WHAT YOU'LL DOhe Generative AI Architect - Senior Manager plays a crucial role in our AI Center of Excellence (CoE), spearheading the design, deployment, and governance of generative AI solutions across the organization. This senior role demands a unique blend of technical expertise in AI, strategic vision, and hands-on experience with generative models, ensuring that AI initiatives drive business impact and align with organizational goals. The Generative AI Architect will work closely with diverse stakeholders—digital teams, enterprise architects, and governance bodies—to deliver scalable, ethical, and high-performance AI solutions that meet the highest standards across projects.Key Responsibilities:

• End-to-End Generative AI Architecture:
  Collaborate with digital teams, architects, and stakeholders to architect comprehensive AI solutions within the enterprise. Partner closely with teams, including Team Builder, Career Development (CD) Platform, and RevOps, to ensure seamless integration of AI solutions, maximizing their effectiveness across various business functions.
• Solution Architecture for Early-Stage Initiatives:
  Lead the architectural design for early-stage generative AI projects, guiding proof-of-concept (PoC) and prototype development with the AI CoE. Prepare these projects for review by the Investment Committee (IC) to secure funding.
• Cloud Engineering:
  Implement deployment strategies such as containerization, DevSecOps, CI/CD, performance monitoring, and logging using tools like Docker, Docker Compose, Kubernetes, and GitHub Actions.
• API Management and Deployment:
  Oversee REST and GraphQL API design, model serving, and endpoint creation with tools like Flask and FastAPI.
• Cloud-Based Model Deployment:
  Leverage cloud platforms like AWS (Lambda, S3, EC2, SageMaker) and Azure ML to facilitate scalable model deployment.
• AI/ML Lifecycle Management:
  Manage model development, experiment tracking, version control, and deployment using tools such as MLflow, DVC, and Weights & Biases.
• AI Governance and Risk Assessment:
  Actively engage with AI Governance frameworks and the Enterprise Architecture CoE to:
  
• Assess generative AI solutions across digital teams, identifying potential risks such as technical debt or overlapping initiatives.
• Evaluate generative AI proposals for IC review, ensuring alignment with organizational standards and assessing feasibility, stack compatibility, and build-vs-buy decisions.
• Responsible AI Implementation:
  Partner with the Generative AI Platforms team to ensure Responsible AI principles and standards are woven into LLM evaluations and applications, promoting ethical and secure AI deployment.
• Cross-Functional Collaboration:
  Serve as a subject matter expert on generative AI, guiding cross-functional teams, including digital, platform, and governance stakeholders. Promote knowledge-sharing, establish best practices, and contribute to a collaborative, AI-centric culture.
• Strategic Planning & Innovation:
  Develop and execute architectural strategies and roadmaps in alignment with the company’s vision. Stay updated on industry advancements to drive AI innovation and integrate cutting-edge practices.
• Security and Compliance:
  Ensure that AI solutions comply with security protocols and regulatory standards, implementing necessary safeguards to mitigate AI-related risks.
• Go-To-Market Strategy (GTM):
  Collaborate with onsite teams and senior architects to define go-to-market strategies for AI solutions, aligning development with client needs for impactful, effective implementations.

YOU BRING (EXPERIENCE & QUALIFICATIONS)Required Skills & Qualifications:

• Educational Background:
  Master’s or Ph.D. in Computer Science, Machine Learning, AI, Data Science, or a related discipline.
• Technical Expertise:
  Extensive experience in generative AI and machine learning frameworks, including models like GANs, VAEs, transformer-based architectures, and LLMs.
• Solution and Enterprise Architecture Experience:
  Proven track record in designing and deploying AI architectures at scale, with strong capabilities in risk assessment and alignment with enterprise standards.
• Governance and Standards Alignment:
  Experience in establishing or working within AI governance frameworks, focusing on risk mitigation, Responsible AI compliance, and adherence to organizational standards.
• Leadership and Communication Skills:
  Exceptional interpersonal, leadership, and communication abilities, with a demonstrated capacity to work across teams, lead cross-functional projects, and communicate complex technical concepts to non-technical stakeholders.

Preferred Qualifications:

• Cloud & MLOps Expertise:
  Proficiency in MLOps and AI lifecycle management, particularly for scalable deployments on platforms such as AWS, GCP, and Azure.
• Responsible AI Knowledge:
  In-depth understanding of Responsible AI practices, particularly in generative AI, and experience in designing and implementing these within enterprise frameworks.
• Thought Leadership:
  Contributions to AI and generative technologies through publications, presentations, or industry engagement are a strong advantage.
• Technical Proficiency:
  Hands-on experience with cloud-based AI/ML solutions and programming languages (e.G., Python, PySpark), data modeling, and microservices. Experience with LLM orchestration on platforms like OpenAI on Azure, AWS Bedrock, GCP Vertex AI, or Gemini AI, alongside familiarity with MLOps tools (MLFlow, batch prediction, real-time endpoints) and DevOps tools like Azure DevOps, GitHub Actions, Jenkins, Terraform, and AWS CloudFormation.

YOU'LL WORK WITHBCG’s information technology group collaboratively delivers the latest digital technologies that enable our consultants to lead and our business to grow. For our IT jobs, we seek individuals with expertise in the areas of IT infrastructure, application development, business systems, collaborative and social technologies, information security, and project leadership.