Large Language Model Architect

Project Role : Large Language Model Architect Project Role Description : Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data. Must have skills : Google Cloud Data Services Good to have skills : Microsoft Azure Data Services, Snowflake Data Warehouse Minimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary: AI Powered Tech Talent You are a a strong individual contributor knowledge engineer growing into a team lead. You are well versed in the full knowledge graph development lifecycle. You formulate real-world problems into practical, efficient, scalable AI and Knowledge Graph solutions, working hands-on across the lifecycle from ingestion through modeling, curation, and deployment. You apply current methodologies, techniques, and algorithms with the right architecture, and begin to guide junior engineers on the project. You stay current with knowledge engineering, generative AI, LLM, and multi-modal models look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with the team. You collaborate with users, use case reps, engineers, architects, and UI designers to deliver their piece of an end-to-end solution. Build Knowledge Graph components that contribute to transforming a client's data architecture. Design, develop, and implement AI and semantic solutions ensure their work integrates cleanly with the broader system. Work alongside the project team and delivery leads. Build solid working relationships with client counterparts on their workstream. Help assemble the supporting evidence for the recommended semantic layer solution. Support Accenture sales efforts when called on. Keep developing skills in cutting-edge Data & AI solutions, especially agentic technologies, and shares with the team. Bachelor's degree or equivalent Bachelor's degree or equivalent, plus at least 3 of the following: Minimum 2 years of experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Minimum 2 years of experience in schema design, ontology management, and KG curation Minimum 2 years of designing and developing KG solutions and graph-based ML models (functional + technical) Minimum 1 year of experience with end-to-end data pipeline implementation for AI applications (esp. LLMs), with hands-on design and configuration Minimum 2 years of experience with strong knowledge of relational databases, object stores, graph databases (Stardog, Neo4J, Amazon Neptune), and vector databases (no leadership/commercial requirement at this band) 2+ years of hands-on experience with cloud platforms (AWS, Azure, GCP) 2+ years of experience in Python, with experience in frameworks like Tensorflow, PyTorch, and tools for building ETL pipelines (e.g. Apache NiFi, Airflow) Practical experience with NLP and/or Search techniques Prompt engineering, and LLMs for enterprise-scale applications. You have team lead experience Strong collaboration skills with the ability to work across engineering, research, and product teams across multiple time zones. You have external client-facing consulting experience Broad experience in diverse ML techniques and agentic systems As a Large Language Model Architect, a typical day involves designing and structuring advanced language models capable of understanding and generating human-like text. This role requires envisioning the architecture of neural networks that are trained on extensive datasets of unstructured text, ensuring the models can effectively interpret and produce natural language. The position demands continuous refinement of model parameters and collaboration with various stakeholders to align the architecture with project goals and evolving technological advancements. The architect plays a key role in shaping the capabilities and performance of language models that support diverse applications across industries. Roles & Responsibilities: - Expected to be an SME, collaborate and manage the team to perform. - Responsible for team decisions. - Engage with multiple teams and contribute on key decisions. - Provide solutions to problems for their immediate team and across multiple teams. - Lead the development and implementation of scalable language model architectures to meet project requirements. - Facilitate knowledge sharing and mentorship within the team to foster professional growth and technical excellence. - Coordinate cross-functional efforts to integrate language models into broader systems and workflows. Professional & Technical Skills: - Must To Have Skills: Proficiency in Google Cloud Data Services. - Good To Have Skills: Experience with Microsoft Azure Data Services, Snowflake Data Warehouse. - Strong expertise in designing and optimizing neural network architectures for natural language processing tasks. - Experience with large-scale data processing and management in cloud environments. - Ability to analyze and improve model performance through parameter tuning and evaluation metrics. - Familiarity with data storage, retrieval, and transformation techniques relevant to language model training. Additional Information: - The candidate should have minimum 5 years of experience in Google Cloud Data Services. - This position is based at our Bengaluru office. - A 15 years full time education is required. 15 years full time education Important Notice We have been alerted to the existence of fraudulent messages asking job seekers to set up payment to cover various costs associated with establishing employment at Accenture. No one is ever required to pay for employment at Accenture. If you are contacted by someone asking for payment, please do not respond, and contact us at india.fc.check@accenture.com immediately. Equal Employment Opportunity Statement All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Please read Accenture’s Recruiting and Hiring Statement for more information on how we process your data during the Recruiting and Hiring process.