{"schemaVersion":"jobsearcher.job.v1","id":"b6e47ae9783cec3876ea372d","url":"https://jobsearcher.com/jobs/b6e47ae9783cec3876ea372d","canonicalUrl":"https://jobsearcher.com/jobs/b6e47ae9783cec3876ea372d","title":"Senior Python Developer","description":"Role Summary We are looking for an AI Native Development Architect to design and guide the build of cloud-native, data- and AI-driven applications on AWS. You will define target architectures, enable engineering teams with reusable patterns and reference implementations, and accelerate delivery using modern AI-assisted development tools.\nKey Responsibilities:\nDefine end-to-end architecture for AI-native products, including application, data, integration, security, and operations on AWS.\nLead design reviews and provide technical direction across Python and C#/.NET codebases.\nArchitect data pipelines and analytical workloads using PySpark and AWS Glue; establish standards for data quality, lineage, and observability.\nDesign and implement scalable APIs and microservices using FastAPI (and/or .NET Web APIs) with clear contracts, versioning, and performance SLAs.\nEstablish reference architectures for LLM/RAG-enabled capabilities (e.g., retrieval patterns, prompt management, evaluation, guardrails) aligned with organizational policies.\nPartner with Security, Platform, and DevOps teams to implement secure-by-design practices (IAM, secrets, network controls, encryption, threat modeling).\nDefine CI/CD, branching, testing, and release practices; improve developer productivity with automation and paved-road templates.\nChampion AI-assisted engineering workflows using tools such as GitHub Copilot, Cursor, and Claude AI while ensuring code quality and compliance.\nMentor engineers, create technical documentation, and drive adoption of best practices across teams.\nRequired Skills Primary Skills: Python : strong hands-on experience building services and data workloads using Python, PySpark, AWS Glue, and FastAPI. C#/.NET : ability to design and review .NET services and libraries; familiarity with modern .NET runtime and patterns. AWS : strong understanding of AWS architecture fundamentals (networking, IAM, compute, storage, managed services) and designing for scale, reliability, and cost. AI Native Development Tools Proficiency using AI coding assistants to accelerate development while maintaining engineering rigor: GitHub Copilot, Cursor, Claude AI. Ability to establish team guidelines for AI-assisted coding (review standards, secure prompting, IP/compliance awareness, and validation/testing). Preferred Qualifications: Experience designing GenAI solutions (RAG, tool/function calling, agents) and implementing evaluation/monitoring approaches. Experience with infrastructure as code (e.g., CloudFormation/CDK/Terraform) and container platforms (Docker/ECS/EKS). Knowledge of MLOps patterns (model lifecycle, feature stores, experiment tracking) and data governance concepts. Strong understanding of observability practices (logs/metrics/traces) and SRE-oriented reliability design. Soft Skills & Competencies: Architecture leadership: can balance short-term delivery with long-term platform thinking. Clear communication: can translate complex technical decisions for engineering and business stakeholders. Hands-on mindset: comfortable prototyping and jumping into code to unblock teams. Quality and security focus: promotes testing discipline, secure coding, and operational readiness. Collaboration and mentorship: builds alignment, coaches engineers, and scales best practices across squads. What Success Looks Like (First 90 Days): Established reference architectures and coding standards for AI-native services; improved delivery throughput via AI-assisted workflows; delivered at least one production-ready blueprint (API + data pipeline) on AWS with strong security, observability, and cost controls.\nFor applications and inquiries, contact: hirings@openkyber.com","company":"Openkyber","rawCompany":"openkyber","city":"Alaska","state":"MI","isRemote":false,"isActive":false,"createdAt":"2026-08-05T11:55:30.688Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Senior Python Developer","description":"Role Summary We are looking for an AI Native Development Architect to design and guide the build of cloud-native, data- and AI-driven applications on AWS. You will define target architectures, enable engineering teams with reusable patterns and reference implementations, and accelerate delivery using modern AI-assisted development tools.\nKey Responsibilities:\nDefine end-to-end architecture for AI-native products, including application, data, integration, security, and operations on AWS.\nLead design reviews and provide technical direction across Python and C#/.NET codebases.\nArchitect data pipelines and analytical workloads using PySpark and AWS Glue; establish standards for data quality, lineage, and observability.\nDesign and implement scalable APIs and microservices using FastAPI (and/or .NET Web APIs) with clear contracts, versioning, and performance SLAs.\nEstablish reference architectures for LLM/RAG-enabled capabilities (e.g., retrieval patterns, prompt management, evaluation, guardrails) aligned with organizational policies.\nPartner with Security, Platform, and DevOps teams to implement secure-by-design practices (IAM, secrets, network controls, encryption, threat modeling).\nDefine CI/CD, branching, testing, and release practices; improve developer productivity with automation and paved-road templates.\nChampion AI-assisted engineering workflows using tools such as GitHub Copilot, Cursor, and Claude AI while ensuring code quality and compliance.\nMentor engineers, create technical documentation, and drive adoption of best practices across teams.\nRequired Skills Primary Skills: Python : strong hands-on experience building services and data workloads using Python, PySpark, AWS Glue, and FastAPI. C#/.NET : ability to design and review .NET services and libraries; familiarity with modern .NET runtime and patterns. AWS : strong understanding of AWS architecture fundamentals (networking, IAM, compute, storage, managed services) and designing for scale, reliability, and cost. AI Native Development Tools Proficiency using AI coding assistants to accelerate development while maintaining engineering rigor: GitHub Copilot, Cursor, Claude AI. Ability to establish team guidelines for AI-assisted coding (review standards, secure prompting, IP/compliance awareness, and validation/testing). Preferred Qualifications: Experience designing GenAI solutions (RAG, tool/function calling, agents) and implementing evaluation/monitoring approaches. Experience with infrastructure as code (e.g., CloudFormation/CDK/Terraform) and container platforms (Docker/ECS/EKS). Knowledge of MLOps patterns (model lifecycle, feature stores, experiment tracking) and data governance concepts. Strong understanding of observability practices (logs/metrics/traces) and SRE-oriented reliability design. Soft Skills & Competencies: Architecture leadership: can balance short-term delivery with long-term platform thinking. Clear communication: can translate complex technical decisions for engineering and business stakeholders. Hands-on mindset: comfortable prototyping and jumping into code to unblock teams. Quality and security focus: promotes testing discipline, secure coding, and operational readiness. Collaboration and mentorship: builds alignment, coaches engineers, and scales best practices across squads. What Success Looks Like (First 90 Days): Established reference architectures and coding standards for AI-native services; improved delivery throughput via AI-assisted workflows; delivered at least one production-ready blueprint (API + data pipeline) on AWS with strong security, observability, and cost controls.\nFor applications and inquiries, contact: hirings@openkyber.com","datePosted":"2026-08-05T11:55:30.688Z","dateModified":"2026-08-05T11:55:30.688Z","hiringOrganization":{"@type":"Organization","name":"Openkyber","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Alaska","addressRegion":"MI","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"b6e47ae9783cec3876ea372d"},"url":"https://jobsearcher.com/jobs/b6e47ae9783cec3876ea372d"}}