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AI Engineer

Job in Round Rock, Williamson County, Texas, 78682, USA
Listing for: Rose International
Full Time, Seasonal/Temporary position
Listed on 2026-09-09
Job specializations:
  • Software Development
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 96000 - 120000 USD Yearly USD 96000.00 120000.00 YEAR
Job Description & How to Apply Below

Date Posted: 08/26/2026

Hiring Organization:
Rose International

Position Number: 506326

Industry: IT Company

Job Title:

AI Engineer

Job Location:

Round Rock, TX, USA, 78681

Work Model:
Onsite

Shift: Standard working hours

Employment Type:

Temporary

FT/PT:
Full-Time

Estimated Duration (In months): 13

Min Hourly Rate($): 70.00

Max Hourly Rate($): 87.00

Must Have Skills/Attributes: AI, JavaScript, Python, REST, SDLC, Security, Typescript

Experience Desired:
Software engineering experience (8+ yrs);
Hands-on experience with modern AI/LLM development (4+ yrs);
Strong programming proficiency (e.g., Python, Type Script/JavaScript, Go, or similar) (8 yrs);
Security Harness Engineering (3+ yrs)

Preferred Education:

Bachelor’s Degree

C2C is not available

Job Description

Only qualified AI Engineer candidates located near Round Rock, TX are to be considered due to the position requiring an onsite presence

Required Education
  • Bachelor's in computer science or a related field, or equivalent practical.
Preferred Education
  • Master's degree in computer science or a related field
Required Skills, Experience & Abilities
  • Senior level Software Engineer with 8+ years' experience.
  • Must have enterprise scalability experience with previous well-known company.
  • Must have security experience, specifically security harness engineering experience.
  • Must have enterprise scalability, Security Harness Engineering, and hands‑on AI software engineering experience.
  • Demonstrated experience developing and deploying AI-based solutions in production environments, with measurable business or operational impact
  • Strong programming proficiency (e.g., Python, Type Script/JavaScript, Go, or similar) and adherence to software engineering best practices, including testing, code quality, and maintainability
  • 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
  • Solid understanding of software architecture and systems design, including API design, event‑driven patterns, and data modeling for scalability and extensibility
  • 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)
  • Demonstrated ability to work independently across the full delivery lifecycle - requirements analysis, solution design, implementation, deployment, and stakeholder engagement - with accountability for results
  • Strong communication and collaboration skills, with the ability to convey technical concepts to both engineering and business audiences
  • Working knowledge of secure development practices and experience designing solutions that meet enterprise security and compliance requirements
Desired Skills, Experience & Abilities
  • Experience applying AI within a security domain - application security, Dev Sec Ops , code analysis, threat modeling, firmware security or software supply‑chain security
  • Familiarity with secure‑by-design / secure‑by‑default principles and relevant frameworks (e.g., OWASP, including the OWASP Top 10 for LLM Applications; NIST SSDF)
  • Experience with MCP (Model Context Protocol), building agent skills and tools, or extending AI coding assistants (e.g., Claude Code, Git Hub Copilot, Cursor, Devin)
  • Experience with AI evaluation frameworks, guardrails, prompt/response caching strategies, and LLMOps in production
Role

Principal-level AI software engineer who builds production-ready AI solutions that make the software development lifecycle more secure and automated.

Responsibilities
  • Design, build, and deploy AI-powered capabilities across the SDLC, including:
  • Spec Driven Development workflows that support the translation…
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