{"id":1681238,"url":"https://alion.io/job/bleckmann-ai-engineer","title":"AI Engineer","company":{"id":2137303,"name":"Bleckmann","domain":"bleckmann.com","url":"https://alion.io/company/bleckmann","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":{"grade":"B","score":75,"open_postings":5,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-03T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Belgium"],"countries":["BE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Cortex","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","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":"Scrum","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Tool Use","optional":false},{"name":"Agile","optional":true},{"name":"Computer Vision","optional":true},{"name":"GDPR","optional":true},{"name":"OCR","optional":true},{"name":"Prometheus","optional":true},{"name":"Time Series Forecasting","optional":true}],"status":"live","first_seen_at":"2026-09-22T00:00:00Z","employer_posted_date":"2026-09-22","last_verified_at":"2026-10-03T15:14:44Z","board_verified":true,"closed_at":null,"days_open":12,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":12},"description":"Ready to Join the Backstage Crew?\nAt Bleckmann, we’ve been delivering on promises since 1862. As a market leader in supply chain management for fashion and lifestyle brands, we keep the show running behind the scenes - from moving boxes to moving data, from pack & ship to IT and HR.\nBut we’re not just logistics experts. We’re The Backstage Crew - a tight-knit team of 6,500+ people who make fashion and lifestyle brands shine by doing the work that matters most, out of the spotlight but never out of impact.\nWhether you're on the warehouse floor or behind a screen, you’ll find:\nStrong connections with colleagues who support and celebrate you.\n\nFast growth in a company that’s expanding across Europe, the US, and Asia.\n\nHigh energy in a dynamic environment where no two days are the same.\n\nGuided freedom to take initiative, solve problems your way, and grow your career.\n\nWe believe in entrepreneurship, expertise, excellence, andengagement - and we live these values every day. From repairing returned goods to reducing waste, we help brands extend product lifecycles with sustainability in mind.\nSo if you’re ready to roll out the red carpet for our clients - and for each other - we’ve got a spot for you.\nBehind the scenes is where the real excitement begins. Ready to join us?\nYour role\nAs an AI Engineer, you build AI solutions end to end: AI workflows and pipelines, intelligent agents and applications with AI integrations, built on Snowflake and Azure AI Foundry. You take a business challenge, design the flow, build it and bring it to production, working closely with business stakeholders, IT and Data Engineers.\nConcrete examples of what you will work on: extracting structured data from documents, building the pipelines that process and enrich that data, building agents that answer questions on our own data, and delivering the web applications the business teams use to work with the results.\nThis is a hands-on building role. Most of the work is applying and integrating existing AI models into workflows and applications. Building and training your own machine learning model is part of the job where that is the better answer, but it is not the centre of gravity.\nYour responsibilities\nAI Solution Development (35%)\nDesign and build AI solutions on prioritized business use cases, from first prototype to production\nBuild AI workflows and agents: prompt design, tool calling, retrieval, structured output and guardrails\nBuild the AI pipelines behind them: ingestion, processing, enrichment and scheduling, event-driven where that fits\nExtract structured data from unstructured sources such as PDF, Excel and e-mail, and make it usable downstream\nBuild and deploy the applications around them: APIs, front-end, containers and CI/CD\nBuild, train and evaluate machine learning models where that is the better fit, for example forecasting or classification\nMaintain and improve existing AI solutions in production\nUse Case Implementation & Innovation (20%)\nCollaborate with business stakeholders to identify and refine AI use cases, for example during AI bootcamps\nTranslate business questions into a concrete technical design, and make the distinction explicit between a fixed automated flow, a question and answer solution on our own data, and an autonomous agent\nPerform feasibility assessments and validate potential business value\nContribute to shaping and prioritizing the AI roadmap\nPrototype innovative solutions and experiment with new technologies\nData & Platform Integration (15%)\nWork in Snowflake as the central platform: Cortex functions, Snowpark, semantic views and container services for hosting applications\nCollaborate with Data Engineers to consume validated data products delivered via Snowflake\nDesign and implement data preparation logic for AI use cases\nLeverage and contribute to the semantic layer so AI solutions use consistent, business-aligned definitions\nImplement logging, monitoring and data traceability for AI pipelines\nOptimize performance, scalability and cost of AI solutions within Snowflake and Azure\nAI Data Quality & Grounding (15%)\nEnsure high-quality and relevant data is used as input for AI models and agents\nDesign context-building mechanisms such as retrieval, context windows and embeddings to ground models in trusted data\nImplement guardrails so models only respond based on available data and avoid