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

• 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

• Build, modify, and maintain multi-step lead-capture flows and web experiences
• Develop backend functionality using PHP and MySQL
• Integrate and troubleshoot third-party APIs
• Create and maintain logging, reporting, and analytics solutions
• Improve conversion performance through iteration and optimization
• Write maintainable, reusable, and production-safe code
• Work within existing systems and improve legacy implementations where needed
• Collaborate asynchronously with the engineering team and communicate progress clearly
• Independently ship production-ready flow updates
• Use AI coding tools effectively while maintaining code quality
• Build reliable logging and reporting solutions
• Deliver clean API integrations with proper error handling
• Communicate proactively and require minimal oversight

AI Engineer jobs in Nigeria

Senior Software Engineer – AI Code Evaluation

Technical Program Operations Lead – AI Engineering

Senior Full Stack AI Engineer

Senior PHP Backend Developer, AI-Assisted Development