The AI Engineering Lead will coordinate several autonomous AI engineering teams while remaining accountable for accurate, usable software delivery. This is a hands-on technical leadership role focused on translating priorities into clear briefs, organizing parallel work, and maintaining strong engineering and operational controls.

The role combines software engineering judgment with automation management. You will configure AI coding tools, terminal sessions, and workflows; monitor progress; recover interrupted work; and ensure that code changes, tests, releases, and AI-generated output are properly reviewed and verified.

Success means delivering accepted engineering outcomes, not maximizing prompts or active sessions. Work must remain traceable through clear ownership, evidence-based status updates, meaningful testing, written handoffs, and appropriate escalation of material risks.

Key Responsibilities

- Translate business priorities into clear outcomes, written task briefs, scope boundaries, and measurable definitions of success.
- Coordinate parallel AI engineering workstreams, shared code, technical decisions, and dependencies.
- Configure AI coding tools, terminal sessions, and management automation while keeping objectives, progress, and handoffs visible.
- Monitor AI team managers, respond to questions, and recover interruptions without losing evidence or creating duplicate ownership.
- Inspect technical changes and tests, require appropriate review, and oversee safe source integration, releases, and real-world verification.
- Evaluate AI output through source review, meaningful tests, and quality checks rather than relying on automated summaries.
- Protect confidential information and access boundaries, and escalate decisions beyond the role's authority to the appropriate owner.
- Assess capacity across machines, review paths,



and model accounts, expanding activity based on measured demand and established limits.
- Investigate recurring failures and remove their underlying causes so operating methods remain simple as they scale.
- Maintain written intent, ownership, and handoffs so work remains recoverable when sessions fail or stall.

Requirements

- Lead-level experience, with at least 5 years in software engineering and technical leadership of concurrent development workstreams.
- Hands-on experience with several AI coding tools or agent frameworks.
- Strong ability to understand code changes, investigate defects, run meaningful tests, and evaluate AI-generated output.
- Experience using command-line tools, shell scripting, Git, and repeatable software development workflows.
- Experience building and troubleshooting automation for concurrent sessions or development processes.
- Experience with macOS automation, or equivalent desktop automation experience with the ability to learn macOS-based workflows.
- Ability to organize parallel workstreams, identify dependencies, assign clear ownership, and prevent duplicated work.
- Ability to write precise task instructions, concise progress summaries, evidence-based decisions, and recoverable handover notes.
- Ability to manage working-context limits, preserve unfinished work, respect permissions, and distinguish active processes from verified outcomes.
- Ability to assess system capacity, review paths, model account limits, and operational cost as team activity scales.
- Demonstrated discipline in identifying and removing the root causes of recurring failures.
- Hands-on experience with AI Coding Assistants, AI Agent Frameworks, Command Line, Test Automation, AI Output Evaluation, Incident Diagnosis, Workflow Automation, Release Verification.

Job Type: Full-time

Work Location: Remote

📌 AI Engineering Lead (Agentic Development) (México)
🏢 Niuro
📍 México