AI engineer

Planck Technologies is a company specialized in Software Development, dedicated to shaping futures and creating value through innovative IT solutions. By expanding teams and offering a comprehensive range of services from Software Development and Infrastructure Management to Cybersecurity we empower clients with all the expertise they need in one place. Inspired by the principles of quantum physics, we push beyond traditional boundaries to deliver customized solutions that redefine the IT landscape and drive shared success.

• Build AI applications, assistants, agents, and workflow automation components using modern Generative AI engineering practices;
• Design and implement integrations with Azure AI services, Azure AI Foundry, APIs, enterprise systems, data platforms, and internal tools;
• Develop Retrieval-Augmented Generation (RAG) components and implement tool-use, orchestration, evaluation, and monitoring capabilities;
• Design and implement guardrails to ensure the reliability, security, and responsible operation of production AI solutions;
• Collaborate with data engineers and data scientists to connect models, prompts, workflows, and data pipelines into reliable end-to-end solutions;
• Support the implementation of agentic workflows that can be reused across different country teams;
• Develop and optimize AI-enabled automation solutions to address business needs;
• Improve developer experience, engineering standards, and reusable templates for AI software development;
• Ensure production readiness and scalability of AI applications and solutions;
• Contribute to the continuous improvement of GenAI engineering practices and delivery processes.

• Proven experience as an AI Engineer, GenAI Engineer, or Software Engineer focused on AI solutions;
• Strong software engineering skills in Python and SQL;
• Hands-on experience building GenAI applications, AI assistants, agents, and AI-enabled workflow automation;
• Experience with Azure AI services, Azure AI Foundry, or comparable AI platforms;
• Solid understanding of Retrieval-Augmented Generation (RAG), prompt engineering, and context engineering;
• Knowledge of tool calling, orchestration, evaluation, monitoring, and guardrails for production AI systems;
• Experience integrating APIs, cloud-native services, data pipelines, and enterprise systems;
• Familiarity with GenAI software engineering tools such as GitHub Copilot, Cursor, or OpenCode;
• Ability to translate ambiguous business requirements into reliable and scalable technical solutions;
• Strong problem-solving skills and a product-oriented engineering mindset;
• Ability to collaborate with data engineers, data scientists, and cross-functional teams.
• Будет плюсом: Experience with Microsoft Agent Framework, LangChain, MCP, or comparable agent frameworks; Experience with agentic workflow builders, dashboards, or user-facing AI applications; Knowledge of Snowflake and vector databases; Experience with AI observability tooling and LLM gateway patterns; Experience building reusable AI components and solutions for enterprise environments

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