Who We Are
Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact.
To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading-edge management consulting along with technology and design, corporate and digital ventures—and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive.
What You'll Do
Product & Stakeholder Partnership
Partner closely with product owners, functional leaders, and stakeholders within the People function to define requirements, shape backlog items, and translate business problems into technical solutions.
Work with global and local market teams during rollouts to understand adoption, identify gaps, and continuously improve the solution.
Partner with enterprise teams across architecture, security, Responsible AI etc. to seek approvals for the AI solutions during deployments and rollouts
Communicate clearly and effectively with both technical and non-technical stakeholders.
Ensure GenAI solutions are designed and delivered in accordance with Responsible AI, security, privacy, data governance, and regulatory requirements.
Establish appropriate AI guardrails covering areas such as prompt injection, data leakage, unauthorized tool access, unsafe outputs, and inappropriate model behaviour.
Partner with Responsible AI, Security, Privacy, Legal, Risk, and Enterprise Architecture teams to obtain necessary approvals and establish production-readiness standards.
Ensure appropriate documentation of AI system architecture, model usage, data flows, risks, evaluations, and operational controls.
Embed responsible AI and security considerations throughout the product lifecycle rather than treating them as post-development activities
GenAI Architecture & Technical Strategy
Define the technical vision, architecture, and engineering strategy for enterprise GenAI products.
Design and guide implementation of LLM-powered applications, RAG architectures, agentic workflows, LLM orchestration, tool/function calling, and AI-powered decision-support solutions.
Evaluate and select appropriate foundation models, embedding models, AI platforms, retrieval technologies, orchestration frameworks, and cloud services based on business and technical requirements.
Establish reusable GenAI architecture patterns, reference architectures, engineering standards, and technical accelerators across the AI CoE.
Make pragmatic build-vs-buy, model-selection, and platform decisions considering quality, scalability, security, latency, and cost.
Conduct architecture and design reviews and provide technical direction across multiple engineering teams and workstreams.
AI Evaluation & Quality
Define evaluation frameworks for GenAI applications covering accuracy, relevance, groundedness, hallucination, safety, robustness, latency, and cost.
Establish automated evaluation and regression-testing strategies for models, prompts, RAG pipelines, and agentic workflows.
Partner with Product and business stakeholders to define AI quality and product success metrics.
LLMOps / MLOps & Production Engineering
Establish production-grade LLMOps/MLOps practices covering model and prompt versioning, deployment, monitoring, observability, and continuous improvement.
Define operational metrics covering AI quality, latency, reliability, usage, and cost.
Establish CI/CD and automated testing practices for GenAI applications, prompts, RAG pipelines, and agentic…