Full Stack Large Language Model Developer Associate Director at Accenture

Arlington, Virginia, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Data & AI, ConsultingIndustries

Requirements

Minimum of 5 years of demonstrated expertise in successfully designing and building resilient AI systems or products, using Evals in AI systems, Continuous Integration, Continuous Delivery, Pair Programming, and Test-Driven Development with the ability to author robust Unit, Integration, and Functional Tests
Minimum 5 years of experience designing and creating AI Solutions using design patterns like retrieval augmentation generation (RAG) and handling data pipelines
Minimum of 5 years of experience in Engineering teams with one or more programming languages and frameworks, such as Python, Javascript, Java, Spring or GoLang, showcasing a strong command over the technical foundations and mastery of one or more AI Frameworks like Autogen, LangGraph or Semantic Kernel
Minimum of 5 years of experience working with application services from at least one public cloud (AWS, GCP, Azure, etc.)
Minimum of 4 years of experience working in AI Engineering for business applications or building products with strong understanding of fine tuning & prompt engineering
Minimum of 3 years of experience leading a team or being part of team management, preferably in AI-driven projects

Responsibilities

Design, develop, and optimize AI prompts and next-generation applications powered by Large Language Models (LLMs)
Architect and implement generative agent systems using frameworks for multi-model coordination to tackle complex tasks
Develop application and component strategies, overseeing both user experience and backend systems
Define, evaluate, and optimize AI system architectures, leveraging relevant frameworks and best practices
Conduct thorough code reviews, provide expert guidance on enhancements and issue resolution, and ensure adherence to engineering standards
Build and maintain scalable machine learning infrastructure, including distributed training pipelines and seamless integration with APIs
Apply advanced evaluation methodologies to ensure model robustness, safety, fairness, and minimize hallucination risks
Collaborate closely with cross-functional teams—including business leaders, engineers, architects, and designers—to align AI systems with business objectives
Support troubleshooting and issue resolution during testing phases as well as in production environments
Document technical architecture, methodologies, and innovations for effective knowledge transfer and ongoing advancement

Skills

LLM

Large Language Models

Prompt Engineering

Fine-tuning

Generative AI

AI Architectures

Machine Learning

Full Stack Development

Code Review

System Integration

Backend Systems

Multi-model Coordination

AI Frameworks

Accenture

Global professional services for digital transformation

About Accenture

Accenture provides a wide range of professional services, including strategy and consulting, technology, and operations, to help organizations improve their performance. Their services assist clients in navigating digital transformation, enhancing operational efficiency, and achieving sustainable growth. Accenture's offerings include cloud migration, cybersecurity, artificial intelligence, and data analytics, which are tailored to meet the needs of various industries such as financial services, healthcare, and retail. What sets Accenture apart from its competitors is its extensive industry knowledge and ability to deliver comprehensive solutions that address both immediate challenges and long-term goals. The company's aim is to support clients in reducing their environmental impact while driving innovation and growth.

Dublin, IrelandHeadquarters

1989Year Founded

$8.5MTotal Funding

IPOCompany Stage

Consulting, Enterprise Software, CybersecurityIndustries

10,001+Employees

Risks

Rapid AI advancements may outpace Accenture's current capabilities, risking competitive disadvantages.

Integration challenges from multiple acquisitions could affect Accenture's operational efficiency.

The rise of AI-driven startups may disrupt Accenture's market share in customer service solutions.

Differentiation

Accenture's acquisitions enhance its capabilities in digital twin technology for financial services.

The company is expanding its expertise in net-zero infrastructure through strategic acquisitions.

Accenture's focus on software-defined vehicles positions it as a leader in automotive innovation.

Upsides

Accenture's investment in EMTECH supports central bank modernization amid digital currency evolution.

The acquisition of Award Solutions boosts Accenture's presence in the growing 5G and IoT markets.

Accenture's strategic acquisitions align with high-growth markets like digital twins and net-zero projects.

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