Global IT Software Engineer Director & Chapter Lead- Gen AI/LLM

WHAT YOU'LL DO

To realize our aspirations to build a Gen AI assistant that will transform the way BCG works, we are looking for an LLM Engineering Director who is passionate about designing, developing, and optimizing GenAI products. You will work as a Squad Leader in your domain of expertise, helping to advance the work and using your experience to maximize Squad performance. You will also be committed to maintaining and developing your own expertise and knowledge to ensure that you and your Chapter members bring the latest thinking to your roles. You will bring expertise in full stack development, performance, and stability of custom-built products. This role is involved in all aspects of LLM based application including LLM expertise, data science/ML, backend development including API and core functional logic. Work would also involve documentation of all designs and development. It would be required to attend and lead any needed agile ceremonies and demo/present the development work incrementally.

Among your responsibilities, you will:

1. Continuously develop Chapter expertise
2. Develop Chapter members and the Chapter as a whole
3. Share knowledge and expertise within and outside of the Chapter
4. Identify resource needs throughout the organization
5. Work in a Squad to realize its mission
6. Enable the organization's new way of working

YOU'RE GOOD AT

• Being a great hands-on engineer and mentoring other team members.
• Inspiring and motivating your team.
• Comfortable with both planning and execution.
• Influencing and being a technical thought partner with Product Owners and other ITCLs.
• Committing to cross-functional collaboration to achieve the best results for the organization.
• Enjoying coaching and developing people to improve their performance, knowledge, and expertise.
• Being passionate, intellectually curious, and enjoying learning new skills and capabilities.
• Bringing a data-driven approach to decision-making and problem-solving, both in day-to-day management and in making strategic trade-offs.
• Capability to think and work at a systems level, combining data science and engineering skills.
• Delivering as an engineer on the features you own by yourself.

YOU BRING (EXPERIENCE & QUALIFICATIONS)

• BA degree in Computer Science, Statistics, or related field with a focus on Artificial Intelligence, Machine Learning, or Natural Language Processing.
• At least 10 years of working experience, ideally 2+ years of experience developing and experimenting with LLMs and 6+ years of experience developing AI/ML technologies within large and business-critical applications.

Experience & Skills (Mandatory)

• Proficiency in Python and all associated DS libraries and frameworks.
• Strong knowledge in AI, machine learning, and natural language processing.
• Experience with leveraging, training and fine-tuning Foundation Models, including multimodal inputs and outputs.
• Strong experience working with key LLM models APIs (e.g. OpenAI, Anthropic) and LLM Frameworks (e.g. LangChain, LlamaIndex).
• Experience with multi-agent frameworks/systems and an understanding of multi-agent systems and their applications in complex problem-solving scenarios.
• Experience with unstructured.io or similar libraries for handling various document formats and extracting structured information from unstructured data.
• Expertise in using LlamaIndex for building and querying knowledge bases, including its data connectors, indexing strategies, and query engines.
• Knowledge of effective text chunking techniques for optimal processing and indexing of large documents or datasets.
• Proficiency in generating and working with text embeddings using models like BERT, GPT, or domain-specific embedding models. Understanding of embedding spaces and their applications in semantic search and information retrieval.
• Experience in constructing and querying knowledge graphs, including technologies like Neo4j or RDF triplestores. Understanding of ontology design and graph-based reasoning.
• Experience with RAG concepts and fundamentals (vectorDBs, semantic search, etc.), expertise in implementing RAG systems that combine knowledge bases with generative AI models.

Experience & Skills (Nice to have)

• Experience with cloud infrastructure for AI/ML.
• Experience with LLM guardrails.
• Experience with LLM monitoring and observability.
• Experience with security related to LLM integration.

YOU'LL WORK WITH

• Your AI Engineering team, by setting their direction, establishing objectives and key results, working on the staffing and development of your chapter, and ensuring that you maximize outputs and working products.
• Tribe Leaders, Product Owners and other Tribe Chapter Leads with whom you shall work to manage chapter resources and ensure a positive collaboration.
• Agile Coaches and Scrum Masters, that will ensure that you adopt agile principles, mindset and ways of working into your daily routine and who will coach you during the transformation.
• Squad members of a specific squad, led by a Product Owner.