2535 Cloud Engineer Multiple Openings jobs in Atlanta,GA

Data Analyst 2 - IT Help Desk [209668]

Aquent Talent

Atlanta, GA

Degree in Computer Science, Data Analytics, or a related field
Azure Data Fundamentals
Power BI Data Analyst Associate
Azure AI Fundamentals
Experience using Azure Machine Learning to build low-code/no-code solutions
Hands-on experience with ServiceNow data and IT Service Management (ITSM) modules
Strong experience with Power BI, including data visualization, modeling, and DAX
Working knowledge of SQL and Kusto Query Language (KQL)

Skill

Atlanta, GA

This requisition is for the US Citizen seat on a three-person engineering team.
The selected candidate will be the team's designated US-based resource
Must be a US Citizen — Lawful Permanent Residents do not qualify for this role.
Demonstrable product-security or regulated-compliance background (CRA, IEC 62443, FDA, DoD, ISO 27001, or similar) with the ability to translate regulation into technical solutions
Hands-on, production-scale experience with SAST and SCA tools (e.g., Veracode, CodeSonar)
Practical experience generating and maintaining SBOMs
CI/CD build and automation across GitHub, GitLab, GitHub Actions, and AWS
Working knowledge of C and C++
Working knowledge of Python (automation scripts, supporting tools)
Experience integrating security into multiple build systems and toolchains (CMake, Make, vendor-specific)
Track record scaling security workflows across portfolios with many repositories and a mix of legacy and greenfield work
Experience designing or contributing to vulnerability, waiver, or risk-acceptance databases
Awareness of embedded systems and long-lifecycle product constraints

Cargill

Atlanta, GA 30303

Minimum requirement of 6 years of relevant work experience.
Typically reflects 10 years or more of relevant experience.
10+ years of experience in cybersecurity architecture or engineering roles.
Strong understanding of modern AI/ML architectures, pipelines, and platforms.
Hands-on experience with Generative AI and Agentic AI security, including LLMs, AI agents, prompt safety testing, and AI governance.
Ability to clearly communicate AI security risks to technical and non-technical stakeholders.