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What You'll Do
About the Role
The Global IT - Director & Chapter Lead is a hands-on senior engineer and technical leader responsible for designing, building, and owning enterprise-grade Generative AI applications on AWS. This role carries a significant leadership mandate - managing and aligning multiple cross-functional Agile squads simultaneously, each working on distinct but interdependent workstreams. This layer of organizational complexity demands a leader who can hold both the technical and human dimensions of delivery with equal fluency.
As a member of a cross-functional Agile squad, this individual works closely with Product Owners, Architects, the squads, and business stakeholders to deliver scalable, secure, production-ready solutions. The expectation goes well beyond execution - this role drives organizational change, shapes functional practices, influences senior leadership, develops team capability, and operates with the highest level of integrity.
The role leads technical design and implementation leveraging Python, AWS-native services, RAG, vector search, and LLMs via AWS Bedrock and OpenAI. Experience with Sitecore Content Hub is a strong advantage, as GenAI will increasingly be applied to enterprise content and digital asset ecosystems.
Key responsibilities
1. Technical Leadership & Architecture
- Act as the technical lead for GenAI application development, owning architecture, design decisions, and implementation end-to-end proactively identify and frame highly complex challenges, address root causes, and drive systemic resolution.
- Proactively expand and contribute to BCG's technical and function-specific GenAI knowledge learn, adapt, and leverage emerging digital tools promote a culture of digital curiosity across the squad.
- Develop, apply, and share relevant policies and best practices that shape GenAI functional practices to drive business outcomes and mitigate delivery and compliance risk.
- Set technical standards, conduct rigorous design and code reviews, mentor engineers, and drive continuous improvement in cloud-native patterns and production readiness.
- Embrace and drive change by demonstrating adaptability and agility work creatively and consistently to evolve ways of working.
- Own and align the technical direction across multiple Agile squads working on concurrent, interdependent GenAI workstreams ensure architectural coherence and consistent engineering standards are maintained across all squads.
- Navigate and resolve cross-squad dependencies, technical conflicts, and competing priorities act as the primary escalation point for complex engineering decisions that span team boundaries.
- Champion Responsible AI principles, ensuring fairness, transparency, and accountability are embedded in all AI-driven solutions.
2. Solution Design & Delivery
- Collaborate with Product Owners, architects, designers, and stakeholders to translate complex and ambiguous business requirements into scalable GenAI solutions anticipate and manage changing priorities.
- Design and implement end-to-end GenAI pipelines: document ingestion, embedding generation, vector storage, retrieval, and conversational interfaces.
- Build and maintain event-driven ingestion pipelines where content pushed to Amazon S3 triggers workflows for document parsing, chunking, embedding, and indexing.
- Implement and optimize RAG architectures on AWS Bedrock using OpenAI LLMs and OpenSearch vector databases design and tune prompt engineering, embedding models, chunking approaches, and vector search relevance.
- Develop GenAI services, agents, and APIs in Python following clean code principles, modular design, and testable patterns.
- Architect and manage AWS infrastructure: S3, Lambda, Step Functions, Bedrock, OpenSearch, IAM, and CloudWatch.
- Drive and deliver complex, high-quality outputs mindful of broad business impact manage resources and expectations effectively set and meet milestones for NFRs (scalability, performance, reliability, cost).
- Proactively identify technical challenges and risks develop and execute mitigation plans contribute thought leadership to the GenAI roadmap.
- Manage delivery complexity across squads: coordinate release cadences, balance shared infrastructure, resolve inter-squad blockers, and maintain visibility of end-to-end progress for senior stakeholders.
- Operate effectively in conditions of high ambiguity - where requirements are incomplete, priorities shift across teams, and technical decisions carry broad downstream impact make confident, well-reasoned calls without waiting for perfect information.
3. Communication, Presence & Stakeholder Influence
- Modulate communication to audience and context - from deep technical discussions with engineers to executive narratives for senior leadership frame complex, ambiguous GenAI topics with appropriate detail and technicality.
- Drive conclusions based on data and expertise develop compelling narratives to influence stakeholders and reach resolution on architectural and product decisions.
- Lead conversations and meetings effectively encourage open dialogue actively listen and shape perspectives and outcomes across business and technical forums.
- Promote effective usage and collaboration through digital communication and knowledge-sharing tools.
- Create and maintain technical documentation including architecture diagrams, runbooks, and operational guides as authoritative shared references.
