Senior AI Engineer & Tech Lead for Enterprise Agentic AI

Accenture; Culver City (CA); On-site; USD 133,000 - 302,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

401(k) plan

Bonus opportunities

Paid holidays

Paid time off

Job summary

Accenture is seeking an AI Native Engineer with 3+ years of hands-on experience building cloud-native AI agents for enterprise environments. You will design, deploy, and scale agentic workflows across complex domains, partnering with clients and ecosystem partners to deliver robust AI-native solutions.

You’ll work directly with clients, shaping use cases, prototyping rapidly, and embedding within client environments to ensure secure, scalable implementations and measurable business impact.

Qualifications

• Minimum 10 years' experience with end-to-end software engineering and SDLC expertise.
• Minimum 8 years' experience in cloud-native systems, APIs, microservices, containerization, serverless.
• Programming in Python, Java, or equivalent; familiarity with evaluation tooling, logging, monitoring, and agent observability.
• Deploying to production — CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging.
• With client communication and collaboration, including being capable of leading technical workshops and delivering under ambiguity.
• Minimum of 3 years’ experience in engineering with cloud-native systems (APIs, microservices, containerization, serverless).
• Minimum of 2 years of hands-on experience designing and delivering Agentic AI solutions.
• Minimum of 1.5 years' experience with semantic models, knowledge graphs, or enterprise knowledge.
• Using coding agents and AI-assisted software development.
• Minimum of 1 year expertise in designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments.
• Bachelor's degree or equivalent work experience.

Responsibilities

• Agent Architecture and Engineering: Design and engineer enterprise-ready AI agents encompassing retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
• AI Platform Integration: Develop abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.) to enable seamless integration and enablement.
• Cloud-Native Engineering: Leverage containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability to deliver scalable AI-native systems.
• Domain-Specific Workflows: Tailor and deploy agentic applications across verticals — e.g., finance, healthcare, retail — addressing domain-specific processes via intelligent automation.
• Client Engagement: Conduct design workshops, POCs, and code-with sessions to shape data-driven agent workflows with stakeholders, fostering trust and adoption.
• Measure & Improve: Define and use key metrics, test harnesses, and evaluation plans to measure agent accuracy, latency, safety, and cost effectiveness.
• Knowledge Sharing: Craft reusable patterns, documentation, and best practices to influence internal assets and client roadmaps.

Skills

End-to-end software engineering

SDLC expertise

Python or Java

Evaluation tooling

Logging & monitoring

Client communication

Ambiguity navigation

Cloud-native systems

APIs & microservices

Containerization

Serverless

OpenAI/Claude & AI models

Agentic AI fundamentals

Education

Bachelor's degree or equivalent

Tools

Terraform

Helm

Kubernetes

Docker

Job description

Accenture is seeking an AI Native Engineer with 3+ years of hands-on experience building cloud-native AI agents for enterprise environments. You will design, deploy, and scale agentic workflows across complex domains, partnering with clients and ecosystem partners to deliver robust AI-native solutions.

You’ll work directly with clients, shaping use cases, prototyping rapidly, and embedding within client environments to ensure secure, scalable implementations and measurable business impact.