Xebia | Director

IT Platform Engineer Director & Chapter Lead- Gen AI/ LLM
Role - Gen AI/LLM
Location - Any Xebia Location (3days/ week WFO)
Exp - 14+ Years of exp
JOB DESCRIPTION
HTML, CSS, and Java-script
2+ years experience using TypeScript
Experience with React-Js, including modern features like Hooks and Contexts
Experience writing both object-oriented and functional JS/TS
Experience writing tests in Jest or similar testing framework
Experience building beautiful and high-performance websites
Experience using and building sites backed by NodeJS
Experience with Docker
Experience with NextJS
Familiar with concepts such as server-side rendering, lazy loading and state hydration
Experience using build tools like Webpack
Experience using the NodeJS package managers npm and/or yarn
Experience using git, branching and ability to solve merge conflicts when merging or rebasing
Bonus points for experience with Contentful.
YOU BRING (EXPERIENCE & QUALIFICATIONS)
Master’s or bachelor’s degree in engineering
Proven Experience in Gen AI, Artificial Intelligence, Machine Learning, or Natural Language Processing
14+ 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.
8+years 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 experience working with key LLM models APIs (e.g. AWS Bedrock, Azure Open AI/ OpenAI) and LLM Frameworks (e.g. LangChain, LlamaIndex).
Experience with cloud infrastructure for AI/Generative AI/ML on AWS, Azure.
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.
Knowledge of effective text chunking techniques for optimal processing and indexing of large documents or datasets.
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 (Vector DBs, AWS OpenSearch, semantic search, etc.), Expertise in implementing RAG systems that combine knowledge bases with Generative AI models.
Knowledge of training and fine-tuning Foundation Models, including multimodal inputs and outputs.
Proficiency in Python, TypeScript, NodeJS, ReactJS (and equivalent) and all associated GenAI libraries and frameworks.
Experience with containerization and orchestration technologies (Kubernetes, Docker).
Proficiency in cloud platforms (AWS, Azure, GCP) and infrastructure as code (Terraform).
Experience & Skills (Nice to have)
Experience with LLM guardrails
Experience with LLM monitoring and observability
Experience with security related to LLM integration
Experience in LLM Testing and Evaluation
LLM Security

---