{"schemaVersion":"jobsearcher.job.v1","id":"bdcba182fd5b1ce0c0c65af1","url":"https://jobsearcher.com/jobs/bdcba182fd5b1ce0c0c65af1","canonicalUrl":"https://jobsearcher.com/jobs/bdcba182fd5b1ce0c0c65af1","title":"AWS Technical Apprentice / Trainee","description":"Job Title: Principal / Senior AI Engineer (Agentic AI | Python | AWS)\nLocation: Richmond, VA or McLean, VA (Hybrid Local Candidates Only) InPerson Interview 1 st preference ex Capone\nDuration: 7 Months Contract\nRole Overview: We are seeking a highly experienced Principal / Senior AI Engineer to join a fast-paced, cross-functional engineering team within a leading enterprise organization. This is a hands-on builder role focused on designing and delivering Agentic AI solutions and transforming Generative AI prototypes into scalable, production-grade systems. The ideal candidate will have deep expertise in Python full-stack development, LLMs, and AWS cloud architecture, along with proven experience building reliable, secure, and high-performance AI-driven applications.\nKey Responsibilities\nAgentic AI & Application Development: Design, develop, and deploy AI-driven applications and multi-agent systems using frameworks like LangChain, LangGraph, and CrewAI\nBuild agentic workflows to automate complex engineering and business processes\nRAG & LLM Engineering: Develop and optimize Retrieval-Augmented Generation (RAG) pipelines using Amazon Bedrock and vector databases (OpenSearch, Pinecone)\nWork with LLMs (GPT, Claude, Llama) for real-world enterprise use cases\nImplement LLM orchestration, tool usage, and function calling\nFull-Stack & Backend Development: Develop scalable applications using Python (frontend & backend), FastAPI, Pydantic, and async programming\nEnable real-time AI capabilities including streaming responses and APIs\nAI Integration & Enterprise Systems: Integrate AI solutions with enterprise platforms such as ServiceNow, CMDB, and JIRA\nCollaborate with frontend teams (React) to deliver intuitive AI-powered user experiences\nResponsible AI & Governance: Implement guardrails including prompt engineering, content moderation, bias detection, and output validation\nEnsure compliance with enterprise security and AI governance standards\nObservability, Evaluation & MLOps: Build evaluation frameworks using Ragas, DeepEval\nImplement observability using LangSmith, OpenTelemetry\nDevelop and maintain CI/CD pipelines for AI/ML workflows, prompt versioning, and deployment\nEngineering Excellence: Contribute to system design, architecture, and best practices\nProvide technical leadership and AI expertise across teams\nDrive improvements in engineering and operational excellence\nRequired Qualifications\n10+ years of overall software engineering experience\n7+ years of strong hands-on experience with Python (full-stack/backend)\n2+ years of hands-on experience in AI / Generative AI / LLMs\n5+ years of experience with AWS cloud (Bedrock, SageMaker, Lambda, etc.)\nProven experience building scalable, production-grade applications\nStrong knowledge of system design, distributed systems, and backend architecture\nTechnical Skills:\nAI / GenAI: GPT-series, Claude, Llama, Hugging Face Transformers, PEFT\nAgent Frameworks: LangChain, LangGraph, CrewAI, multi-agent systems, tool usage, function calling\nBackend / Full Stack : Python 3.10+, FastAPI, Pydantic, Async programming\nCloud & Infrastructure : AWS (Bedrock, SageMaker, Lambda, RDS, pgvector), Serverless architecture\nVector Databases : OpenSearch, Pinecone\nObservability & Evaluation : LangSmith, OpenTelemetry, Ragas, DeepEval\nPreferred Qualifications\nExperience building production-grade AI/ML platforms\nHands-on experience with LLM fine-tuning\nExperience with multi-agent AI systems\nFamiliarity with CI/CD pipelines and MLOps practices\nPrior experience with Client (highly preferred)\nExperience with enterprise-scale integrations and platforms\n-\nFor applications and inquiries, contact: hirings@openkyber.com","company":"Openkyber","rawCompany":"openkyber","city":"Puposky","state":"MN","isRemote":false,"isActive":false,"createdAt":"2026-08-15T12:53:49.210Z","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":"15-1251.00","title":"Computer