Full Stack Agentic AI Engineer

We Are

Accenture is helping enterprises reinvent their organizations and businesses with human-centered AI solutions and services to drive breakthrough innovation and lasting competitive advantage. With more than 45,000 AI and data professionals across the company, our AI & Data practice brings together cutting-edge AI technologies, deep industry experience, strategic investment, exceptional interdisciplinary talent, and a powerful ecosystem of partners to help clients scale AI with speed and confidence.

You Are

A Full Stack Agentic AI Engineer leader who focuses on delivering end‑to‑end agentic AI solutions while providing advanced technical expertise to support complex Mid‑Market customer engagements. The scope spans agentic AI as a Service intelligent systems, full‑stack solution development, and human‑AI interaction, alongside close collaboration with diverse teams, including but not limited, client teams, global capability teams, and operational teams, to translate business challenges into scalable, production‑ready agentic AI solutions.

The Work

The role contributes to building and positioning cloud‑based, customizable advanced agentic AI offerings, combining hands‑on solution development with discovery, technical validation, and customer‑facing demonstrations to enable credible, highly differentiated agentic AI‑as‑a‑Service outcomes.

Key Responsibilities

+ Design, build, deploy, and operate end to end, human-centered agentic AI systems across frontend, backend, data, and intelligent components

+ Integrate AI / ML / NLP capabilities into workflows to address real-world client or business problems

+ Implement agentic AI behaviors using human-centered design and hybrid neural symbolic approaches

+ Support complex Mid-Market sales opportunities by partnering with Sales to shape advanced technical solutions

+ Participate in discovery sessions to identify customer challenges, objectives, and technical requirements

+ Lead technical demos, workshops, and proof of concept engagements to demonstrate solution fit and value

+ Contribute to technical solution design and input into proposals, statements of work, and contracts

+ Provide technical guidance on industry use cases, best practices, and pre delivery considerations

+ Develop scalable APIs and services that ensure performance, reliability, and maintainability

+ Collaborate across product, business, and sales teams to deliver cohesive technical and customer facing outcomes

Travel may be required for this role.  The amount of travel will vary from 0 to 100% depending on business need and client requirements.

Here's what you need

+ Minimum of 7 years of experience as a full stack AI or machine learning engineer or scientist, working with AI / ML models in production at scale, including monitoring, alerting, bug fixing and auditing

+ Minimum of 7 years of experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming

+ Minimum of 5 years of experience in distributed computing systems and architecture that may support AI / Agentic AI applications, big data analytics, engineering simulations, scientific compute, grid and cloud computing, distributed networks

+ Minimum of 4 years of experience in building and deploying AI / ML based software to a cloud environment.

+ Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate's Degree, must have minimum 6 years work experience)

Professional Skills Requirements

+ Strong written & verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders

+ Strong client-facing skillsets in a consulting environment

+ Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams

+ Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation

Bonus points if you have

+ Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., Tensor Flow, PyTorch).

+ Experience working with language models like LLM's APIs and optimizing their usage for specific…