{"id":3365478,"url":"https://alion.io/job/spin-ic3-ai-engineer","title":"IC3 - AI Engineer","company":{"id":1811024,"name":"Spin","domain":"spin.app","url":"https://alion.io/company/spin-app","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":79,"open_postings":6,"ghost_share":0,"stale_share":0.833,"repost_share":0,"time_to_fill_p50_days":23,"computed_at":"2026-10-31T05:58:55Z"}},"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":"structured","locations":["Mexico"],"countries":["MX"],"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":"AWS","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Milvus","optional":false},{"name":"NLP","optional":false},{"name":"Pinecone","optional":false},{"name":"Python","optional":false},{"name":"Qdrant","optional":false},{"name":"RAG","optional":false},{"name":"Weaviate","optional":false},{"name":"Amazon SageMaker","optional":true},{"name":"Hugging Face","optional":true},{"name":"LangChain","optional":true},{"name":"LlamaIndex","optional":true},{"name":"PyTorch","optional":true},{"name":"TensorFlow","optional":true},{"name":"Vertex AI","optional":true}],"status":"live","first_seen_at":"2026-10-27T19:07:28Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-31T12:31:35Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"Objective \nWe’re buildinganAI-firstorganization- and we’relookingforengineerswhoactuallybuild, notjustexperiment. We’rehiringanAI Engineertodevelop, integrate, and maintainAI-poweredproductsacrossourecosystem- fromLLM-basedcustomerexperiencestointernalcopilotsthattransformhowteamsoperate. \nYou’llbe partofa centralizedAI ProductsChapter, embeddingintosquadstobringreal AI solutionsintoproduction. \nWhat you’lldo \nBuild and deploy Generative AI solutions (LLMs, RAG, agents, copilots) under standard production practices. \nImplement scalable AI components and services within production systems. \nWork across the full software lifecycle: assist in prototyping, deploy models, and optimize performance. \nIntegrate AI models with real-world systems, APIs, data platforms, and backend workflows. \nImplement evaluation frameworks, monitoring mechanisms, and feedback loops to track model performance. \nPartner with Product, Data, and Engineering squads to deliver impactful AI-driven features. \nWhat we’relooking for \nSolid software engineering background (Python + modern backend stack). \nHands-on experience building with LLMs, Generative AI, or NLP frameworks. \nPractical experience deploying ML/AI features into production environments. \nFamiliarity with cloud services (AWS/GCP), API design, and data pipelines. \nA strong problem-solving, execution-oriented, and continuous-learning mindset. \nWhy this role \nYou won’t just build models → you’ll ship real AI products into production. \nYou’ll collaborate across multiple squads → gain broad exposure and technical growth. \nYou’ll contribute directly to shaping best practices for AI Engineering within the organization. \nRequired Knowledge &Experience \nExperience: 3-5 years of overall experience in Data & Tech, with at least 1.5-2 years of hands-on experience developing AI/ML and Generative AI solutions. \nEducation: Bachelor’s or Master’s degree in Data Science, Computer Science, Applied Mathematics, or a related technical field. \nAI Competencies: Strong foundational understanding of Deep Learning, Natural Language Processing (NLP), and Generative AI (LLMs, RAG architecture, function calling, agents). \nTechnical Stack: Proficiency in Python and familiarity with ML libraries (PyTorch or TensorFlow), alongside hands-on use of AI frameworks (LangChain, LlamaIndex, or Hugging Face). \nCloud & Data Platforms: Hands-on experience with cloud-native AI/ML services (AWS SageMaker or Google Vertex AI) and standard data processing tools. \nInfrastructure & Tools: Practical experience using vector databases (Pinecone, Milvus, Qdrant, or Weaviate) and MLOps tools for model tracking and logging. \nCommunication: Ability to clearly explain technical trade-offs and AI concepts to both technical teammates and product partners. \nEthics & Compliance: Basic understanding of AI safety, data privacy, and responsible AI practices. \nSoft Skills: Proactive problem-solving, strong sense of ownership, willingness to learn, and commitment to writing clean, maintainable code. \nIf you’re excited about building real AI products (not just talking about them), we should talk. \nEn Spin estamos comprometidos con construir un lugar de trabajo diverso e inclusivo.\nCreemos en la igualdad de oportunidades y promovemos un entorno libre de discriminación por motivos de raza, origen nacional, género, identidad de género, orientación sexual, discapacidad, edad o cualquier otra condición legalmente protegida.","description_format":"text","description_chars":3447,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Payment Processing & Gateways","Digital Banks & Neobanks"],"lifecycle":[{"event":"open","at":"2026-10-27T22:54:46Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring 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