Если вы раньше входили через Google, сбросьте пароль для своей Gmail-почты через кнопку «Забыли пароль?» на экране входа. Затем войдите по email и новому паролю.
Если аккаунта ещё нет, зарегистрируйтесь с Gmail-почтой — после подтверждения почты мы предложим задать пароль.
Что нового
Загружаю обновления...
Что нового
Загружаю обновления...
Работа найдется быстрее с подпискойКандидат найдётся быстрее с подпиской
Чтобы адаптировать резюме под вакансию или составить сопроводительное письмо, загрузите резюме
описание
The company develops enterprise software products, open-source solutions, and accelerators. The role focuses on an AI initiative that brings Conversational AI to Service Desk request submission through guided chat experiences and integrated ITSM workflows.
задачи
Develop the React chat frontend for submitting service requests through guided conversations;
Create the central Frontdesk Agent for classifying and routing user intent;
Build the agent hub that coordinates the multi-agent system using Spring AI AgentCore;
Design and maintain an ETL pipeline for ServiceNow Service Catalog metadata;
Index catalog metadata into AWS Bedrock Knowledge Bases and keep it updated;
Build a reusable agent framework with capability templates, tool definitions, prompt scaffolding, and an agentic conversion workflow;
Create individual catalog item agents that manage complete request submissions and integrate with ServiceNow APIs;
Monitor agent interactions and LLM calls using OpenTelemetry and Dynatrace;
Maintain standards for code quality, testability, and documentation;
Use AI-assisted development tools to improve efficiency;
Provide leadership and mentorship to team members;
Direct architectural decisions throughout the project.
требования
At least 6 years of software engineering experience, including at least 2 years in a technical leadership capacity;
Strong Java and Spring Boot skills;
Strong Node.js backend development skills;
Hands-on experience with AWS Lambda, API Gateway, and S3;
Working knowledge of AWS IAM and KMS;
Strong knowledge of LLM and AI engineering principles, including prompt design, RAG pipelines, agentic patterns, tool usage, and LLM evaluation;
Experience with Spring AI or comparable LLM orchestration frameworks;
Experience with AWS Bedrock AgentCore and Knowledge Bases or similar managed RAG/vector solutions;
Proficiency with Docker, Git, and Terraform;
Knowledge of GitHub Actions for CI/CD pipelines;
Ability to make independent decisions, navigate ambiguity, and resolve blockers through research and testing;
English at B2+ level or higher;
Nice to have: React.JS, Python for automation scripting, ServiceNow Service Catalog.