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278 results for Cybersecurity Engineer jobs
- Austin, TX
- onsite
- Temporary to Hire
- 39.5865 - 45.837 USD / Hourly
- <p>We are looking for a <strong>Network Architect</strong> to support our client's team here in Austin, Texas. This will be a contract opportunity with potential to become permanent. This position focuses on designing and maintaining reliable network environments while providing hands-on engineering support for controller troubleshooting and repair. The role is well suited for someone who can balance architecture planning with field-level problem solving and is comfortable with travel as part of project and support needs.</p><p><br></p><p><strong>Responsibilities:</strong></p><p>• Design and improve network architecture that supports renewable energy systems and related operational infrastructure.</p><p>• Provide engineering support for controller diagnostics, troubleshooting, and break-fix activities in live environments.</p><p>• Evaluate network performance and implement changes that strengthen stability, connectivity, and overall system reliability.</p><p>• Partner with technical teams to align infrastructure decisions with application, security, and operational requirements.</p><p>• Support integration efforts involving cloud platforms, APIs, and connected systems where network architecture plays a critical role.</p><p>• Travel to project or operating sites as needed to investigate issues, support deployments, and assist with technical resolution.</p><p>• Document architecture decisions, support procedures, and remediation steps to promote consistency across environments.</p>
- 2026-11-03T00:00:00Z
- Bloomington, MN
- remote
- Temporary / Contract
- 80 - 95 USD / Hourly
- We are looking for an experienced Profisee MDM Engineer to help strengthen and evolve a master data management environment in Bloomington, Minnesota. This Long-term Contract position will focus on improving platform performance, elevating data reliability, and creating more efficient stewardship practices that support broader business use. The role will work closely with technical and business partners to expand the value of master data across connected systems, analytics, and operational processes.<br><br>Responsibilities:<br>• Evaluate the current Profisee MDM landscape and define a practical strategy to enhance scalability, usability, and long-term sustainability.<br>• Refine platform design and configuration to eliminate unnecessary complexity and improve ongoing supportability.<br>• Create and implement automated solutions that reduce manual stewardship tasks and increase process efficiency.<br>• Strengthen data quality controls, governance practices, and monitoring to improve trust in critical master data assets.<br>• Collaborate with cross-functional teams to connect master data with enterprise applications, reporting tools, and downstream data platforms.<br>• Support platform upgrades, stabilization efforts, and remediation activities that improve reliability and reduce technical debt.<br>• Analyze master data structures and profiling results to identify improvement opportunities and resolve data-related issues.<br>• Contribute to integration and pipeline support for master data movement across APIs, analytics environments, and business systems.
- 2026-11-11T00:00:00Z
- San Francisco, CA
- onsite
- Temporary / Contract
- 95 - 110 USD / Hourly
- We are looking for an Applied AI Training Engineer to join a Contract opportunity in San Francisco, California. This role focuses on shaping high-quality data and evaluation assets that strengthen how large language models learn specialized enterprise software concepts, workflows, and decision patterns. The ideal candidate will combine AI training expertise, strong technical judgment, and close collaboration with subject matter experts to improve model accuracy, consistency, and real-world usefulness across complex business scenarios.<br><br>Responsibilities:<br>• Develop structured training examples that help large language models learn enterprise software behaviors, terminology, and task flows with precision.<br>• Collaborate with subject matter experts to convert product knowledge, process logic, and business context into usable datasets for model training.<br>• Define data design approaches that expand domain coverage and support reliable model performance across a wide range of user scenarios.<br>• Build, organize, and enhance large-scale datasets, including generating synthetic examples when they add value to model learning.<br>• Review model responses, investigate failure patterns, and adjust training content to close knowledge gaps and improve output quality.<br>• Establish reusable frameworks, taxonomies, and teaching methods for introducing new concepts, schemas, and specialized domains to AI systems.<br>• Create benchmark datasets and evaluation methods to measure reasoning quality, factual accuracy, coverage, and generalization.<br>• Implement quality controls that detect inconsistency, ambiguity, imbalance, and missing information within training data collections.<br>• Write and maintain Python-based tools to create, transform, validate, and manage training data efficiently at scale.<br>• Refine model behavior to better align responses with customer expectations, domain expertise, and intended software functionality.
- 2026-11-10T00:00:00Z