Why this role stands out
This hybrid role offers a fantastic opportunity to grow your AI integration and security expertise by developing cutting-edge Python solutions for mission-critical applications, with a competitive salary and excellent benefits. You'll thrive here if you're a skilled Python developer with a passion for AI, problem-solving, and collaborating within a dynamic team environment. Apply now to contribute to impactful projects and advance your career in a reputable organization.
Quick overview
Job description
Job Description Kryptauri is seeking a Software Engineer to connect AI capabilities with the data and tools that mission professionals use every day. Working alongside senior engineers, you will develop Python integrations that bring models, external APIs, and multiple data sources into dependable operational workflows. Your work will include building tools with the Model Context Protocol and agent frameworks such as PydanticAI, LangGraph, and DeepAgents. You will clarify user needs, locate relevant information within varied datasets, and test integrations with fellow developers. As capabilities mature, you will troubleshoot failures and improve how AI services fit into existing software environments.
Required Skills Three years of relevant experience and a bachelor's degree in a technical discipline; four additional years of experience may substitute for the degree. Python proficiency for JSON processing, data manipulation, and REST API integration. Experience querying data through HTTP APIs. Understanding of prompt design, context management, structured model responses, and tool or function calling. Familiarity with Git, Jira, and Confluence. Ability to explain data analysis findings to customers.
Desired Skills Experience building agent workflows or coordinating multiple AI agents. Understanding of signals intelligence collection and analysis, cybersecurity workflows, or operational cyber capabilities. Experience automating delivery through GitLab CI/CD. Familiarity with retrieval-augmented generation, vector databases, or semantic search. Practical work in AI areas such as autonomous systems, planning, intelligent systems, or large language models. Familiarity with AWS, Docker, or Kubernetes.
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