hallucinations\nValidate AI output against known business logic, metrics or datasets\nDesign filtering, validation and enrichment logic to reduce noise and inconsistencies\nCollaborate with Data Engineers to raise and resolve structural data quality issues\nGovernance, Security & Compliance (10%)\nEnsure AI solutions comply with internal governance and data protection policies\nParticipate in AI risk assessments and documentation processes\nFollow AI tool registration and approval processes\nDocument models, assumptions and limitations\nApply responsible AI practices: bias awareness, explainability and traceability\nCollaboration & Delivery (5%)\nParticipate actively in Scrum ceremonies\nCollaborate with internal teams: BI, IT and business stakeholders\nWork with external partners to co-develop AI solutions and ensure knowledge transfer to internal teams\nCommunicate progress, risks and results clearly to stakeholders\nYour profile\nWhat you bring (must-have)\nStrong Python, used to build and ship working applications, not only notebooks and experiments\nSolid SQL and experience with a cloud data platform. Snowflake is an advantage.\nHands-on experience with LLMs in real solutions: prompt engineering, RAG, embeddings and tool calling or agents\nExperience integrating AI services and APIs, for example Azure AI Foundry, OpenAI or Snowflake Cortex\nAble to deliver a solution end to end: data flow, API, deployment through Docker and CI/CD, and a usable interface\nMachine learning fundamentals, and able to build, train and evaluate a model where that is the better answer than an LLM.\nCommunicates clearly with business stakeholders and turns their question into a design they recognise \nWhat is a plus (nice to have)\nSnowflake Cortex, Snowpark, semantic views and container services\nDeeper data science experience: time series forecasting, feature engineering and model evaluation at scale\nFront-end experience, for example React\nDocument processing, OCR or information extraction at scale\nMLOps and model lifecycle management\nAwareness of AI governance, security and data privacy (GDPR)\nExperience in logistics, supply chain or operational environments\nWhat this role is not\nNot a research role. Machine learning is part of the work, but most solutions are built by applying and integrating existing models rather than by developing new ones. A profile centred on deep learning research or computer vision does not match this position.\nNot an analysis or reporting role. Profiles from BI, data analysis or S&OP analytics without hands-on build experience will not find what they are looking for here.\nExperienced or starting\nBoth are welcome. Experienced candidates who can run a use case independently, and recent graduates with a strong AI profile who want to grow into the role.\nHow hybrid working is arranged depends on where you sit in that range. Experienced profiles work largely independently and can spend a good part of the week working from home. Starting profiles learn the platform and our way of building by working alongside the team, so they are on site in Grobbendonk for most of the week. That balance shifts towards more home working as you grow into the role.\nSoft Skills\nStrong analytical and problem-solving mindset\nAbility to translate business problems into technical AI solutions\nFocus on delivering value, not just building models\nHigh attention to data quality, reliability, and correctness\nPassion for innovation and continuous learning in AI\nStrong collaboration skills in cross-functional teams\nAbility to work effectively in an Agile / Scrum environment\nComfortable working in a hybrid setup (internal + external partners)\nProactive and ownership-driven mindset\nAbility to manage ambiguity and evolving requirements\nAbility to explain complex AI concepts in a clear and business-friendly way\nStrong communication towards: Business stakeholders (translate needs into solutions) and Technical teams (align with Data Engineers / IT)\nWhat we offer\nA role with direct impact on business development\nExposure to international clients, carriers and internal stakeholders\nA dynamic environment where requests are varied and often cross-functional\nRoom to improve processes, templates, data quality and ways of working\nGuided freedom to take initiative and grow your expertise\nA collaborative team environment with short communication lines\nHybrid working possibilities, depending on location and business needs\nAt Bleckmann, we are guided by our values: We take a parachute and jump (Entrepreneurship), we unpack our knowledge (Expertise), we raise the bar with every box (Excellence), and we spark energy that connects (Engagement).","description_format":"text","description_chars":9029,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Continuous learning","Hybrid work"],"hiring_locations":[{"name":"Belgium","iso":"BE","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Lifestyle","Transportation & Logistics","Logistics"],"lifecycle":[{"event":"open","at":"2026-10-02T09:40:38Z"}],"visa":[],"liveness":{"score":53,"band":"ok","label":"Likely open","p_open":1,"p_active":0.707,"p_room":0.75,"age_days":11,"expected_fill_days":14,"reasons":["conf:4","win:late"],"computed_at":"2026-10-03T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/bleckmann-ai-engineer","json_url":"https://alion.io/job/bleckmann-ai-engineer.json","meta":{"generated_at":"2026-10-04T02:38:49Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3848,"day_limit":5000,"remaining_today":1152,"minute_limit":60,"resets_at":"2026-10-05T00:00:00Z"}}}