Software Engineer (Web) - Future Contract Opportunities

Role overview

This is a proactive posting to build a network of contractors for anticipated future project needs. Engagements are project-based, with timing, scope, duration, and hours varying by assignment, and hourly rates typically fall in the $79–$120 range depending on the project and required expertise. The work blends full-stack engineering, client-facing consulting instincts, and the judgment to apply AI where it genuinely creates value.

Responsibilities

- Embed with client teams to discover, scope, and deliver full-stack web applications end to end, from ambiguous brief through production - Design, build, and deploy scalable web applications across the stack using modern front-end and back-end frameworks along with cloud platforms - Identify, prototype, and ship AI-enabled features such as LLM integration, retrieval-augmented generation, agentic workflows, and intelligent automation, with appropriate evaluation, guardrails, and cost or latency awareness - Use AI-assisted development tooling to accelerate delivery and raise team velocity without compromising code quality - Implement infrastructure-as-code and automated deployment pipelines so solutions are reliable, observable, and scalable - Maintain high-quality automated tests, including evaluation harnesses for AI features, to ensure robustness - Conduct thorough code reviews, advocate for best practices, and uphold engineering standards in fast-moving, client-facing environments - Provide technical leadership and mentorship, lifting AI and full-stack fluency across teams and clients - Manage delivery expectations directly with client stakeholders, balancing speed, quality, and scope in real time

Requirements

- Proven experience operating as a full-stack engineer who is comfortable in ambiguity, short feedback loops, and discovery-driven work - Proficiency with modern web stacks such as React, Next.js, and TypeScript, paired with contemporary back-end frameworks and cloud platforms - Hands-on experience integrating AI capabilities, including LLMs, RAG, and agentic workflows, into production systems with thoughtful evaluation and guardrails - Strong communication skills, with the ability to explain technical constraints and the capabilities or limits of AI to both technical and non-technical audiences - Track record of code review, mentorship, and maintaining high engineering standards under delivery pressure - Comfort with client-facing work, including discovery conversations and direct stakeholder management

Nice to have

- Experience taking an AI feature from prototype to production, including monitoring, evaluation, and iteration once real users are in the loop - Experience building and managing scaled frontend architectures such as microfrontends, monorepos, and shared internal libraries - Experience managing and evolving CI/CD pipelines and related DevOps tooling - Experience building authentication and protected applications - Familiarity with tools for monitoring, logging, and securing applications, including AI observability - Experience architecting complex software systems - Experience fine-tuning, distilling, or otherwise customizing models, with a point of view on when that is warranted versus prompting or retrieval