Chief Architect of Responsible AI Systems

1 week ago

Mount Abu, Rajasthan, India beBeeInnovation Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Job Title

As AI accelerates, safety can't be an afterthought. The Head of Engineering – AI Safety Services plays a critical role in building the guardrails that let innovation move fast without breaking trust.

It's not just about scaling technology — it's about scaling it responsibly.

Key Responsibilities
  • Drive the future of responsible AI innovation by leading the design, development, and delivery of cutting-edge AI safety services and platforms.
  1. Lead and mentor a cross-functional team of AI engineers, platform engineers, and a product manager.
  2. Set clear goals, promote collaboration, and cultivate a culture of impact and rapid learning.
  3. Implement agile processes to ensure speed, security, and quality in development.
  1. Partner closely with clients to understand their AI safety goals, challenges, and integration needs.
  2. Translate customer requirements into actionable roadmaps aligned with innovation cycles.
  1. 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.
  1. Implement and enforce best practices in secure coding, automation, monitoring, and infrastructure-as-code.
  2. Maintain high system reliability through SLAs/SLOs, rigorous testing, and operational dashboards.
  1. Stay updated on advancements in AI safety, model evaluation, and adversarial robustness.
  2. Pilot and integrate emerging techniques to improve AI deployment speed and safety.
Requirements
  • 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 Skills
  • 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.
Bonus Points
  • 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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