Programmers","slug":"computer-programmers"}],"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":"AWS Technical Apprentice / Trainee","description":"Job Title: Principal / Senior AI Engineer (Agentic AI | Python | AWS)\nLocation: Richmond, VA or McLean, VA (Hybrid Local Candidates Only) InPerson Interview 1 st preference ex Capone\nDuration: 7 Months Contract\nRole Overview: We are seeking a highly experienced Principal / Senior AI Engineer to join a fast-paced, cross-functional engineering team within a leading enterprise organization. This is a hands-on builder role focused on designing and delivering Agentic AI solutions and transforming Generative AI prototypes into scalable, production-grade systems. The ideal candidate will have deep expertise in Python full-stack development, LLMs, and AWS cloud architecture, along with proven experience building reliable, secure, and high-performance AI-driven applications.\nKey Responsibilities\nAgentic AI & Application Development: Design, develop, and deploy AI-driven applications and multi-agent systems using frameworks like LangChain, LangGraph, and CrewAI\nBuild agentic workflows to automate complex engineering and business processes\nRAG & LLM Engineering: Develop and optimize Retrieval-Augmented Generation (RAG) pipelines using Amazon Bedrock and vector databases (OpenSearch, Pinecone)\nWork with LLMs (GPT, Claude, Llama) for real-world enterprise use cases\nImplement LLM orchestration, tool usage, and function calling\nFull-Stack & Backend Development: Develop scalable applications using Python (frontend & backend), FastAPI, Pydantic, and async programming\nEnable real-time AI capabilities including streaming responses and APIs\nAI Integration & Enterprise Systems: Integrate AI solutions with enterprise platforms such as ServiceNow, CMDB, and JIRA\nCollaborate with frontend teams (React) to deliver intuitive AI-powered user experiences\nResponsible AI & Governance: Implement guardrails including prompt engineering, content moderation, bias detection, and output validation\nEnsure compliance with enterprise security and AI governance standards\nObservability, Evaluation & MLOps: Build evaluation frameworks using Ragas, DeepEval\nImplement observability using LangSmith, OpenTelemetry\nDevelop and maintain CI/CD pipelines for AI/ML workflows, prompt versioning, and deployment\nEngineering Excellence: Contribute to system design, architecture, and best practices\nProvide technical leadership and AI expertise across teams\nDrive improvements in engineering and operational excellence\nRequired Qualifications\n10+ years of overall software engineering experience\n7+ years of strong hands-on experience with Python (full-stack/backend)\n2+ years of hands-on experience in AI / Generative AI / LLMs\n5+ years of experience with AWS cloud (Bedrock, SageMaker, Lambda, etc.)\nProven experience building scalable, production-grade applications\nStrong knowledge of system design, distributed systems, and backend architecture\nTechnical Skills:\nAI / GenAI: GPT-series, Claude, Llama, Hugging Face Transformers, PEFT\nAgent Frameworks: LangChain, LangGraph, CrewAI, multi-agent systems, tool usage, function calling\nBackend / Full Stack : Python 3.10+, FastAPI, Pydantic, Async programming\nCloud & Infrastructure : AWS (Bedrock, SageMaker, Lambda, RDS, pgvector), Serverless architecture\nVector Databases : OpenSearch, Pinecone\nObservability & Evaluation : LangSmith, OpenTelemetry, Ragas, DeepEval\nPreferred Qualifications\nExperience building production-grade AI/ML platforms\nHands-on experience with LLM fine-tuning\nExperience with multi-agent AI systems\nFamiliarity with CI/CD pipelines and MLOps practices\nPrior experience with Client (highly preferred)\nExperience with enterprise-scale integrations and platforms\n-\nFor applications and inquiries, contact: hirings@openkyber.com","datePosted":"2026-08-15T12:53:49.210Z","dateModified":"2026-08-15T12:53:49.210Z","hiringOrganization":{"@type":"Organization","name":"Openkyber","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Puposky","addressRegion":"MN","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"bdcba182fd5b1ce0c0c65af1"},"url":"https://jobsearcher.com/jobs/bdcba182fd5b1ce0c0c65af1"}}