Chief AI Safety Architect

3 days ago

Nagpur, Maharashtra, India beBeeInnovation Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
AI Safety Engineer Leader

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

As AI accelerates, safety can't be an afterthought. The AI Safety Engineer Leader 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:
  • 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, and 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).

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