AI Native Software Engineer

Accenture

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
ChicagoMilwaukeeDallasColumbusKirklandCincinnatiNew YorkClevelandOklahoma CityAustinAlbanyArlingtonSt. PeteHartfordPittsburghSt. LouisMiamiSacramentoRaleighMinneapolisMountain ViewScottsdaleSan FranciscoMorristownDenverBostonPhiladelphiaDes MoinesOverland ParkLos AngelesCharlotteWalnut CreekCarmelSeattleHoustonAtlantaOrlandoRedmondBentonvilleBeavertonNashvilleDetroitSan Diego
Salary
$94,400–$316,300 / yr
Employment
Full-time
Posted
2 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $183k
This role $205k
$68k most similar roles pay here $343k

This role pays more than 68% of similar roles. Most pay $147,818–$219,150 — the shaded band above. At the midpoint, this role pays about $205k versus about $183k for comparable roles.

Based on 240 similar postings.

Employer

About Accenture

Accenture is a leading global professional services company specializing in IT, strategy, consulting, and operations, with a strong focus on digital transformation, cloud computing, and artificial intelligence.

Accenture currently has 221 open roles on FindRole.

Listed pay typically runs $94,400–$266,300 across 175 roles with salary data.

Most-posted roles

View all roles at Accenture

At a glance

TL;DR · AI Native Software Engineer

As an AI Native Software Engineer, you will join a team focused on building production systems where AI is a first-class engineering capability. You will own the entire technical lifecycle, transforming ambiguous requirements into robust architectures and executable products. Your daily work involves designing distributed systems, managing cloud infrastructure, developing APIs, and building agentic capabilities integrated into live enterprise workflows. You will utilize technologies including Java, Python, Go, TypeScript/JavaScript, and C#, while leveraging AWS, Azure, or GCP platforms with Docker, Kubernetes, and Terraform. The role requires expertise in DevSecOps, CI/CD pipelines, and data engineering across relational and non-relational stores. You will solve complex problems by integrating frontier models from providers like OpenAI and Anthropic into production environments, ensuring these probabilistic components remain trustworthy within deterministic enterprise systems while utilizing AI-native tools to accelerate development.

What you'll do

  • Design and build end-to-end production systems including front-end, APIs, backend services, data flows, and infrastructure.
  • Develop and deploy cloud-native platforms using containers, Kubernetes, serverless technologies, and infrastructure as code.
  • Build and manage automated CI/CD pipelines with integrated security scanning, testing, and deployment controls.
  • Design and implement production AI systems featuring agentic capabilities, retrieval-augmented generation, and evaluation frameworks.
  • Integrate advanced AI models into enterprise workflows while ensuring safety through guardrails and observability tools.
  • Use AI-native engineering techniques to automate code generation, testing, documentation, and system modernization.
  • Lead multidisciplinary teams by setting technical standards and communicating complex trade-offs to client stakeholders.
  • Convert project outcomes into reusable patterns, tooling, and internal assets to improve organizational capabilities.

What we're looking for

  • Minimum of 5 years of professional software engineering experience building and operating production systems.
  • Minimum of 5 years of hands-on experience across the stack from front end/APIs to services, integration, and persistence.
  • Minimum of 5 years of programming experience in Java, Python, Go, TypeScript/JavaScript, or C#.
  • Minimum of 5 years of experience with a major cloud platform (AWS, Azure, or GCP) including containers, orchestration, and infrastructure as code.
  • Minimum of 5 years of experience designing and operating CI/CD pipelines with automated testing and security controls.
  • Minimum of 1 year of experience building and deploying AI-enabled or agentic systems in production or near-production environments.
  • Minimum of 1 year of experience applying AI-native engineering tools and workflows to daily software development tasks.
  • Minimum of 5 years of experience leading engineering teams or significant technical workstreams including client-facing discussions.
  • Bachelor's degree in Computer Science, Engineering, or equivalent (or 12 years of experience).
  • Relevant cloud, security, or AI certifications (preferred).
  • Experience building multi-agent orchestrations using frameworks like LangGraph, Crew AI, or OpenAI SDK (preferred).
  • Portfolio or public repository featuring self-built agents, tools, or plugins (preferred).

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