AI Engineering Lead (Agentic Development)

Experience and Skills

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.

Skills

AI Coding Assistants

AI Agent Frameworks

Software Engineering

Git

Shell Scripting

Command Line

macOS

Desktop Automation

Test Automation

AI Output Evaluation

Incident Diagnosis

Workflow Automation

Release Verification

automation

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.

Nice to Have

Concurrent Development Teams

Evidence-Driven Delivery

Agent Orchestration

Capacity Planning

Benefits

We provide the opportunity to participate in impactful and technically rigorous industrial data projects that drive innovation and professional growth. Our work environment emphasizes technical excellence, collaboration, and continuous innovation.

Niuro supports a 100% remote work model, allowing flexibility in work location globally. We invest in career development through ongoing training programs and leadership opportunities, ensuring continuous growth and success.

Upon successful completion of the initial contract, there is potential for long-term collaboration and stable, full-time employment, reflecting our long-term commitment to our team members.

Joining Niuro means becoming part of a global community dedicated to technological excellence and benefiting from a strong administrative support infrastructure that enables you to focus on impactful work without d