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Accenture

Advises businesses and runs their technology

Forward Deployed Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A bachelor's or master's degree in Computer Science, Engineering, or a related field is required.
  • At least 10 years of experience in software engineering, solutions architecture, or technical consulting is required.
  • At least 3 years of experience delivering AI/ML or LLM-based solutions in production is required.
  • A proven track record of leading complex, customer-facing technical engagements is required.
  • Write production-quality code, with expert-level proficiency in at least one programming language and the ability to learn others as needed.
  • Understand distributed systems and API design, and identify architectural risks.
  • Have experience with observability and CI/CD practices.
  • Have hands-on production experience with Claude, GPT, and Gemini, and understand model trade-offs including cost, latency, context limits, reasoning quality, and limitations.
  • Understand prompt engineering, build retrieval-augmented generation (RAG) pipelines for real-world data, and work with agentic frameworks and MCP.
  • Understand vector database selection and chunking strategy.
  • Have strength in at least one major cloud platform, such as AWS, Azure, or GCP, and understand enterprise infrastructure constraints.
  • Have production experience with containerisation and orchestration.
  • Work across data platforms such as Snowflake, BigQuery, Databricks, or bespoke platforms, and integrate large language models with complex data environments.

Responsibilities

  • Own the technical relationship with enterprise clients from initial discovery through production, including C-suite engagement and long-term roadmap influence.
  • Run workshops to identify and prioritise high-value AI use cases and translate business problems into concrete engineering plans.
  • Architect and ship enterprise-grade AI systems, selecting tools such as Claude, GPT, and Gemini based on the problem.
  • Design pipelines and agentic workflows to meet enterprise security, scalability, cost-efficiency, and reliability requirements at production load.
  • Integrate large language models with complex enterprise data environments, including cloud platforms and data warehouses.
  • Set technical direction on engagements and make architecture, tooling, and trade-off decisions.
  • Mentor engineers on both sides of the client relationship and raise the standard of the team.
  • Lead incident resolution and complex troubleshooting.
  • Define evaluation frameworks to assess model quality, safety, and business impact.
  • Implement LLMOps practices, including monitoring, observability, and drift detection in production environments.
  • Ensure every deployment meets enterprise security and compliance requirements from the outset.

Desired Qualifications

  • Experience deploying AI solutions in regulated industries such as finance, healthcare, or government.
  • Familiarity with responsible AI and model risk management frameworks.
  • Contributions to open-source projects or technical publications.
  • Experience with evaluation and observability tools such as LangSmith, Promptfoo, or Weights & Biases.
  • Prior experience in a startup or high-growth technology environment.

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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