AI Engineer

• Review and evaluate AI-generated code across programming languages and software engineering scenarios
• Assess code for correctness, reliability, security, scalability, readability, and maintainability
• Identify bugs, logical errors, incomplete implementations, edge-case failures, and architectural weaknesses
• Analyze unfamiliar codebases and understand the impact of proposed changes
• Review bug fixes, feature implementations, refactoring, API integrations, configuration changes, and database operations
• Compare alternative implementations and determine whether they satisfy technical requirements
• Rewrite or improve code to create high-quality reference solutions
• Provide clear technical explanations of identified issues and recommended improvements
• Develop evaluation criteria, technical annotations, and rubrics for code-quality assessment
• Collaborate with researchers and engineering teams to design coding benchmarks and improve LLM evaluation methodologies

Senior Software Engineer – AI Code Evaluation

• Own end-to-end program delivery across scope, timelines, quality, throughput, contributor performance, and cost.
• Design and manage workflows for coding datasets, agentic trajectories, RL environments, benchmarks, and rubric-based evaluations.
• Identify operational bottlenecks and improve workflows through better instructions, sequencing, incentives, review systems, and capacity planning.
• Define contributor requirements and partner with talent teams to source, assess, onboard, train, and ramp distributed software engineers.
• Build team-lead and reviewer structures for programs involving 100–1,000+ contributors.
• Own quality-control systems and analyze datasets to identify trends, systematic errors, and root causes.
• Act as a primary customer contact for AI labs, communicating progress, risks, quality trends, and recovery plans.
• Translate research objectives into practical task specifications and challenge requirements when they may not produce the intended evaluation signal.
• Use Python, SQL, or similar tools to automate quality sampling, defect analysis, throughput reporting, and operational reviews.
• Convert successful workflows into reusable playbooks, quality controls, evaluation assets, and contributor-management systems.
• Share operational learnings and mentor other program leads.

Technical Program Operations Lead – AI Engineering

• Create realistic, challenging coding tasks involving feature implementation and software bug fixes.
• Design tasks that reflect real-world backend engineering scenarios.
• Develop deterministic verifiers that accept reasonable valid solutions and reject incorrect outputs.
• Work with backend technologies such as Java, Node.js, Go, Rust, TypeScript, Python, C++, or similar languages.
• Evaluate code for correctness, reliability, maintainability, and performance.
• Incorporate automated testing and clear validation criteria into coding tasks.
• Identify and account for edge cases, performance bottlenecks, and potential implementation errors.
• Apply secure coding principles and cybersecurity considerations where relevant.
• Refine tasks and verification logic based on project requirements and quality standards.

Backend Software Engineer – AI Training Projects

• Own and develop the existing internal CRM across the Node.js/Express backend and React frontend
• Audit the codebase for gaps, bugs, technical debt, security risks, and incomplete functionality
• Create a plan to complete and stabilize the CRM
• Develop, test, and maintain lead management, communications, agent workflows, reporting, and administrative features
• Debug and resolve issues affecting live applications
• Maintain and improve AI functionality using OpenAI and Anthropic APIs
• Work within the agentic tool gateway, including tool permissions, policy controls, and safety restrictions
• Maintain real-time functionality using Redis, Socket.IO, and Twilio Voice
• Protect customer and agent data through authentication, authorization, validation, logging, and tenant isolation
• Manage deployments and infrastructure across Render, Cloudflare, AWS S3, MongoDB Atlas, GitHub, and GitHub Actions
• Maintain CI/CD and production deployment processes
• Work with the founder and operations manager to translate business requirements into technical solutions
• Build licensing and onboarding systems to replace the current GoHighLevel process
• Support additional internal systems, operational technology, and AI implementation projects
• Become the primary technical owner of the CRM and establish a stable release process and development roadmap

Senior Full Stack AI Engineer

• Design and develop AI-powered solutions for natural language, speech, images, documents, and structured data
• Build and improve systems for search, question answering, summarization, content generation, classification, extraction, automation, and intelligent assistants
• Work with large language, speech, image, OCR, and multimodal models
• Develop AI pipelines processing text, audio, images, scanned documents, PDFs, forms, and tables
• Evaluate AI models for quality, speed, cost, reliability, scalability, and business fit
• Deploy AI services into production and integrate them with web, mobile, backend, and internal systems
• Improve AI system performance through testing, monitoring, optimization, and continuous iteration
• Collaborate with product, engineering, design, and business teams to deliver practical AI features
• Mentor engineers, review technical decisions, and contribute to AI architecture and best practices
• Research, compare, and select suitable AI models and tools
• Build useful, reliable, scalable AI features ready for real users
• Help reduce errors, improve quality, and turn AI experiments into production products