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
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
Education:
Bachelor's or master's degree in computer science or a related field, or equivalent practical Security Harness Engineering
Applicant Notices & Disclaimers
For information on benefits, equal opportunity employment, and location-specific applicant notices, click here
At SPECTRAFORCE, we are committed to maintaining a workplace that ensures fair compensation and wage transparency in adherence with all applicable state and local laws.This position's pay range is $75.00/hr - $80.00/hr.
