{"id":3063063,"url":"https://alion.io/job/whitecloak-ai-native-product-architect","title":"AI Native Product Architect","company":{"id":3775755,"name":"Whitecloak","domain":"whitecloak.com","url":"https://alion.io/company/whitecloak","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"A","score":86,"open_postings":9,"ghost_share":0,"stale_share":0.556,"repost_share":0,"time_to_fill_p50_days":49,"computed_at":"2026-10-31T05:58:55Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pasig, Philippines"],"countries":["PH"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":90000,"max":160000,"currency":"PHP","period":"month","gross":null,"usd_annual":30516},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Clean Architecture","optional":false},{"name":"GCP","optional":false},{"name":"Kubernetes","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"RAG","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-09-30T02:30:02Z","employer_posted_date":"2026-10-22","last_verified_at":"2026-10-31T05:24:08Z","board_verified":true,"closed_at":null,"days_open":31,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":31},"description":"We are looking for an AI-Native Product Architect to design, validate, and scale modern software and AI-powered solutions. This role combines solution architecture, rapid product development, AI engineering, and technical leadership to transform ideas into scalable business outcomes.\nThe ideal candidate can bridge business strategy, product vision, and engineering execution while leveraging AI to accelerate delivery, enhance team productivity, and create intelligent digital experiences. They are responsible for architecting secure, scalable, and maintainable systems that combine traditional software engineering with modern AI capabilities.\nThis role serves as a key driver of technology innovation, helping organizations adopt AI-native approaches to product development, engineering excellence, and digital transformation.\nResponsibilities\nDesign end-to-end business and technology solutions that align with stakeholder needs, enterprise constraints, and strategic objectives.\nDefine solution architectures, technology stacks, integration patterns, cloud strategies, and implementation roadmaps for software and AI-enabled systems.\nLead rapid MVP, prototype, and proof-of-concept initiatives to validate opportunities, reduce delivery risk, and accelerate time-to-market.\nDesign and implement AI-powered solutions including agents, copilots, RAG architectures, workflow automation, and intelligent business applications.\nBuild reusable AI harnesses, accelerators, prompt frameworks, and engineering workflows that improve productivity, quality, and AI adoption.\nProvide technical leadership to engineering teams, ensuring solutions are scalable, secure, maintainable, observable, and cost-efficient.\nEstablish architecture standards, governance practices, reusable assets, and reference architectures that improve delivery consistency across projects.\nResearch, evaluate, and recommend emerging AI, cloud, data, and engineering technologies that create business value and competitive advantage.\nQualifications\nMinimum 5 years of software engineering experience, with at least 3 years in a Technical Lead, Architect, or equivalent leadership role.\nStrong experience designing scalable cloud-native applications and distributed systems.\nHands-on experience architecting and deploying solutions on major cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP), including cloud-native services, networking, security, scalability, and cost optimization.\nExperience building enterprise MVPs, prototypes, and production-ready solutions.\nHands-on experience with AI technologies including LLMs, AI agents, workflow automation, or RAG architectures.\nStrong understanding of architectural patterns such as Clean Architecture, Microservices, Event-Driven Architecture, Domain-Driven Design (DDD), and CQRS.\nExperience with containers, Kubernetes, CI/CD, DevOps, Infrastructure as Code (Terraform or equivalent), and observability practices.\nExcellent leadership, communication, stakeholder management, and problem-solving skills.\nDetailed Expectations\nAI-Native Solution Architecture\nDesign end-to-end business and technical solutions that integrate AI capabilities into products, platforms, and enterprise workflows.\nArchitect systems that combine traditional software components with LLMs, AI agents, RAG pipelines, and workflow automation.\nEvaluate tradeoffs between build, buy, and AI-assisted approaches.\nDefine scalable architectures that support rapid experimentation and long-term growth\nMVP Development & Product Validation\nLead the creation of MVPs and proof-of-concepts to validate business opportunities rapidly.\nTranslate ambiguous business requirements into working prototypes and production-ready architectures.\nApply Lean Startup and product discovery principles to reduce delivery risk.\nDesign architectures that support iterative experimentation and fast market feedback.\nAI Harness Engineering\nDesign and maintain AI harnesses that enable engineers, analysts, and business teams to effectively utilize AI.\nBuild reusable AI workflows, prompts, agents, evaluation frameworks, and engineering accelerators.\nEstablish standards for prompt engineering, agent orchestration, AI testing, and model evaluation.\nDevelop reusable AI assets and playbooks that increase organizational productivity.\nEngineering Productivity & AI Transformation\nDrive adoption of AI-assisted software development practices.\nEstablish AI-native development workflows utilizing coding assistants, agentic development tools, and automated testing systems.\nDefine best practices for human-AI collaboration across the software delivery lifecycle.\nContinuously identify opportunities where AI can improve engineering velocity and quality.\nTechnical Leadership\nGuide engineering teams in implementing scalable, secure, and maintainable solutions.\nConduct architecture reviews and provide technical governance.\nMentor engineers, technical leads, and architects on AI-native development approaches.\nEstablish architecture standards and reusable reference architectures.\nEmerging Technology Research\nEvaluate emerging AI models, frameworks, and engineering tools.\nContinuously assess advancements in AI, cloud, data, and platform technologies.\nRecommend new technologies that create strategic advantages for clients and internal 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