Generative AI Software Engineer Specialist (all genders)

Who We Are

Accenture Song is the world's largest tech-powered creative group — a fusion of creativity, technology, intelligence, and experience. Within Song, our practice helps iconic brands reinvent the products, services, and spaces that define their relationship with customers. We work across the full spectrum: from defining product strategy and crafting human-centred digital experiences to engineering the AI-powered platforms and design systems that bring them to life at scale.

We operate like a studio embedded inside a global consultancy: small, high-craft teams with a direct line between design decisions and shipped products. With 70 Song Studios and more than 4,000 designers and makers across six continents, our Design & Digital Products team brings together specialists in Product Design, Product Management, Engineering, Experience Design, and Content Design — all united by a belief that the best digital products make people's lives genuinely better.

For us, AI is not a feature we bolt on — it is the operating model we build around. We are actively shaping what it means to design, build, and deliver AI-native products at enterprise scale, and we are looking for engineers who want to be at the centre of that reinvention.

Who You Are

You are an AI Native Product Engineer with demonstrated experience building cloud-native systems and shipping production‑grade AI solutions. You combine hands‑on engineering depth with the creativity and product intuition to shape solutions that make sense for real users and enterprises. You’re as comfortable writing production code as you are whiteboarding system designs, facilitating a client workshop, or mapping a product roadmap. You thrive in ambiguity and act as a bridge between vision and execution.

You do not treat AI as a toolset to learn on the side. It is your primary medium. You architect around large language models, retrieval systems, and multi‑agent orchestration the way previous generations of engineers built around microservices — with rigour, craft, and a clear eye on what will actually work in production. You translate complex AI behaviour into tangible user experiences that non‑technical stakeholders can understand and trust.

The Work

You will embed directly with clients as a technologist, product thinker, and trusted engineering partner. Working within cross‑functional Song studio teams — alongside Product Designers, Experience Designers, Product Managers, and Strategists — you will lead the engineering of AI‑native digital products from concept through to production. You will shape not only what gets built but how it gets built, setting the technical standard for AI‑native delivery within the practice. This is not a back‑office role. You will be in the room with clients, translating AI possibilities into product realities, and in the codebase, making those realities work.

AI‑Native Product Engineering

• Product Orchestration: Partner with business and technical stakeholders to frame problems, align priorities, and translate needs into orchestrated AI workflows.
• Agent Architecture & Engineering: Design and engineer enterprise‑ready AI agents — including retrieval, orchestration, policy‑based routing, tool invocation, evaluation harnesses, and lifecycle observability.
• Human‑AI Experience Engineering: Translate complex AI behaviours (confidence states, reasoning traces, agentic actions, fallback flows) into transparent, controllable, and accessible user experiences — in close collaboration with Experience Designers and Product Designers.
• AI Platform Integration: Build robust abstraction layers across AI providers (Anthropic Claude, OpenAI, Google Vertex AI, open‑source models) to create portable, multi‑provider pipelines that reduce client lock‑in and maximise flexibility.
• AI Design System Contributions: Contribute to AI‑native component libraries and design system patterns — error states, human‑in‑the‑loop interactions, progressive disclosure of AI reasoning — ensuring consistency and scalability across client products.

Cloud‑Native Engineering & Delivery

• Scalable Systems: Apply containerisation (Kubernetes, Docker), microservices, serverless, and event‑driven architectures to ship AI‑native systems that perform reliably at enterprise scale.
• Production Discipline: Own CI/CD pipelines, infrastructure‑as‑code (Terraform, Helm), monitoring, and debugging. Deploy to production and take responsibility for what you ship.
• Rapid Prototyping: Build working prototypes and proof‑of‑concept systems that close the gap between design vision and technical reality — using AI tooling actively to accelerate your own delivery.

Client Partnership & Practice Building

• Trusted Advisor: Serve as the primary technical voice in client engagements — framing problems, aligning technical trade‑offs with business goals, and communicating clearly to both engineers and executive stakeholders.
• Workshop Facilitation: Lead design sprints, co‑creation sessions, and code‑with workshops. Bring clients into the process, not just the outcome.
• Measurement & Improvement: Define and track evaluation frameworks for agent accuracy, latency, cost, and safety. Use data to drive continuous improvement of deployed AI systems.
• Knowledge Amplification: Document reusable patterns, architectural decision records, and best practices.

• Demonstrated engineering experience with cloud‑native systems — APIs, microservices, containerisation, serverless architectures.
• Deep, production‑proven expertise in agentic AI systems: agents, multi‑agent orchestration, context engineering, RAG pipelines, and workflow automation.
• Hands‑on experience with leading AI platforms — Anthropic Claude, OpenAI, Google Vertex AI — and comfort building abstraction layers across multiple providers.
• Strong programming skills in Python (primary) and at least one of Java, TypeScript, or C#; experience with evaluation tooling, logging, and agent observability stacks.
• Production deployment experience: CI/CD, infrastructure‑as‑code (Terraform, Helm), monitoring, incident response, and debugging.
• Fluency in English — able to run workshops, present to executives, and write technical documentation.
• Bachelor's degree in Computer Science, Engineering, or equivalent; AI certifications or demonstrated agentic tooling experience is a plus.

Bonus Points

• Experience at the intersection of design and engineering — contributing to or building upon design systems, working alongside UX/product designers on AI‑powered experiences.
• Background as a Product Engineer, Solutions Architect, or Forward‑Deployed AI Engineer in a consulting, agency, or product studio environment.
• Familiarity with responsible AI principles: guardrails, content filters, human‑in‑the‑loop design, bias evaluation, and fallback strategies.
• Experience across multiple industries — retail, finance, healthcare, media — tailoring agentic workflows to sector‑specific processes and compliance requirements.
• A portfolio of shipped work: apps, agents, open‑source contributions, hackathon projects, or startup experience that demonstrates creative problem‑solving under constraints.
• German language good to have, but not mandatory.

The Accenture Song Culture: Here, YOU Make the Difference

Our Design & Digital Products practice thrives on collaboration, curiosity, and a relentless commitment to craft. We build small, high‑ownership teams where the distance between a design decision and a shipped product is intentionally short. You will work alongside some of the most talented designers, strategists, and engineers in the industry — and you will have the backing of Accenture's global scale and client relationships.

Accenture champions inclusion and diversity as core to how we work and grow. Your skills, perspective, and ambition make you unique — and when diverse strengths come together, extraordinary things happen. We support flexible working models, meaningful career development, and a culture where what you contribute matters more than where you sit in the hierarchy. As a business imperative, every person at Accenture has the responsibility to create and sustain an inclusive environment. Inclusion and diversity are fundamental to our culture and our core values.

#LI-EU