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Location: Poland (remote) Work Schedule: Full-time Contract Type: pure B2B (JDG) We are looking for an experienced AI Architect to design and lead the development of scalable, production-grade AI solutions. This role focuses on building modern AI/ML and agent-based systems, defining architecture standards, and driving adoption of AI technologies across the organization . Our customer is a multinational corporation with more than a century of history and offices in over 180 countries. Their most ambitious goal at the time is to introduce a range of Reduced-Risk Products (RRPs). The target audience is more than 1 billion consumers around the globe. IT platform hosts 700+ application s. Intellia's mission is to help the client with the engineering of a comprehensive software ecosystem for a game-changing IoT product on the margin of innovative consumer experience and cutting-edge technology. Our teams are involved in the engineering of core platform components for best-in-class eCommerce, Digital Marketing and IoT solutions. As a DevOps engineer, you will become a part of Core Architecture Team and be responsible for the architecture, implementation of best practices in our Digital Engineering Enterprise Platfo rm. The Platform is a set of services and internet applications that accelerate the development and delivery of software applications by taking care of common SDLC challenges. The Platform provides access and consumption for engineering teams to a set of services, technologies, practices for their development and for operating their application, ensuring a set of compliance and best practi ces. The project has been in production for 2+ years and has been supported by multiple t eams. Our technical domain s are:- AWS cloud, partially Azure- SSO, Organizations, Service control policies, access m odels.- IAAC: terraform enterprise, terratest, c halice- Serverless: lambda, step functions, wide range of misc automations, f argate- System, Application, Network and security archite ctures- Orchecstration: k8s (eks)- SRE activities (logging, tracing, monitoring), OpsGenie, Splunk- Hashicorp Vault- Hybrid Netw orking Requir ements:7+ years of experience in software engineering/architectur e rolesStrong experience designing and deli vering AI/ML solutions in pro ductionHands-on experienc e with LLMs and generative AI systemsExperienc e with agent-based architectures and orchestration fra meworksStrong expert ise in AWS (EKS, Lambda, S3, API Gateway , etc.)Experienc e with Kubernetes and Te rraformStrong programming ski lls in Python (ML frameworks, APIs, data proc essing)Experienc e with ML frameworks and ecosystems (PyTorch, TensorFlow , etc.)Understand ing of data pipelines and large-scale data pro cessingExperienc e with MLOps practices an d toolsStrong understand ing of distributed systems and cloud-native archit ectures Nice to HaveExperien ce with LangGraph, LangChain, or similar fr ameworksBackgr ound in platform engineering or internal AI p latformsExperien ce with vector databases, RAG, and embedding p ipelinesKnowl edge of AI governance, ethics, and model ev aluationExperience wor king in enterprise or large-scale envi ronments So ft Skil lsStrong architectural thinking and system desi gn skillsAbility to translate business ne eds into technical solutionsE ffective communication with both technical and non-technical sta keholdersLeadership mindset with the ab ility to mentor and gu ide teamsHigh level of ownership and accou ntabilityCuriosity and drive to stay curr ent with rapidly evolving AI tec hnologies Respons ibilities:Design e nd-to-end AI/ML arc hitectures, including LLM-based and agent-driv en systemsDefine and implement scalable, secure, and cost-efficient AI soluti ons on AWSLead architecture deci sions for AI platforms, pipelines, an d servicesDesign an d oversee agent-based workflows and orchestration frameworksIntegrate AI sys tems with enterprise platforms and cloud infr astructureEnsure best prac tices for model lifecycle manageme nt (MLOps)Collaborate with engineering teams to guide implementation an d deliveryEvaluate a nd select AI frameworks, tools, and te chnolo giesDrive AI adoption and innovation across teams and st akeholdersEnsure compli ance with security, governance, and data privacy standards