apply button below!\nAppsilon is committed to being a diverse and inclusive workplace. We encourage applicants of different backgrounds, cultures, genders, experiences, abilities, and perspectives to apply. 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