Advanced AI Full Stack Engineer

About the role

We are at the forefront of a new era in enterprise AI — one that moves beyond isolated models and experiments toward fully governed, production-grade AI systems. Our Data & AI practice brings together more than 45,000 professionals dedicated to helping clients build, deploy, and operate AI at scale. We design and engineer the platforms, runtimes, and developer tooling that make autonomous AI agents a reliable reality for the world's largest organizations.

Responsibilities

• Design and build agent orchestration runtimes — stateful execution loops that coordinate tool discovery, model inference, approval gates, and context management.
• Implement sandboxed execution environments with declarative policy enforcement (network egress, filesystem, compute quotas) that isolate agent workloads at the infrastructure level.
• Develop pluggable provider interfaces so that sandbox backends (container-based or microVM-based) are swappable without changing agent code.
• Build Python and Node.js/TypeScript SDKs and CLIs that give developers first-class interfaces for authoring, validating, and running AI agents locally and in enterprise environments.
• Design REST, gRPC, and event-streaming APIs (WebSocket, SSE) that serve as the communication backbone between agent runtimes, IDE integrations, and platform services.
• Implement framework adapters that normalize event streams from multiple AI frameworks into a unified platform event model, enabling consistent observability and governance regardless of the underlying agent framework.
• Build and maintain intelligent inference routing layers that intercept model API calls and dispatch them to on-premise or cloud model endpoints based on data-sovereignty, cost, and capability policies.
• Engineer multi-tier memory architectures spanning in-process working memory, cross-session relational stores, vector databases for semantic retrieval, and version-controlled procedural pipelines — each backed by swappable provider interfaces.
• Implement ephemeral credential injection and RBAC-scoped data access so agents operate under least-privilege principles without long-lived secrets in agent code.
• Instrument platform components with distributed tracing (OpenTelemetry), cost attribution, and P50/P95/P99 latency metrics exportable to standard observability backends.
• Build CI/CD governance tooling — static validation pipelines that enforce schema correctness, separation-of-duty rules, and regulatory constraints before agent packages are promoted to production registries.
• Implement human-in-the-loop approval gates and audit-trail mechanisms compatible with enterprise compliance requirements.
• Work closely with cross-functional teams — AI researchers, product managers, security engineers, and enterprise architects — to align platform capabilities with real-world agent use cases.
• Provide technical guidance on platform architecture decisions, code reviews, and engineering best practices across the team.
• Communicate architectural trade-offs and platform roadmap decisions clearly to both technical and non-technical stakeholders.

Requirements

• Bachelor's degree (or equivalent minimum 12 years work experience, or minimum 6 years' work experience with Associate's degree) in Computer Science, Computer Engineering, or a related field.
• Minimum of 2 years of experience with Python and/or Node.js/TypeScript building production backend services or platform tooling.
• Minimum of 1 year of experience building or integrating with AI/LLM systems, agent frameworks, or AI developer tooling.
• Hands-on experience with async Python frameworks (FastAPI, asyncio), containerisation and Kubernetes, event-streaming protocols (WebSocket, SSE, gRPC), and vector/relational databases.
• Familiarity with AI agent protocols (MCP, ACP, A2A), OpenTelemetry instrumentation, and modern AI framework ecosystems (LangGraph, OpenAI Agents SDK, Anthropic Claude SDK).

Qualifications

• Master's or PhD in Computer Science, Computer Engineering, or a related field is a plus but not required.

Skills

• Software engineering skills, particularly in Python and Node.js/TypeScript.
• Experience with distributed systems, AI infrastructure, and developer experience.
• Experience with agent orchestration frameworks, inference serving infrastructure, sandboxed execution environments, and multi-tenant platform engineering.
• Experience with async Python frameworks, containerisation, Kubernetes, event-streaming protocols, and vector/relational databases.
• Experience with AI agent protocols, OpenTelemetry instrumentation, and modern AI framework ecosystems.

Benefits

Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below.

Pay

Annual Salary Range: California $73,800 to $220,400 Cleveland $68,300 to $176,300 Colorado $73,800 to $190,400 District of Columbia $78,500 to $202,700 Illinois $68,300 to $190,400 Maryland $73,800 to $190,400 Massachusetts $73,800 to $202,700 Minnesota $73,800 to $190,400 New York $68,300 to $220,400 New Jersey $78,500 to $220,400 Washington $80,200 to $202,700

Schedule

This role requires working onsite in Mountain View, CA. Applicants must be local to Mountain View area or willing to relocate prior to joining.