4. Teaming & Collaboration
- Work positively and collaboratively with stakeholders build and develop strong relationships partner effectively with diverse teams and broad networks seek to help and develop others.
- Balance individual, team, and network responsibilities manage expectations across Agile delivery cycles.
- Demonstrate adaptability and consideration of impact on others actively embrace new opportunities.
- Identify, manage, and mitigate conflict appropriately coach others to resolve conflicts constructively.
5. People Development & Leadership
- Generate interest and engagement across the squad bring out the best in team members by coaching effectively and creating meaningful development opportunities.
- Collect and provide frequent developmental feedback actively support team learning drive the performance management process throughout the year including goal setting, check-ins, and reviews.
- Strike an appropriate balance between team empowerment and managerial direction lead quality team meetings with clear objectives, deliverables, and team norms.
- Manage people across multiple squads: maintain awareness of individual performance, development needs, and team health simultaneously scale coaching and feedback practices across a broader set of engineers and leads.
- Foster a shared culture and ways of working across squads ensure consistency in values, engineering standards, and team norms even as squads operate independently.
6. Observability, Governance & Responsible AI
- Build and maintain QuickSight dashboards integrate tools such as Arize AI and PromptFoo to measure LLM accuracy, retrieval quality, latency, and system performance.
- Apply security, privacy, and compliance best practices including data protection, access control, and responsible AI handle confidential data responsibly and take appropriate security precautions.
- Perform this role with the highest level of integrity, generating trust and protecting organizational and client interests treat all others with respect regardless of background, position, or performance.
- Demonstrate a growth mindset proactively seek and act on feedback for self-development display perseverance and tenacity in the face of obstacles.
What You'll Bring
Core Technical Experience
- 10-12 years of professional software engineering experience building enterprise-grade applications.
- Strong experience in GenAI / ML / NLP, including production deployment of LLM-based systems.
- Strong experience with Python for backend and GenAI application development.
- Proven experience designing and implementing RAG systems: prompt engineering, embedding generation, chunking strategies, and vector search relevance tuning.
- Production experience with AWS Bedrock, OpenAI LLMs, and similar LLM platforms.
- Strong experience with AWS cloud services: S3, Lambda, Step Functions, OpenSearch, IAM, monitoring, and logging tools.
- Hands-on experience with vector databases and search technologies, particularly OpenSearch.
- Experience designing event-driven and serverless architectures.
- Familiarity with LLM evaluation and observability: metrics for accuracy, hallucination, latency, and cost.
- Experience building dashboards and analytics using Amazon QuickSight or similar tools.
- Strong understanding of RESTful APIs, microservices, and cloud-native integration patterns.
- Experience working in Agile/Scrum environments with cross-functional teams.
- Demonstrate ability to identify and frame highly complex, ambiguous challenges address root causes drive systemic change - not just deliver to specification.
- Track record of driving organizational change and evolving ways of working embraces and promotes adaptability.
- Ability to develop compelling technical narratives for senior leadership and influence decisions at the executive level.
- Experience shaping functional practices and contributing to policies that drive business outcomes and mitigate risk.
- Proven record of people development: coaching, performance management, and building team capability over time.
- Ability to manage competing priorities across workstreams while maintaining delivery quality and stakeholder trust.
- Demonstrated experience managing multiple teams or squads simultaneously, navigating organizational complexity, cross-team dependencies, and large-scale delivery programs.
- Comfortable operating in high-ambiguity environments where scope is incomplete and decisions carry broad impact across multiple teams and stakeholders.
- Creates a positive and inclusive working environment that values diverse perspectives.
Additional info
Good to have:
- Experience with or willingness to learn Sitecore Content Hub, DAM systems, or enterprise content platforms.
- Prior experience applying GenAI to content, document management, or digital asset workflows.
- Familiarity with GenAI evaluation tools such as Arize AI, PromptFoo, or similar frameworks.
- Experience with CI/CD pipelines, infrastructure as code, and DevOps best practices.
- Knowledge of data privacy, governance, and responsible AI frameworks.
- Experience with containerization (Docker) and orchestration concepts.
- Exposure to frontend frameworks or conversational UI development.
- Bachelor's degree in computer science, Engineering, or a related field (or equivalent practical experience).
Boston Consulting Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity / expression, national origin, disability, protected veteran status, or any other characteristic protected under national, provincial, or local law, where applicable, and those with criminal histories will be considered in a manner consistent with applicable state and local laws.
BCG is an E - Verify Employer. for more information on E-Verify.
