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описание
Exadel is an AI-first global technology company that provides engineering and digital transformation services, including AI platforms, enterprise solutions, and customer projects.
задачи
Design, build, and maintain internal applications, automations, and AI-powered workflows;
Develop backend services and APIs in Python, Java Script (Node), and related technologies;
Build user-facing tools and dashboards using React;
Integrate LLMs and external services into business workflows using OpenAI, Gemini, AWS, and GCP;
Partner with data scientists to productionize prototypes and analytical solutions;
Improve the architecture, reliability, testing, observability, and deployment of team-owned systems;
Work with business, operations, and sales stakeholders to understand pain points and translate them into practical solutions;
Identify opportunities to automate repetitive work and streamline internal processes;
Establish engineering best practices for code quality, system design, CI/CD, and documentation;
Mentor other engineers and help raise the overall engineering bar of the team.
требования
Solid commercial experience in software engineering focused on building production systems;
Strong backend engineering skills, ideally in Python;
Experience building modern web applications with React;
Experience designing and consuming APIs, integrating third-party services, and building automation workflows;
Solid understanding of software architecture, system design, and scalable application development;
Experience with AWS, GCP, or Azure;
Experience with containers, deployment pipelines, and production engineering practices;
Familiarity with LLM-based application development, including OpenAI, Gemini, or similar platforms;
Ability to evaluate when AI is useful in a workflow and when traditional engineering patterns are better;
Strong communication skills and ability to work with technical and non-technical stakeholders;
Proven ability to turn ambiguous business needs into working software;
English at Upper-Intermediate level;
Nice to have: workflow orchestration and automation tooling, internal tools or sales enablement systems, vector databases, retrieval pipelines, agentic workflows, prompt design, asynchronous processing, task queues, event-driven systems, analytics, experimentation, collaboration with data science or ML teams, Postgres, data storage technologies, observability, monitoring, production support, SaaS, enterprise platforms, customer-facing solution engineering.