Global IT Software Engineer Senior Manager - Gen AI/ LLM

WHAT YOU'LL DO We are seeking a highly skilled and experienced full-stack Software Engineer Expert Senior Manager with Gen AI /LLM expertise to join our Gen AI platform team. This role focuses on building and maintaining cloud-native platforms specifically designed for Generative AI and Large Language Model (LLM) development. The ideal candidate will have a strong background in reusable software components, frameworks, microservices and APIs, cloud infrastructure, and DevOps/MLOps/LLMOps, with a passion for creating scalable, reliable, and efficient systems. YOU'RE GOOD AT Being a great hands-on engineer passionate of building platform capabilities. Performing successfully in a fast-paced, multi-cultural and service-oriented environment Verbal and written communication at a business and technical level High level of initiative, self-motivation, resourcefulness, and collaboration Are passionate, intellectually curious, and enjoy learning new skills and capabilities. Building relationships and reliable team player, displaying consideration and respect for others Interpreting rules and guidelines flexibly to enhance the business and aligning with BCG’s values and culture Exhibiting ownership and accountability for the squad deliverables Servicing customer teams / platform users with a strong customer centricity Attention to detail, well organized, able to set priorities and take decisions Being flexible to be available outside of normal business hours for international calls as needed YOU BRING (EXPERIENCE & QUALIFICATIONS) Bachelor’s degree in computer science engineering (or equivalent degree or experience) Proven Experience in Gen AI, Artificial Intelligence, Machine Learning, or Natural Language Processing 12 years of relevant experience in delivering platform or complex technology solutions with strong technical background, preferably in global organization/ enterprise. 2 years’ experience in experimenting and developing with LLM. 1 years of experience developing with LLMs for production use case. 8years of experience in leading Enterprise scale software engineering/ platform engineering teams. Passionate expert in Modern Engineering, DevOps practices - Strong understanding of CI/CD, AI/ ML pipelines and automation tools. Experience & Skills (Mandatory) Strong knowledge and experience in Generative AI/ LLM based development. Strong knowledge and experience in building conversational agent-based UX. Strong experience working with key LLM models APIs (e.g. AWS Bedrock, Azure Open AI/ OpenAI) and LLM Frameworks (e.g. LangChain, LlamaIndex) Experience with multi-agent frameworks and an understanding of multi-agent systems and their applications in complex, multi-step problem-solving scenarios. Expertise in building enterprise grade, secure data ingestion pipelines for unstructured data – including indexing, search, and advance retrieval patterns. Proficiency in generating and working with text embeddings with understanding of embedding spaces and their applications in semantic search and information retrieval. Knowledge and Experience in building knowledge graphs in production. Experience with RAG concepts and fundamentals (VectorDBs, AWS OpenSearch, semantic search, etc.), Expertise in implementing RAG systems that combine knowledge bases with Generative AI models. Proficiency in Python, TypeScript, NodeJS, ReactJS (and equivalent) and all associated GenAI libraries and frameworks. Experience with containerization and orchestration technologies (Kubernetes, Docker). Experience & Skills (Nice to have) Experience with LLM guardrails Experience with security related to LLM integration Experience in LLM Testing and Evaluation LLM Security YOU'LL WORK WITH Your Gen AI Platform Engineering chapter in Cloud and Platform Engineering Portfolio Product Owners, Chapter Leads and other squad members. Agile Coaches and Scrum Leads, 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. J-18808-Ljbffr