IT 与编程
AI Engineer - AWS Bedrock AgentCore & Production Agentic Systems | LATAM & Europe(远程职位)
Toptal
AI Engineer - AWS Bedrock AgentCore & Production Agentic Systems | LATAM & Europe:「IT 与编程」类别,完全远程
这条招聘信息来自 Toptal,岗位是 AI Engineer - AWS Bedrock AgentCore & Production Agentic Systems | LATAM & Europe。职位属于「IT 与编程」类别,完全远程。公司不限制候选人的居住地,在任何地方都可以申请。
招聘信息里列出的主要工具是:AWS、Python。简历上最好能给出正是这几项能力的具体例子。
公司没有公布具体数字,这一项会在面试时谈定。对工作时间,招聘信息没有提出任何条件。
这个职位通过了自动核查:凡是要求外国工作许可、签证担保、特定国籍,或者必须居住在指定国家的招聘信息,都不会进入列表。
要点
- 公司
- Toptal
- 类别
- IT 与编程
- 谁可以申请
- 来自世界任何国家
- 工作方式
- 完全远程
- 工具
- AWS, Python
- 发布时间
- 2026年7月28日 (29 天前)
- 有效期
- 截至 2026年9月6日
- 来源
- We Work Remotely
新职位邮件提醒:IT 与编程
职位板每天更新数次。只有出现新的、已核查的职位时才会写信。不发垃圾邮件,也不需要注册账号。
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Telegram 上的最新职位
每一条新的远程职位,发布即推送。无需注册。
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公司发布的职位描述
Headquarters: Remote
URL: https://www.toptal.com/
About the Role
We're looking for engineers to help build and productionize AI systems on AWS Bedrock AgentCore - real conversational AI, RAG pipelines, and agent architectures that go well beyond proof-of-concept and serve live traffic and real users. Whether your strength is on the AI application side (agents, RAG, orchestration) or the platform side (deployment, observability, security), this role sits at the center of turning working demos into production-grade, reliable systems on Bedrock's agentic stack. If you've built and shipped on AgentCore specifically - not just Bedrock in general - and want your work to run in production rather than sit in a notebook, this is built for that.
What You'll Do
* Design, build, and deploy conversational AI systems, chatbots, and AI agents using AWS Bedrock AgentCore
* Architect and ship production-grade RAG (Retrieval-Augmented Generation) systems - not prototypes, but systems serving live traffic
* Build and deploy LLM applications primarily on AWS Bedrock and AgentCore, with Azure OpenAI or equivalent platforms as secondary context
* Develop and orchestrate agent architectures within AgentCore, using frameworks such as LangChain, LangGraph, or LlamaIndex where applicable
* Build and maintain MCP (Model Context Protocol) server integrations to extend AgentCore agent capabilities
* Design and build the production service layer around AgentCore (Lambda, API Gateway, IAM, DynamoDB, OpenSearch, or equivalents)
* Establish CI/CD pipelines and manage development, beta, and production environments for AgentCore-based services
* Implement observability for AgentCore agents: tracing, dashboards, per-turn cost and latency metrics, error rates, and audit trails
* Implement key security controls - data-leakage protection, session isolation, auth/authz boundaries, secure prompt/response storage
* Write clean, maintainable, production-quality Python across the AI application and platform stack
* Monitor, evaluate, and iterate on agent, RAG, and platform performance in production
* Stay current with fast-moving developments in Bedrock, AgentCore, and agentic AI systems, and bring relevant advances into the project
What You Bring
* Proven, hands-on experience building and deploying AI agents on AWS Bedrock AgentCore in a production environment - not personal projects or tutorials
* Direct experience with AWS Bedrock's agentic tooling (AgentCore, Bedrock Agents, or equivalent Bedrock-native orchestration)
* Strong Python skills for AI application development and/or service integration
* Working experience with AWS cloud environments; Azure experience is a plus but not the primary requirement
* Experience with at least one of: agent orchestration frameworks (LangChain, LangGraph, LlamaIndex), RAG system design, or AWS production infrastructure (Lambda, API Gateway, IAM, DynamoDB, OpenSearch)
* Experience with observability and monitoring for AI or distributed systems
* Strong understanding of security, data handling, and production-readiness tradeoffs
* Comfortable working in a fast-moving, evolving technical environment with pragmatic engineering judgment
Nice to Have
* Experience with MCP servers
* Experience with infrastructure-as-code (CDK, CloudFormation) and CI/CD pipeline design
* Experience with distributed data tools such as Apache Spark, PySpark, or AWS EMR
* Experience with Amazon SageMaker or similar ML platforms
* Experience with OpenSearch vector search administration for RAG workloads
* Experience building data pipelines for AI evaluation and KPI extraction
* Experience with Azure OpenAI or other non-AWS LLM platforms
* Comfort working in an AI-assisted development environment using AI build and review tools
How to Apply
Ready to build production agentic systems on AWS Bedrock AgentCore? Apply through Toptal here: https://www.toptal.com/talent/apply
To apply: https://weworkremotely.com/remote-jobs/toptal-ai-engineer-aws-bedrock-agentcore-production-agentic-systems-latam-europe
职位正文保留公司发布时的原文,因为投递的时候用的也是同一种语言。
关于这个职位的常见问题
我可以在自己居住的地方申请「AI Engineer - AWS Bedrock AgentCore & Production Agentic Systems | LATAM & Europe」这个职位吗?
可以。对于这个职位,Toptal 接受来自世界任何国家的候选人,所以你不需要其他国家的工作许可。这条招聘信息通过了自动核查:如果雇主要求工作许可、签证担保,或者必须居住在某个特定国家,它就不会出现在本站。
标明的报酬是多少?
对于这个职位,Toptal 没有公布报酬。多数远程招聘信息不给出具体数字,这件事会在面试时谈定。
怎么申请?
你通过发布在 We Work Remotely 上的原始招聘信息,直接向雇主提交申请。Donator 不代收申请,不收取佣金,也不保存简历。
这是什么类型的职位?
这是「IT 与编程」类别中的一个完全远程职位。混合办公的招聘信息,以及任何需要到办公室的职位,本站都不会发布。
适合这个职位的免费证书
这条招聘信息要求 Python。下面是正好覆盖这几项工具的免费证书。
CS50x: Introduction to Computer Science
certificateHarvard CS50 · ~100 h
Harvard's own branded certificate is free once you pass every problem set and the final project. The edX verified certificate is a separate paid product and is not needed.
strong brandCS50P: Programming with Python
certificateHarvard CS50 · ~60 h
Same mechanism as CS50x: at least 70% on every assignment plus a final project. The certificate does not expire.
strong brandPython Essentials 1 and 2
digital badgeCisco Networking Academy · ~60 h
A two-part course with a separate badge for each part. It also doubles as preparation for OpenEDG's paid PCEP exam.
strong brandDeveloper certificates (10+ tracks)
certificatefreeCodeCamp · ~300 h
A non-profit; a card is never requested. The certificate is issued after five projects are submitted and pass.
moderate weight
