Chief Architect of Responsible AI Systems

6 days ago

India beBeeInnovation Full time US$ 1,50,000 - US$ 2,00,000

As AI continues to evolve, responsible innovation is crucial. The Head of Engineering – AI Safety Services plays a vital role in building the necessary guardrails to ensure that technological advancements do not compromise trust.

This leadership position involves overseeing the design, development, and delivery of cutting-edge AI safety services and platforms. It requires driving innovation while maintaining security and quality.

The ideal candidate will have experience leading cross-functional teams, implementing agile processes, and promoting collaboration. They will also possess strong communication and problem-solving skills.

Key Responsibilities:

  • Team Leadership & Strategy:
    • Lead and mentor a team of AI engineers, platform engineers, and product managers.
    • Set clear goals and promote 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 needs and challenges.
    • Translate client 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, and make strategic build-vs-buy decisions to accelerate customer success.
  • Engineering Excellence:
    • Implement 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:

  • 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)

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