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Accenture

Advises businesses and runs their technology

Large Language Model Architect

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • A bachelor's degree or equivalent.
  • At least 5 years of experience with Snowflake Data Warehouse.
  • At least 2 years of experience with Knowledge Graph technologies such as RDF, SPARQL, LPG, and SHACL.
  • At least 2 years of experience in schema design, ontology management, and Knowledge Graph curation.
  • At least 2 years of experience designing and developing Knowledge Graph solutions and graph-based machine learning models, both functional and technical.
  • At least 1 year of experience implementing end-to-end data pipelines for artificial intelligence applications, especially large language models, including hands-on design and configuration.
  • At least 2 years of experience with relational databases, object stores, graph databases such as Stardog, Neo4j, and Amazon Neptune, and vector databases.
  • At least 2 years of hands-on experience with cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform.
  • At least 2 years of experience with Python, TensorFlow, PyTorch, and tools for building extract, transform, and load pipelines such as Apache NiFi and Airflow.
  • Practical experience with natural language processing and/or search techniques.
  • Experience with prompt engineering and large language models for enterprise-scale applications.
  • Team lead experience.
  • External client-facing consulting experience.
  • Broad experience in diverse machine learning techniques and agentic systems.
  • Strong understanding of data warehousing concepts and cloud-based data storage solutions.
  • Experience designing scalable data architectures to support machine learning workloads.
  • Familiarity with data processing pipelines and optimization techniques for large datasets.
  • Ability to analyze and troubleshoot complex data integration and performance issues.
  • Strong collaboration skills and ability to work across engineering, research, and product teams in multiple time zones.
  • 15 years of full-time education.

Responsibilities

  • Architect large language models that process and generate natural language, including designing neural network parameters trained on large quantities of unlabeled text data.
  • Formulate real-world problems into practical, efficient, and scalable artificial intelligence and Knowledge Graph solutions, working hands-on across ingestion, modeling, curation, and deployment.
  • Apply current methodologies, techniques, and algorithms with appropriate architecture, and guide junior engineers on the project.
  • Stay current with knowledge engineering, generative artificial intelligence, large language models, and multimodal models, and identify opportunities to apply them.
  • Design, evaluate, and maintain ontologies as needed.
  • Articulate the value of generative artificial intelligence and Knowledge Graph approaches for business problems, and share learnings with the team.
  • Collaborate with users, use-case representatives, engineers, architects, and user-interface designers to deliver an end-to-end solution.
  • Build Knowledge Graph components that contribute to transforming a client's data architecture.
  • Design, develop, and implement artificial intelligence and semantic solutions, ensuring they integrate cleanly with the broader system.
  • Work alongside the project team and delivery leads.
  • Build working relationships with client counterparts on the workstream.
  • Help assemble supporting evidence for the recommended semantic layer solution.
  • Support sales efforts when called upon.
  • Continue developing skills in data and artificial intelligence solutions, especially agentic technologies, and share knowledge with the team.
  • Design and structure advanced language models capable of understanding and generating human-like text, including neural network configurations that process unstructured text data.
  • Envision scalable architectures for training and deploying language models, ensuring performance and accuracy requirements are met.
  • Collaborate with teams to align model capabilities with project goals and refine model parameters to improve language comprehension and generation.
  • Serve as a subject-matter expert, collaborate with and manage the team, and take responsibility for team decisions.
  • Engage with multiple teams and contribute to key decisions.
  • Provide solutions to problems for the immediate team and across multiple teams.
  • Lead development and implementation of architectural strategies for large language models.
  • Facilitate knowledge sharing and mentorship within the team.
  • Coordinate cross-functional efforts to integrate language models into broader systems.

Desired Qualifications

  • Experience with Microsoft Azure Data Services.
  • Experience with Data Science.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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