Principal - Responsible AI Solution Architect

AIToolboard

United States

On-site

USD 140,000 - 200,000

Full time

14 days+
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Job summary

Slalom Washington, US is seeking an AI Governance Strategist & Solution Architect to join its AI team as a Responsible AI Strategist or Technical Solution Architect. You will guide clients in complex AI/ML strategies with governance, oversight, and regulatory alignment in a dynamic, multidisciplinary setting.

The role emphasizes collaboration with risk partners, senior executives, and delivery teams to deploy compliant AI solutions and advance responsible AI practices.

Qualifications

  • Advanced degree such as an MA or PhD degree in a qualitative or quantitative social science, ethics or philosophy, law, or policy or a technical background in large-scale computing, modeling, data science; or related field.
  • At least 2 years of work experience on issues pertaining to artificial intelligence, machine learning, generative AI, and responsible AI.
  • Experience in Healthcare, Life Sciences, Banking or any highly regulated industry or sector.
  • Expertise in privacy, security, cyber, data analytics, risk management, research, accessibility, FinOps, risk modeling, environmental and carbon footprint modeling, software development/coding, or product development.
  • Knowledge and experience operationalizing responsible AI topics such as evaluation and testing and control integration for AI systems. Expertise in socio-technical aspects of AI (e.g., equity and fairness, RAI red teaming, performance, et

Responsibilities

  • Develop, implement, and integrate strategies, frameworks and guidelines for responsible AI and AI Governance.
  • Conduct thorough assessments of AI systems to identify impacts and mitigate potential risks, limitations, biases and ethical concerns.
  • Setting up robust policies, controls, standards, and risk frameworks in collaboration with clients and their risk partners to oversee and ensure AI initiatives agree with organizational values, regulatory requirements, and controls.
  • Lead initiatives to enhance transparency and explainability of AI systems, making them more understandable and trustworthy for users.
  • Select appropriate technologies from a pool of open-source and commercial offerings, considering deployment models and integration with existing tools.
  • Understand and contribute to MLOps, LLMOps, AgentOps, and AI transformations to SDLC to deploy and manage machine learning models and large language models and AI systems
  • Enable the engineering of AI platforms and architecture with embedded controls, capability, and tooling for security, compliance, and auditability.
  • Provide training and support to team members on responsible AI principles and practices.
  • Represent Slalom and support the development of thought leadership by engaging with external stakeholders, including industry groups, academic institutions, and regulatory bodies.
  • Foster partnerships with third-party vendors, delivery partners, contractors, industry groups, and institutions to ensure client and organizational needs are consistently met.
  • Advocate for the importance of Responsible AI and Trust and Safety through speaking engagements, publications, and participation at industry events.
  • Lead client engagements as a Subject Matter Expert in AI Risk Management and Ethics to solve customer problems and translate requirements into actionable solutions
  • Work within existing technology platforms and business operations to design effective record-keeping, human oversight, observability layers, integrated control architecture and systems of record for robust auditability
  • Remains up-to-date on the emerging frameworks, standards, policies, technical approaches, AI landscape and related issues by participating in workshops, reading academic research and professional publications, maintaining personal networks, and participating in relevant events.

Skills

AI governance
Responsible AI
Risk management
MLOps
Privacy
Security
Data analytics

Education

MA/PhD in relevant field

Job description

Slalom Washington, US

Full-time

About the Role

Role: AI Governance Strategist & Solution Architect: PrincipalJoin Slalom's AI team as a Responsible AI Strategist or Responsible AI Technical Solution Architect.If you are passionate about sociotechnical approaches to technology enablement and possess strong critical thinking skills, and risk management experience, this is the role for you. We are looking to build a cohort and a practice and seek passionate colleagues, collaborators, and team mates.As a Responsible AI technical consultant and architect, you will guide clients and deliver complex AI/ML strategies and solutions, with a focus on alignment with governance, oversight, and regulatory expectations. Ideal for those with a strong blend of technical, policy, risk management and business acumen, you\'ll leverage advanced AI technologies to create impactful solutions and help articulate their benefits to senior executives and delivery and sales teams in a dynamic, multidisciplinary environment.Position Overview:You will play a critical role in ensuring that AI technologies meet emerging regulatory expectations and realize multi-stakeholder value. This role requires close collaboration with various teams and partners to help customers efficiently and securely adopt AI technologies in a compliant and trustworthy manner.Given the complexities across the AI value chain, we welcome submissions from interested candidates across the diversity of sociotechnical interests and expertise, and can work with you to support your career growth through practical applications, team/project-based work and engagement with our leaders and industry experts.

Key Responsibilities
  • Develop, implement, and integrate strategies, frameworks and guidelines for responsible AI and AI Governance.
  • Conduct thorough assessments of AI systems to identify impacts and mitigate potential risks, limitations, biases and ethical concerns.
  • Setting up robust policies, controls, standards, and risk frameworks in collaboration with clients and their risk partners to oversee and ensure AI initiatives agree with organizational values, regulatory requirements, and controls.
  • Lead initiatives to enhance transparency and explainability of AI systems, making them more understandable and trustworthy for users.
  • Select appropriate technologies from a pool of open-source and commercial offerings, considering deployment models and integration with existing tools.
  • Understand and contribute to MLOps, LLMOps, AgentOps, and AI transformations to SDLC to deploy and manage machine learning models and large language models and AI systems
  • Enable the engineering of AI platforms and architecture with embedded controls, capability, and tooling for security, compliance, and auditability.
  • Provide training and support to team members on responsible AI principles and practices.
  • Represent Slalom and support the development of thought leadership by engaging with external stakeholders, including industry groups, academic institutions, and regulatory bodies.
  • Foster partnerships with third-party vendors, delivery partners, contractors, industry groups, and institutions to ensure client and organizational needs are consistently met.
  • Advocate for the importance of Responsible AI and Trust and Safety through speaking engagements, publications, and participation at industry events.
  • Lead client engagements as a Subject Matter Expert in AI Risk Management and Ethics to solve customer problems and translate requirements into actionable solutions
  • Work within existing technology platforms and business operations to design effective record-keeping, human oversight, observability layers, integrated control architecture and systems of record for robust auditability
  • Remains up-to-date on the emerging frameworks, standards, policies, technical approaches, AI landscape and related issues by participating in workshops, reading academic research and professional publications, maintaining personal networks, and participating in relevant events.
Qualifications
  • Advanced degree such as an MA or PhD degree in a qualitative or quantitative social science, ethics or philosophy, law, or policy or a technical background in large-scale computing, modeling, data science; or related field.
  • At least 2 years of work experience on issues pertaining to artificial intelligence, machine learning, generative AI, and responsible AI. Experience with generative AI is required.
  • Experience in Healthcare, Life Sciences, Banking or any highly regulated industry or sector.
  • Expertise in privacy, security, cyber, data analytics, risk management, research, accessibility, FinOps, risk modeling, environmental and carbon footprint modeling, software development/coding, or product development.
  • Knowledge and experience operationalizing responsible AI topics such as evaluation and testing and control integration for AI systems. Expertise in socio-technical aspects of AI (e.g., equity and fairness, RAI red teaming, performance, et
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