aipythondockerawsragdynamodbopensearchprompt engineeringnodeagentic ai
Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата и рынок
$166к-228к/год
$190к$220кмедиана$300к
По похожим ролям (50) ~ $220к/год
На СНГ рынке: $4.2к/мес ($3.6к - $5.1к)
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Роль описана четко и предполагает работу с production AI, но обязательные еженедельные поездки к клиенту в США и широкий круг senior-задач могут подойти не всем.
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Работа в СШАПроектный форматФокус на AIСовременный стек
Оценка от Hirify AI
Мэтч & Сопровод
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Staff AI Developer (AI): Designing and delivering production-ready agentic and GenAI systems, including RAG pipelines, AWS integrations, evaluation, observability, and full-stack services with an accent on reliability, security, scalability, and end-to-end ownership. Focus on building multi-agent workflows, handling LLM failures, designing cloud-native architectures, and leading technical decisions across client delivery teams.
Location: Toronto, ON, or Canada remote; mandatory weekly on-site client delivery 3 days per week in the United States. Candidates must be legally authorized to work in Canada and eligible to secure immediate U.S. non-immigrant work authorization, such as TN status under USMCA.
Salary: $165,604–$228,491 USD annually.
Company
Robots & Pencils designs and delivers production-ready AI systems that integrate into enterprise operations and real-world workflows.
What you will do
Design and build agentic workflows with reasoning loops, tool and function calling, and single- or multi-agent orchestration.
Build and maintain RAG pipelines covering chunking, embeddings, vector search, re-ranking, and knowledge-source refresh handling.
Integrate AWS Bedrock, Agent Core, MCP-based tools, and production system prompts.
Develop evaluation and observability systems using golden datasets, RAGAS-style metrics, LLM-as-judge, and tracing tools.
Build Python and Node.js backend services, serverless AWS architectures, DynamoDB schemas, and event-driven workflows.
Lead architecture decisions, mentor engineers, and own features and releases through debugging, hardening, deployment, and production troubleshooting.
Requirements
6+ years of professional software engineering experience, including meaningful experience shipping GenAI or LLM-powered systems in production.
Hands-on expertise in agentic AI, including reasoning loops, tool or function calling, multi-agent orchestration, and evaluating single-agent versus multi-agent designs.
Practical RAG expertise with chunking strategies, embeddings, vector databases such as OpenSearch, cosine similarity search, and re-ranking.
Experience building LLM evaluation and observability with golden datasets, LLM-as-judge, RAGAS or comparable metrics, and LangFuse, LangSmith, or equivalent tracing.
Strong prompt engineering skills, including structured production system prompts, output constraints, and few-shot design.
Hands-on experience with AWS Bedrock, Agent Core, Lambda, DynamoDB single-table design, S3, SQS, EventBridge, and Step Functions.
Strong Python and Node.js skills, including full-stack application and RESTful API development.
Understanding of production reliability patterns for LLM systems, including retries with backoff, circuit breakers, and fallback models.
Experience with Docker, cloud-native deployment, ambiguous integration-heavy problems, and end-to-end ownership.
Legal authorization to work in Canada and eligibility for immediate U.S. non-immigrant work authorization for mandatory weekly U.S. on-site delivery.
Nice to have
Direct Amazon Bedrock Agent Core experience, including agent registration, MCP tool wiring, memory and session management, and gateway provisioning.
Experience in regulated or high-stakes domains such as education, healthcare, or financial services.
Familiarity with Step Functions, Sequencer, or similar state-machine workflow tools.
Production experience with LLM observability tooling.
Culture & Benefits
Work on cross-functional teams delivering production-ready AI systems in 30–45 days.
Collaboration with product, design, and delivery leads across global teams.
Paid time off and medical, dental, and vision insurance.
401(k) benefits for eligible employees.
Employment may be conditional on a background check under local legislation.
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