Head of Engineering - AI (Product Development)

Role Overview: Head of Engineering – AI Safety Services

Location:

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Mission:

Drive the future of responsible AI innovation by leading the design, development, and delivery of cutting-edge AI safety services and platforms.

Key Responsibilities:

Team Leadership & Strategy:

• Lead and mentor a cross-functional team of AI engineers, platform engineers, and a product manager.
• Set clear goals, promote collaboration, and cultivate a culture of impact and rapid learning.
• Implement agile processes to ensure speed, security, and quality in development.

Customer-Centric Innovation:

• Partner closely with clients to understand their AI safety goals, challenges, and integration needs.
• Translate customer requirements into actionable roadmaps aligned with innovation cycles.

Platform Development & Delivery:

• Oversee the creation of tools for:
• Alignment assessment
• Adversarial testing
• Drift detection
• Interpretability analysis
• Make strategic build-vs-buy decisions to accelerate customer success.

Engineering Excellence:

• Implement and enforce best practices in secure coding, automation, monitoring, and infrastructure-as-code.
• Maintain high system reliability through SLAs/SLOs, rigorous testing, and operational dashboards.

Continuous Innovation:

• Stay updated on advancements in AI safety, model evaluation, and adversarial robustness.
• Pilot and integrate emerging techniques to improve AI deployment speed and safety.

Qualifications & Experience:

Must-Have:

• 5+ years in software engineering, including 2+ years in a leadership role
• Proven experience delivering AI/ML or data-intensive platforms
• Strong background in coaching and talent development
• Excellent communication and cross-functional collaboration skills

Technical Proficiency:

• Languages/Frameworks: Python, TensorFlow, PyTorch, JavaScript, HTML/CSS
• Tools: Docker, Kubernetes, REST APIs, SQL/NoSQL databases
• Cloud Platforms: AWS, GCP, or Azure
• Understanding of LLMs, prompt engineering, and adversarial testing

Nice to Have:

• Familiarity with LangChain, LangGraph
• Experience with distributed systems (e.g., Spark, Flink)
• Knowledge of AI regulatory frameworks (e.g., SOC 2, ISO 27001)

scaling it responsibly