Senior Solution Analyst, Responsible AI – X Delivery

BCG BCG · Consulting · Bengaluru, Karnataka, India +1 · Technology and Engineering

This role focuses on developing and implementing testing and evaluation frameworks for Generative AI products within a Responsible AI context. The Senior Solution Analyst will work on scaling AI risk assessment, collaborating with product teams to mitigate risks, researching new threats and evaluation approaches, and training technical practitioners. The role involves a strong emphasis on ensuring AI systems are safe, secure, equitable, transparent, accountable, and trustworthy.

What you'd actually do

  1. Develop tools and techniques to scale and accelerate AI risk assessment and measurement across BCG and our clients
  2. Collaborate with product teams to influence quality and risk measurement and mitigations in AI/GenAI products through manual efforts and scalable, quantitative approaches
  3. Research new and emerging threats and measurement/evaluation approaches to ensure our approaches stay on the cutting-edge
  4. Work with small technical teams executing risk assessment and measurement on AI/GenAI products
  5. Train and mentor technical practitioners on measurements and evaluation approaches for GenAI products

Skills

Required

  • Design and analysis of experiments
  • Statistical modeling, including hierarchical linear models
  • GenAI, including prompt engineering and programmatically interacting with foundation models through APIs
  • Python and the open-source data science ecosystem
  • Version control with git
  • Ability to proactively identify ethical, social, and business risks posed by AI systems
  • Experience designing and analyzing experiments using advanced statistical methods
  • Experience and enthusiasm for working with Generative AI technologies
  • Broad conceptual understanding of ML and AI paradigms
  • Strong time management and organizational skills
  • Team player mindset
  • Strong written, verbal, and visual communication skills
  • Ability to explain sophisticated data science concepts to non-technical audiences

Nice to have

  • Familiarity with software engineering practices (e.g., unit testing, CI/CD)
  • Exposure to cloud platforms (AWS, Azure, GCP) or SQL databases
  • Knowledge of AI risk management frameworks (e.g., NIST AI RMF, ISO 42001)

What the JD emphasized

  • Responsible AI policy, principles, and standards
  • testing and evaluating GenAI products
  • AI risk assessment and measurement
  • measurement/evaluation approaches

Other signals

  • Responsible AI
  • testing and evaluation frameworks
  • AI risk assessment
  • GenAI products
  • safety testing
  • red teaming