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# AI Software Engineer

- **Company:** Spectraforce
- **Location:** Round Rock, TX, United States
- **Contract:** Temporary contract
- **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Automation of Tests, Static Program Analysis, Software Quality, Computer Programming, Continuous Integration, Cursor (Graphical User Interface Elements), Dynamic Program Analysis, Firmware, Python (Programming Language), Open Web Application Security, Software Architecture, Systems Development Life Cycle, Cloud Services, Secure Coding, Security Software, Software Construction, Software Deployment, Software Requirements Analysis, Software Systems, Systems Integration, Test Data, TypeScript, Enterprise Data Management, Enterprise Software Applications, GitHub Copilot, Large Language Models, Multi-Agent Systems, Software Security, Caching, Scalability Testing, Information Technology, Graphql, Machine Learning Operations, Api Design, Webhooks, Software Version Control, Devsecops, Vulnerability Analysis
- **Published:** August 26, 2026
- **Apply:** http://leoforce.us/Careers/Spectraforce/JobDetails.html?jobid=d552f2e9-3c18-432e-9bc3-004d0f938f74&OrgId=1&UserId=2586

## About the Role

* 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 Security Harness Engineering

## Description

* Designs, codes, tests, debugs and documents software according to client's systems quality standards, policies and procedures.
 * Analyzes business needs and creates software solutions.
 * Responsible for preparing design documentation. Prepares test data for unit, string and parallel testing.
 * Evaluates and recommends software and hardware solutions to meet user needs. Resolves customer issues with software solutions and responds to suggestions for improvements and enhancements.
 * Works with business and development teams to clarify requirements to ensure testability. Drafts, revises, and maintains test plans, test cases, and automated test scripts.
 * Executes test procedures according to software requirements specifications Logs defects and makes recommendations to address defects.
 * Retests software corrections to ensure problems are resolved. Documents evolution of testing procedures for future replication.
 * May conduct performance and scalability testing.

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


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