Software Engineer Consultant

This consultant will serve as a hands-on technical reviewer, advisor, and development governance resource. The primary responsibility is not simply to write new code. Instead, this individual will review AI-generated or “vibe-coded” applications and identify security vulnerabilities, code-quality issues, testing deficiencies, integration risks, architectural weaknesses, and production-readiness concerns.

The consultant will also help establish practical guardrails for employees using AI-assisted development tools, providing the team with a stronger framework for building secure, maintainable, and production-ready software.

This is an excellent opportunity for an experienced software developer or technical consultant who understands both traditional engineering discipline and the increasingly fast-moving world of AI-assisted software development.

What You’ll Do

AI-Generated Application & Code Review

• Perform detailed reviews of existing applications developed using Lovable and AI-assisted/vibe-coding workflows.
• Analyze TypeScript and full-stack application code for defects, security vulnerabilities, maintainability concerns, and production-readiness risks.
• Identify issues that may not be apparent to less experienced developers relying heavily on AI-generated code.
• Review application structure, code organization, dependencies, authentication/authorization approaches, data handling, error handling, and other engineering considerations.
• Troubleshoot existing application behavior and recommend practical remediation strategies.
• Evaluate whether AI-generated implementations follow appropriate software engineering practices rather than accepting generated code at face value.

Security & Production Readiness

• Evaluate applications for potential security weaknesses before they are expanded beyond controlled internal use.
• Review application and API implementations for potential vulnerabilities, insecure configurations, permissions issues, data exposure risks, and other security concerns.
• Help establish technical criteria that applications should meet before being considered production ready.
• Review backend and database interactions, including environments utilizing Supabase.
• Assess dependencies and integrations with third-party systems and APIs.
• Recommend appropriate security, testing, code-review, and release practices as applications mature.
• Help the development team understand where AI-generated code requires additional human validation.

Development Governance & Guardrails

• Establish practical technical and security guardrails for AI-assisted development.
• Provide code-review standards and repeatable review practices the internal team can apply to future projects.
• Advise developers on what to evaluate when accepting, modifying, or deploying AI-generated code.
• Help the organization balance rapid AI-assisted development with sound engineering, security, and maintainability practices.
• Provide clear recommendations without unnecessarily slowing down experimentation or development velocity.
• Partner with relatively new or less experienced developers and help raise the team’s overall engineering discipline.

Testing & Validation

• Assist with application testing and validation, including creation or review of test scripts when appropriate.
• Identify gaps in functionality, exception handling, validation, integration behavior, and security testing.
• Review API integrations and data flows for reliability and potential failure points.
• Help establish appropriate testing expectations for applications produced through AI-assisted development.
• Validate applications as they progress from prototypes or internal tools toward more mature production applications.

Technical Advisory & Team Collaboration

• Function as a trusted technical advisor to the internal IT and development team.
• Conduct code reviews and provide actionable feedback to developers.
• Clearly communicate technical risks to stakeholders with varying levels of software-development experience.
• Explain why a particular piece of generated code or implementation creates risk and recommend a practical alternative.
• Help team members develop stronger instincts around code quality, security, maintainability, testing, and production readiness.
• Provide hands-on technical guidance rather than operating exclusively at a high-level architecture or strategy level., This is a fully remote, part-time consulting engagement requiring approximately 5-10 hours per week, with current approval for up to approximately 10 hours weekly.

Scheduling is expected to be highly flexible. A consultant could potentially contribute approximately a couple of hours per day toward the beginning or end of the workday, depending on mutual availability.

LHH is particularly interested in candidates who bring the following:

1. Strong Hands-On Software Development & Code Review Experience * Demonstrated professional software-development experience with significant responsibility for reviewing, troubleshooting, debugging, and improving application code. * Ability to independently examine an unfamiliar codebase and identify defects, security gaps, technical debt, poor development practices, and production risks. * Strong understanding of what separates functional prototype code from reliable, maintainable, production-ready software. * Experience conducting meaningful peer code reviews and providing specific, actionable recommendations. * Ability to remain hands-on with code. This is not strictly an enterprise architecture or management position.

2. TypeScript / Full-Stack Development Experience * Strong hands-on experience with TypeScript and modern full-stack web application development. * Experience troubleshooting front-end and back-end application behavior. * Understanding of application architecture, databases, authentication, APIs, integrations, and deployment considerations. * Ability to quickly navigate and evaluate an existing TypeScript-based application environment.

3. AI-Assisted Software Development Experience * Experience evaluating, developing, or governing applications created using modern AI-assisted coding platforms. * Direct Lovable experience is highly desirable. * Candidates without Lovable experience may be considered if they have meaningful hands-on experience with comparable AI development tools such as Cursor, GitHub Copilot, Claude Code, or similar platforms. * Understanding of the unique risks associated with AI-generated software, including technically plausible code that may contain hidden security, reliability, scalability, or maintainability issues. * Ability to establish practical development and security guardrails around AI-assisted application development.

Simply having used an AI coding assistant is not sufficient. The strongest candidates will be able to describe specific situations in which they reviewed AI-generated application code, discovered meaningful problems, and corrected or governed the resulting application.

Technical Environment

Experience with several of the following will be especially valuable:

• TypeScript
• Lovable
• Supabase
• GitHub
• Full-stack web application development
• REST APIs and third-party integrations
• Application security and secure coding practices
• Code review and source-control workflows
• Application testing and test scripting
• Authentication and authorization
• Database and backend application development
• AI-assisted development platforms
• AI-generated code review
• Application troubleshooting and debugging

Direct Lovable experience is preferred but not mandatory if the candidate has sufficiently relevant experience with other AI-assisted coding environments.

Preferred Qualifications

• Previous experience reviewing or improving AI-generated or vibe-coded production applications.
• Experience developing standards, policies, review processes, or technical guardrails for AI-assisted development.
• Experience with Lovable and Supabase.
• Strong knowledge of secure application-development practices.
• Experience reviewing API-heavy applications and complex third-party integrations.
• Familiarity with automated and manual application testing approaches.
• Experience moving prototypes or internally developed applications toward enterprise-grade production readiness.
• Architecture experience is helpful but not required.
• Construction, engineering, or general contracting industry experience is a plus but not required.

Technical competency and relevant software-development experience are substantially more important than prior industry experience.

The workload may vary during the engagement. The initial application and code review could require more concentrated effort, followed by a reduced ongoing advisory commitment. Hours may increase again as new applications, modules, or integrations are introduced.

Candidates located in Southern California who could occasionally meet with the team in person may be advantageous, but local residency and onsite work are not required.

Contractor Benefits:

o Medical, dental, and vision insurance

o 401(k) plan with employer match

o Paid holidays

o Paid vacation

o Paid sick leave

LHH Recruitment Solutions is seeking an experienced Consulting Software Developer / AI Application Code Review Consultant for a client that is expanding its use of AI-assisted software development to build internal business applications.

Our client is developing an internal application environment designed to consolidate and simplify workflows across multiple business functions. As adoption grows, some of these applications may eventually support external users as well.

The organization has successfully begun developing applications using Lovable and other modern AI-assisted development methods, but recognizes the need for deeper software engineering oversight before these applications are relied upon at scale or exposed externally.