AI Safety Leader

17 hours ago

Delhi, Delhi, India beBeeInnovation Full time US$ 1,50,000 - US$ 2,50,000
Technical Product Manager Position

We are seeking an experienced Technical Product Manager to drive the future of responsible AI innovation. As a key member of our team, you will be responsible for 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 product managers.
    • Set clear goals, promote collaboration, and cultivate a culture of impact and rapid learning.
    • Implement agile processes to ensure speed, security, and quality in innovation.
  • 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, and 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 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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