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Talent Software Services
Talent Software Services

78 Talent Software Services Research Jobs Hiring Near You

Talent Software Services

Developer III

Columbia, SC · On-site

... research, attend meetings, and review documents. 20% Maintain and modify programs according to specifications Code, compile, and implement application software that is delivered on time and within ...

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Network Engineer

Apex, NC · On-site

$60 - $65/hr

... hardware, software, and services Investigates and resolves problems, inefficiencies, and ... Performs research, operation studies, design reviews, and technical briefings with clients

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What makes Talent Software Services an attractive place to work?

Talent Software Services is a reputable company in the software industry, known for its commitment to delivering innovative solutions to clients. The company's workplace is characterized by a collaborative environment that fosters creativity, open communication, and a culture of continuous learning, allowing employees to grow professionally and personally. By joining Talent Software Services, individuals can contribute to the development of cutting-edge software products and services, gain valuable experience, and advance their careers in a dynamic and supportive work environment.

What are the most popular job types at Talent Software Services?

    What are the most popular jobs at Talent Software Services?

    What are the most popular categories at Talent Software Services?

    Infographic showing various Research job openings at Talent Software Services in the United States as of August 2026, with employment types broken down into 5% Full Time, 1% Part Time, and 94% Contract. Highlights an 79% Physical, 8% Hybrid, and 13% Remote job distribution.

    Principal Software Engineer - IT

    Talent Software Services

    Round Rock, TX • On-site

    $125K - $168K/yr

    Contractor

    Posted 5 days ago

    Job description

    Job Title: Principal Software Engineer(AI Software Engineer / AI Agent Engineer)
    Location: Round Rock, TX (Onsite)
    Duration:12 Month on W2 Contract
    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

    Required Skills and Qualifications
    • Demonstrated experience developing and deploying AI-based solutions in production environments, with measurable business or operational impact
    • Strong programming proficiency (e.g., Python, TypeScript/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

    Preferred Skills and Qualifications
    • Experience applying AI within a security domain - application security, DevSecOps, 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, GitHub Copilot, Cursor, Devin)
    • Experience with AI evaluation frameworks, guardrails, prompt/response caching strategies, and LLMOps in production
    • Bachelor's or master's degree in computer science or a related field, or equivalent practical

    Apply