Full-Time

Large Language Model Architect

Posted on 8/21/2026

Accenture

Accenture

10,001+ employees

Global professional services and technology consulting

No salary listed

Bengaluru, Karnataka, India

In Person

Bachelor's

Category
AI & Machine Learning (2)
,
Required Skills
LLM
Distributed Systems
Neural Networks
Machine Learning
Microservices

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Requirements
  • A minimum of 18 years of experience is required.
  • A minimum of 20 years of experience in Large Language Models is required.
  • At least 15 years of full-time education is required.
  • Proficiency in Large Language Models is required.
  • Experience designing and tuning neural network architectures for natural language processing tasks is required.
  • Strong knowledge of deep learning frameworks and tools used to train large-scale models is required.
  • Ability to handle and preprocess large datasets, particularly unlabeled text corpora, is required.
  • Familiarity with techniques for optimizing model training and inference efficiency is required.
  • Capability to analyze model outputs and troubleshoot language generation and understanding issues is required.
  • Knowledge of solution architecture, business requirements analysis, technical solution design, AI-native architecture patterns, complex software engineering, distributed systems and microservices, platform engineering principles, semantic technologies and knowledge graphs, agentic workflow architecture, event-driven architectures, real-time systems design, workshop facilitation, stakeholder engagement, technology evaluation, cost and effort estimation, integration architecture, AI/ML solution patterns, enterprise architecture, documentation and proposals, and value case development is required.
Responsibilities
  • Architect large language models that process and generate natural language.
  • Design neural network parameters trained on large quantities of unlabeled text data.
  • Collaborate with data scientists and engineers to integrate language models into broader systems and applications.
  • Evaluate model performance and implement improvements to enhance accuracy and efficiency.
  • Stay updated with research and advancements in natural language processing and machine learning.
  • Develop documentation and guidelines for model deployment and maintenance.
  • Mentor junior team members and support their professional growth within the project.
  • Lead solution design for complex artificial intelligence transformation initiatives by translating business requirements into comprehensive technical solutions.
  • Architect end-to-end solutions spanning AI/ML models, data pipelines, integration layers, user experiences, and operational systems using platform engineering principles.
  • Design AI-native architectures incorporating agentic workflows, semantic technologies, knowledge graphs, and distributed AI systems.
  • Apply complex software engineering patterns, including microservices, event-driven architectures, and real-time systems, to design scalable and maintainable solutions.
  • Conduct discovery workshops with business stakeholders to understand problems, constraints, and success criteria.
  • Create solution blueprints, architecture diagrams, and technical proposals for executive and technical audiences.
  • Evaluate build-versus-buy decisions, technology selections, and integration approaches for transformation initiatives.
  • Assess AI-specific architectural concerns, including latency, token costs, model drift, data quality, and observability.
  • Estimate effort, cost, and timelines for proposed solutions with engineering and delivery teams.
  • Partner with architects, engineers, and product teams to refine solutions from concept through implementation.
  • Define solution success metrics and value-realization approaches tied to business outcomes.
  • Navigate technical debt, legacy systems, and organizational constraints to design pragmatic, implementable solutions.
  • Design reusable platform-oriented solutions that serve multiple use cases and scale across the organization.

Accenture is a global professional services firm that helps companies navigate technology-driven change. It offers strategies and services across consulting, digital, technology, and operations, with a strong emphasis on cloud, artificial intelligence, security, and enterprise reinvention. Accenture works by delivering end-to-end solutions, combining advisory work with implementation, technology platforms, and managed services to transform how organizations operate and compete in today’s digital world. The company differentiates itself through its long history as a dedicated tech-advisory arm that gained independence in 2001, its scale, and its active acquisitions—particularly since 2013—to expand capabilities in digital, cloud, and security. Its goal is to help the world’s largest corporations rethink and reshape their operations to stay ahead of rapid technological shifts.

Company Size

10,001+

Company Stage

IPO

Headquarters

Dublin, Ireland

Founded

1989

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Simplify Jobs

Simplify's Take

What believers are saying

  • Q3 FY26 revenue rose 6% to $18.7 billion, with a 17.0% operating margin.
  • Q1 FY26 advanced AI bookings hit $2.2 billion, nearly doubling year over year.
  • July 10, 2026, Accenture raised $5 billion in notes for acquisitions, buybacks, and working capital.

What critics are saying

  • June 18, 2026, Middle East conflict cut Q3 revenue by about $100 million.
  • Accenture trimmed FY26 local-currency growth to 3%-4%, signaling slower deal closures.
  • Federal and managed-services weakness makes AI displacement an existential margin risk.

What makes Accenture unique

  • July 7, 2026, Accenture Edge and Google Cloud launched prebuilt mid-market agentic AI.
  • June 2026, Accenture became OpenAI's first AI Transformation Partner of the Year.
  • July 2026 acquisitions of Dragos, runZero, and NetRise built a scaled xOT cybersecurity platform.

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Benefits

Health Insurance

Professional Development Budget

401(k) Retirement Plan

401(k) Company Match

Company News

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Jul 31st, 2026
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Accenture launched a dedicated mid-market business segment in June 2026, reporting a 13% net income margin for the quarter ended 31 May 2026. The global professional services company's revenue shows modest year-over-year growth, reaching $18.7 billion in Q2 2026. Microsoft restructured its senior leadership team in May 2026, adopting a flatter organisational framework for the artificial intelligence era. The company achieved a 40% net income margin for the quarter ended 30 June 2026, with revenue reaching $90 billion. Microsoft's quarter-over-quarter revenue increases significantly outpace Accenture's growth, driven by customer demand for AI offerings. Microsoft reported diluted earnings per share of $4.81 in its fiscal fourth quarter, up from $3.65 the previous year, demonstrating profitability alongside heavy AI infrastructure investment.

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Jul 30th, 2026
Accenture trades at 13.6x earnings after 35% stock drop despite strong 15.8% margins and $9B acquisition plans

Accenture trades at 13.6 times earnings after its stock fell 35% last year whilst the S&P 500 climbed, creating a steep discount to the market's 24.4 median multiple. The IT consulting firm maintains a 15.8% operating margin and generates a free cash flow yield of 11.9%, though three-year revenue growth of 4.8% trails the market median of 7.8%. The company disclosed a $100 million revenue impact from Middle East conflict and delayed managed services opportunities pushing into fiscal 2027. Management plans to deploy approximately $9 billion in acquisitions this year, including expansion into OT security. Accenture also launched Accenture Edge to target a $240 billion addressable market amongst mid-sized companies. The firm guided fourth-quarter revenue between $17.75 billion and $18.4 billion, with results expected to test whether current pressures represent temporary headwinds or fundamental business challenges.

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