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KT
Kforce Technology Staffing
Principal AI DevSec Engineer
Career Insights for Artificial Intelligence Engineer (General)
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What they do
An Artificial Intelligence Engineer develops, tests, and deploys artificial intelligence models. May work closely with data software engineers and data professionals to train and implement AI models into existing systems or develop new applications.
$125,739 / year median in Texas
Job Description
RESPONSIBILITIES
Kforce is immediately seeking an experienced Principal AI DevSec Engineer in support of our enterprise compute customer based in Round Rock, TX.Responsibilities:
- Design, build, and deploy AI-powered capabilities across the SDLC, including: Spec Driven Development workflows that support the translation of well-formed specifications into secure, verifiable implementations; Assurance of AI-generated code
- guardrails, policy enforcement, and verification for code produced by AI assistants and agents; SDLC skills and agent tooling
- developer-assist skills as well as verification skills that perform automated security checks (design review, dependency and supply-chain analysis, static/dynamic analysis orchestration, release audit support)
- Integrate solutions with enterprise systems
- source control, CI/CD, ticketing, security scanning, identity, and internal platforms
- through APIs, webhooks, and protocols such as MCP (Model Context Protocol)
- Partner with engineering, security, product, and leadership stakeholders to define requirements, evaluate trade-offs, and support solution adoption
- Apply sound architecture and systems design practices: well-defined service boundaries, appropriate data models, secure defaults, observability, and extensibility
REQUIREMENTS
- Demonstrated experience developing and deploying AI-based solutions in production environments, with measurable business or operational impact
- Hands-on experience with modern AI/LLM development, including: Context engineering
- designing what informs the model's context window, including agentic retrieval and search, memory architectures, grounding in enterprise data, and structured outputs; Agentic system design
- agent loop engineering, multi-agent and sub-agent orchestration, and tool/function calling; Context window management and token budgeting, including cost and latency optimization for production workloads; Evaluation of AI system quality, reliability, and safety
- Experience developing and/or deploying applications with large-scale impact (broad user base, high transaction volume, or organization-wide adoption)
- Experience integrating with multiple systems and platforms (REST/GraphQL APIs, CI/CD pipelines, cloud services, enterprise tooling)
- Solid understanding of software architecture and systems design, including API design, event-driven patterns, and data modeling for scalability and extensibility
- Strong programming proficiency (e.g., Python, TypeScript/JavaScript, Go, or similar) and adherence to software engineering best practices, including testing, code quality, and maintainability
- Strong communication and collaboration skills, with the ability to convey technical concepts to both engineering and business audiences
- Demonstrated ability to work independently across the full delivery lifecycle
- requirements analysis, solution design, implementation, deployment, and stakeholder engagement
- with accountability for results
Preferred:
- Experience applying AI within a security domain
- application security, DevSecOps, code analysis, threat modeling, firmware security or software supply-chain security The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role.