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Accenture

Advises businesses and runs their technology

AI Native Software Engineering

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

About the Job

Requirements

  • Extensive software engineering experience in production environments.
  • Hands-on experience designing and deploying agentic AI solutions in a production environment.
  • Demonstrated production-depth experience with agentic orchestration frameworks such as LangGraph, CrewAI, AutoGen, or equivalent.
  • Direct experience calling large language model APIs such as OpenAI, Anthropic, or Vertex AI in production code, including provider abstraction, token management, and latency and cost tradeoffs.
  • Experience owning retrieval-augmented generation pipelines, including embeddings, chunking strategy, vector databases, and context engineering.
  • Knowledge of large language model operations fundamentals, including evaluation harness design, prompt versioning, and production observability.
  • Cloud-native engineering experience with Kubernetes, Docker, microservices, serverless, continuous integration and continuous delivery, and infrastructure as code using Terraform or Helm.
  • Strong Python skills; Java or an equivalent backend language is acceptable.
  • Production debugging and observability experience.

Responsibilities

  • Design and build production-grade agentic systems end-to-end, including multi-agent orchestration, retrieval-augmented generation pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability.
  • Build and own retrieval-augmented generation pipelines, including embeddings, chunking strategy, vector search, context-window engineering, and tuning against quality targets.
  • Integrate and abstract across multiple large language model providers, including OpenAI, Anthropic, Vertex AI, and open-source models, with fallback routing and token, cost, and latency management.
  • Implement large language model operations in production, including evaluation harnesses with quality metrics, prompt versioning, observability tooling such as LangSmith or Braintrust, and cost and safety monitoring.
  • Embed directly with client engineering teams to design, prototype, and deploy agentic solutions through workshops, proofs of concept, code-with sessions, and architecture walkthroughs.
  • Build reusable patterns, accelerators, and playbooks that scale beyond individual client engagements and help subsequent engagements start faster.
  • Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness; present findings and recommendations to client stakeholders in business terms.

Desired Qualifications

  • Quality of experience is weighted over years; candidates who have shipped three production agentic systems in four years are preferred over generalists with passive AI exposure.

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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