Chief AI Safety Architect

7 days ago

Bharatpur, Rajasthan, India beBeeInnovation Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Drive Responsible AI Innovation

The Head of Engineering – AI Safety Services role plays a critical part in creating guardrails for AI innovation. This includes setting the direction, leading the development and delivery of cutting-edge AI safety services and platforms.

Responsibilities include:

Key Responsibilities:
  • Leading a cross-functional team to design, develop, and deliver AI safety services and platforms.
  • Setting clear goals, promoting collaboration, and cultivating a culture of impact and rapid learning.
  • Implementing agile processes to ensure speed, security, and quality in development.

Customer-Centric Innovation:

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

Platform Development & Delivery:

  • Overseeing 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:

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

Qualifications & Experience:

Must-Have Qualifications:

  • 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 Qualifications:

  • 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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