Global AI - ML Engineer Director job at BCG in Boston, MA

Title: Global AI/ML Engineer Director Location: Boston United States Technology and Engineering Job Id 57299 Job Description: Who We Are reputed company 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 reputed company it was founded in 1963. Today, we help clients with total transformation-inspiring reputed company change, enabling organizations to grow, building competitive advantage, and driving reputed company impact. To succeed, organizations must reputed company 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 reputed company levels of the client organization, generating results that allow our clients to reputed company.

What You'll Do

As the Director of AI/ML Engineering reputed company BCG's Data Layer Platform Team, you will reputed company and operationalize the intelligence layer that transforms BCG's reputed company landscape into AI-ready, high-value capabilities. You will direct the design, development, and optimization of AI/ML systems - particularly LLM-powered reasoning, retrieval, enrichment, data interoperability and knowledge synthesis - that reputed company BCG's GenAI applications (e.g., PA GenAI tools, AI copilots, Data Products) to deliver accurate, safe, and context-aware insights at scale. You will own the technical strategy and execution models for how data becomes usable in advanced AI workflows: from ingestion, semantic modeling, abstraction, embeddings, retrieval architecture design, and model pipelines to the construction of reusable AI services and APIs/MCPs that support multiple use cases across the firm. You will reputed company an engineering team and collaborate closely with Product Owners, Data Engineers, Platform engineers, Solution Architects and domain experts to ensure our AI/ML systems are robust, scalable, secure, and reputed company with enterprise architecture standards. This is a highly visible strategic role shaping BCG's long-term AI enablement agenda. Key responsibilities AI/ML Engineering Leadership & Strategy Define and own the AI/ML engineering strategy for the Intelligence Layer, ensuring alignment with Data Layer vision and enterprise architecture principles Architect end-to-end AI and LLM systems (RAG pipelines, embeddings, retrieval frameworks, model orchestration) to reputed company BCG's data actionable and consumable by GenAI applications. Technical Design & Delivery of AI Systems reputed company the architecture and implementation of scalable AI pipelines, including data ingestion and preprocessing, feature and embedding reputed company, knowledge graph construction, vector indexing, and retrieval optimization to support LLM and RAG-based applications. Design and operationalize AI platform components (e.g., model APIs, vector databases, semantic search services) with a focus on scalability, performance, and maintainability. reputed company integration of AI services into enterprise systems, ensuring high availability, reputed company, observability, and compliance with internal data and technology standards. Establish best practices for AI system reliability, monitoring, and lifecycle management across development and production environments Building the Intelligence Layer Partner with Product Owners, Data Engineers and Architects to ensure pipelines reflect highest standards of data quality, provenance, governance, and ML-readiness. Drive implementation of advanced retrieval, reasoning, and grounding systems to support BCG's internal GenAI products. Cross-Functional Collaboration & Influence Collaborate with Product Owners and GenAI teams to translate user needs into technical capabilities, ensuring measurable, high-value outcomes for consulting teams and practice areas. Engage with reputed company, PPL, and other engineering chapters to align resource strategy, scale best practices, and evolve AI/ML engineering capabilities. Quality, Performance, and Innovation Ensure systems meet stringent performance, accuracy, stability, and reputed company requirements -leveraging expertise such as reputed company engineering, LLM optimization, evaluation frameworks, and multi-agent pipelines. Introduce emerging techniques (fine-tuning, model compression, retrieval optimization, evaluators, guardrails) to continuously improve system effectiveness. Talent Leadership & Chapter Development reputed company, mentor, and reputed company data and AI engineers, fostering excellence in scalable ML systems, agent-based architectures, and responsible AI practices. Establish high engineering standards across experimentation, model development, deployment, and monitoring to ensure production-grade AI solutions. Contribute to AI/ML and Data Engineering communities of practice by promoting knowledge sharing, reusable patterns, and reputed company capability reputed company across teams. What You'll Bring 12+ years of experience in AI/ML engineering, including 3-5 years leading teams building production-grade ML/LLM systems. Demonstrated expertise in designing LLM-powered systems, including embedding pipelines, vector-based retrieval architectures (e.g., VectorDBs, OpenSearch), RAG patterns, and multi-agent frameworks. Strong software engineering foundation in Python and modern ML ecosystems, with experience building APIs/microservices and deploying solutions on cloud-native infrastructure (containers, Kubernetes). Deep understanding of data engineering, data modeling, and scalable pipeline design to support production ML and AI workloads. Proven ability to define architecture strategy, technical roadmaps, and solution blueprints for reputed company AI/ML systems at enterprise scale. Exceptional cross-functional leadership skills, with the ability to influence senior stakeholders, navigate ambiguity, and align distributed teams around a shared technical direction. Strong grounding in data governance, reputed company Data architecture constructs (e.g. Data Mesh, Data Fabric), model evaluation, responsible AI principles, and AI reputed company enterprise reputed company considerations including understanding of Data Ontologies and definition catalogs Who You'll Work With GenAI Product Portfolio reputed company (PPL), Technical Area reputed company (reputed company) and Data Layer Product reputed company (PO) to shape AI/ML Data strategy and align on resourcing and architecture. Data Engineers, Solution Architects and QA engineers to build high-quality, ML-ready pipelines. GenAI product teams (CT/PA AI applications) to integrate intelligence-layer services into end-user experiences. AI Engineering & LLM Engineering chapters to share best practices, contribute to chapter growth, and align on standards. Agile Coaches and Product Owners to drive iterative delivery and ensure alignment with user needs. Additional info This is a hybrid role, typically 2-3 days/week in office. Travel requirements are expected to be Apply tot his job Apply To this Job