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Accenture

Advises businesses and runs their technology

Large Language Model Architect

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • A bachelor's degree or equivalent is required.
  • At least 5 years of experience with Google Cloud Data Services is required.
  • At least 2 years of experience with Knowledge Graph technologies, including RDF, SPARQL, LPG, and SHACL, is required.
  • At least 2 years of experience in schema design, ontology management, and Knowledge Graph curation is required.
  • At least 2 years of experience designing and developing Knowledge Graph solutions and graph-based machine learning models is required.
  • At least 1 year of experience implementing end-to-end data pipelines for AI applications, especially large language models, including hands-on design and configuration, is required.
  • At least 2 years of experience with relational databases, object stores, graph databases such as Stardog, Neo4j, and Amazon Neptune, and vector databases is required.
  • At least 2 years of hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform is required.
  • At least 2 years of experience with Python and frameworks such as TensorFlow and PyTorch, and tools for building extract, transform, and load pipelines such as Apache NiFi and Airflow, is required.
  • Practical experience with natural language processing and/or search techniques is required.
  • Experience with prompt engineering and large language models for enterprise-scale applications is required.
  • Team lead experience is required.
  • External client-facing consulting experience is required.
  • Broad experience in diverse machine learning techniques and agentic systems is required.
  • The candidate must have 15 years of full-time education.
  • The candidate must have strong knowledge of relational databases, object stores, graph databases, and vector databases.
  • The candidate must be able to design and optimize neural network architectures for natural language processing tasks.
  • The candidate must have experience with large-scale data processing and management in cloud environments.
  • The candidate must be able to analyze and improve model performance using parameter tuning and evaluation metrics.
  • The candidate must be familiar with data storage, retrieval, and transformation techniques relevant to language model training.
  • The candidate must be able to collaborate across engineering, research, and product teams in multiple time zones.

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, 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.
  • Share learnings with the team and 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 and ensure they integrate with the broader system.
  • Work alongside the project team and delivery leads, and build working relationships with client counterparts on the workstream.
  • 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 learnings with the team.
  • Design and structure advanced language models capable of understanding and generating natural language, refining model parameters and collaborating with stakeholders to align architecture with project goals.
  • 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 for the immediate team and across multiple teams.
  • Lead development and implementation of scalable language model architectures to meet project requirements.
  • Facilitate knowledge sharing and mentorship within the team.
  • Coordinate cross-functional efforts to integrate language models into broader systems and workflows.

Desired Qualifications

  • Experience with Microsoft Azure Data Services is desirable.
  • Experience with Snowflake Data Warehouse is desirable.

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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