Provide cybersecurity expertise throughout the AI and software development lifecycle, ensuring secure design, development, deployment, and operation of AI and cloud applications.
Responsibilities
Work closely with AI developers, software engineering teams, cloud engineering, enterprise architecture, data teams, and business stakeholders to embed security into pro-code development
Act as the SME for Microsoft Azure cloud security, application security, identity and access management, AI security, and the NIST Cybersecurity Framework
Provide cybersecurity expertise and technical guidance for enterprise AI, generative AI, LLM, agentic AI, and conversational AI solutions
Perform security assessments across the complete AI application lifecycle
Assess the security of LLM-based applications, AI agents, Chat UIs, APIs, plugins/tools, data sources, retrieval systems, and application integrations
DevSecOps Engineer embedding security throughout Azure-based SDLC, managing CI/CD pipelines, infrastructure automation, and security tooling
Compensation
We offer a hybrid work model which recognizes the value of striking a balance between in-person collaboration and remote working incl. up to 25 days per year working from abroad
Responsibilities
Lead rollout of Dynamic Application Security Testing (DAST)
Design DAST test coverage for AuthN/AuthZ flaws
Own reporting and remediation workflows for DAST findings
Support and extend the wider DevSecOps pipeline
Administer and optimise GitHub Enterprise
Requirements
Bachelor's degree in Computer Science, Information Technology, or related field
Nice to have: Certifications in DevOps and/or security-related fields
Nice to have: Experience with Azure Cosmos DB
Nice to have: MongoDB
Nice to have: cloud-to-cloud or on-prem-to-cloud database migrations
This position is responsible for making Infrastructure as Code (IaC) the way PERA builds and changes infrastructure. On-premises and AWS resources are defined in code, reviewed, and delivered through pipelines from GitHub Enterprise repositories.
Responsibilities
Provision on-premises and AWS infrastructure through version-controlled Infrastructure as Code, with no manual, console or ad hoc changes
Inventory existing manually built infrastructure and bring it under IaC based on priorities, starting with critical services
Run scheduled drift detection and alert on, correct or codify out-of-band changes
Maintain GitHub Enterprise repositories as the single source of truth, following a documented standard for structure, naming, ownership and CODEOWNERS
Enforce repository rulesets for pull requests, required reviews, required status checks and signed commits on protected branches
Requirements
Degree in technical (STEM) field
Nice to have: AWS Practitioner/Associate certification
Support technical due diligence and transition readiness by using AI-assisted software engineering methods to understand complex codebases, reconstruct dependencies, diagnose builds, accelerate documentation, and improve handover readiness in enterprise cloud and platform environments.
Locations (2)
Košice, Košický kraj, Slovakia
Slovakia
Compensation
Base salary will not be lower than 1850€ /brutto.
Responsibilities
Analyse large software repositories to map services, dependencies, interfaces, build flows, and technical risks relevant to technical due diligence.
Reconstruct the architecture of a cloud software stack derived from OpenStack, including key service boundaries, integration points, APIs, and operational dependencies.
Use AI coding agents and structured prompting patterns to accelerate code understanding, reverse engineering, and documentation generation across large codebases.
Support build-log diagnosis, compile issue triage, and reproducibility analysis across CI/CD pipelines and container-based delivery environments.
Serve as the technical service owner for Duke's enterprise AI platforms, including platform administration, licensing, access management, integrations, and operational support, while helping to advance AI across higher education, healthcare, and research.
Responsibilities
Serve as the technical service owner for Duke's enterprise AI platforms
Monitor platform performance, adoption, usage trends, and emerging technologies
Partner with security, privacy, compliance, legal, and data governance teams to support responsible AI deployment
Consult with departments on AI adoption opportunities and develop training materials
Build automation and integration solutions using AI technologies, APIs, workflow tools, PowerShell, Python
Requirements
Bachelor's degree in Information Technology, Computer Science, Information Systems, Business, Engineering, or a related field
Lead multidisciplinary engineering and product teams to deliver large‑scale, AI‑driven, cloud‑native solutions integrating DevSecOps and Gen‑e2 methodology.
Responsibilities
Lead high‑impact AI‑driven engineering initiatives
Define technical strategy and support clients in transformative adoption of AI‑driven delivery models
Conduct technical analyses and facilitate client workshops
Implement Gen‑e2 best practices across product repository artifacts and AI prompt libraries
Wyetech is seeking a talented and experienced Software Engineer responsible for designing, developing, and implementing complex software capabilities for computer-based systems. The Software Engineer will work closely with other engineers to create software solutions that meet client needs.
Produce structured handover artefacts including architecture summaries, dependency maps, code quality observations, and readiness assessments for receiving engineering teams.
Wyetech hourly salary range pending confirmation. Hourly pay rates listed for this position serve as a general guideline and are not a guarantee of compensation. Compensation will vary dependent upon factors including but not limited to: Government contract rates; education; relevant prior work experience, knowledge, skills, and competencies; certifications, and geographic location. Hourly pay rates reflect the pre-benefit gross wage amounts.
Responsibilities
Designing, developing, and implementing complex software capabilities for computer-based systems
Working closely with other engineers to create software solutions that meet client needs
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