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Accenture · 23 hours ago

AI Native Software Engineer

Arlington, VA

Full-time

Hybrid

Mid, Senior Level

$64K/yr - $196K/yr

3+ years exp

Accenture is a forward-thinking services company at the forefront of AI-native innovation. They are seeking an AI Native Software Engineer who will design and deliver complex agentic solutions and embed directly with clients to develop and deploy AI-native systems across enterprise environments.

Business Information SystemsConstructionConsultingInformation ServicesInformation TechnologyInfrastructureManagement ConsultingOutsourcing

No H1B

Responsibilities

Lead the design and delivery of complex agentic solutions and mentor/coach other engineers

Serve as an individual contributor owning key technical areas end to end

Help shape the playbook for how enterprises adopt and scale AI-native engineering

Embed directly with clients — acting as both technologist and trusted advisor

Partner with stakeholders to define use cases, rapidly prototype, and deploy agentic workflows that are robust, secure, and operational in complex enterprise domains

Design and build enterprise-ready AI agents incorporating retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability

Implement resilient, testable, and maintainable agentic workflows that can be iterated on quickly

Develop and/or extend abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.) to enable seamless integration and multi-provider enablement

Contribute to shared libraries, SDKs, and patterns that can be reused across clients

Leverage containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability stacks to deliver scalable AI-native systems

Own deployment, monitoring, and troubleshooting for your services in production

Tailor and deploy agentic applications across verticals (e.g., finance, healthcare, retail), adapting to domain-specific processes and constraints

Work closely with client SMEs to translate business workflows into agentic solutions

Participate in and/or lead design workshops, POCs, and code-with sessions to shape data-driven agent workflows with stakeholders, fostering trust and adoption

Communicate trade-offs, risks, and recommendations clearly to both technical and non-technical audiences

Define and use key metrics, test harnesses, and evaluation plans to measure agent accuracy, latency, safety, and cost effectiveness

Iterate rapidly based on data, feedback, and changing requirements

Craft reusable patterns, documentation, and best practices that influence internal assets and client roadmaps

Contribute to internal communities of practice around AI-native and agentic engineering

Qualification

Cloud-native systemsAgentic solutionsAI platformsPython programmingCI/CD deploymentContainerizationMicroservicesClient communicationTechnical discussionsMentoring

Required

Minimum of 3 years of engineering experience with cloud-native systems (APIs, microservices, containerization, serverless)

Minimum of 1 year of hands-on experience designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production or near-production environments

Minimum of 1 year of experience with modern AI platforms — OpenAI, Claude, Vertex AI, or open-source models — including building or using abstraction layers for multi-provider pipelines

Minimum of 3 years programming experience in Python, Java, or equivalent, with familiarity in evaluation tooling, logging, monitoring, and agent observability

Minimum of 3 years of experience deploying to production using CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging

Minimum of 3 years of experience in client-facing communication and collaboration, including leading technical discussions, workshops, or delivery sessions under ambiguity

Bachelor's degree in Computer Science, Engineering or equivalent OR equivalent (minimum 12 years) work experience. (If Associate's Degree, must have minimum 6 years work experience)

Preferred

Relevant AI certifications or agentic tooling experience are a plus

You've served as an Agentic / AI Engineer in an enterprise environment

You have additional AI certifications or experience with agentic tooling and frameworks

You've defined or worked with enterprise-grade architectures for compound AI systems, orchestration frameworks, or agent registry / stream-based architectures

You understand the AI-native paradigm — blending cloud-native with generative model architectures — optimizing for performance, modularity, and efficiency

You've delivered solutions across multiple industries (e.g., finance, healthcare) by tailoring agentic workflows to industry needs

Led a small team of engineers, providing coaching, feedback, and career development

Driven execution across multiple workstreams, ensuring quality, delivery, and alignment with client outcomes