Technical Delivery Lead - Applications, Google Cloud

About the role

You're the person the client trusts to make it happen. As a Technical Delivery Lead, you own delivery from initial solution shaping through go-live. You design the execution approach for data and AI engagements, lead the implementation, and ensure the final product fundamentally upgrades how the client leverages data and intelligent automation. You are supported by a dedicated offshore engineering team—you set the strategic direction, and they build alongside you. You are the single point of accountability for what ships.

Responsibilities

• Own the delivery. End-to-end. Scope, timeline, team structure, quality, outcome. You're the single point of accountability the client relies on.
• Design how it gets delivered. Shape the delivery approach for application modernization engagements, define the migration waves, structure the team across workstreams, set the release cadence, and sequence the work to minimize risk and maximize velocity.
• Partner with solution engineers who own the technical architecture; you own how it gets built, tested, and shipped.
• Provide technical advisory across the engagement.

Requirements

• Minimum 7 years in hands-on, client-facing technology roles — you've built and delivered, not just managed.
• Minimum 5 years architecting and delivering on Google Cloud Platform, with deep expertise in application development, modernization, and cloud-native engineering.
• You've independently owned client engagements from technical design through go-live.
• Deep hands-on proficiency with GKE, Apigee, CI/CD pipelines, and modern application architecture — you can design a microservices platform, review a PR, and debug a broken deployment.
• Strong understanding of software engineering principles — clean code, testing strategies, observability, and operational excellence.
• Strong in both technical leadership and delivery management — architecture, scope, risk, stakeholders.

Qualifications

• Advanced proficiency in BigQuery, Dataflow, Pub/Sub, Cloud SQL, Spanner, and Bigtable for data migration, pipeline design, data quality governance, and lakehouse architecture modernizations.
• Hands-on experience executing semantic modeling, Looker deployments, connected sheets integrations, and real-time operational dashboards.
• Core understanding of Vertex AI, Gemini models, AutoML, custom model training, and building production-grade MLOps deployment pipelines.
• Working knowledge of modern agent orchestration patterns, including tool use, grounding mechanisms, Retrieval-Augmented Generation (RAG), Agent Development Kit (ADK), A2A protocol, and Model Context Protocol (MCP).

Skills & Technologies

• Cloud-Native Architecture
• Microservices, event-driven design, 12-factor app patterns, serverless (Cloud Run, Cloud Functions)
• Containers & Orchestration
• Google Kubernetes Engine (GKE), Docker, Anthos, service mesh (Istio)
• API & Integration
• Apigee, API gateway design, event-driven integrations, Pub/Sub
• DevOps & CI/CD
• Cloud Build, Jenkins, GitHub Actions, GitOps, automated testing, release management
• Application Modernization
• Migration assessment, re-platforming, re-architecting, strangler-fig patterns, legacy decomposition
• AI-Augmented Development
• Gemini Code Assist for code generation, review, and developer productivity

What Sets You Apart

• Google Cloud Certifications: Active Professional Google Cloud certifications (specifically Professional Data Engineer, Professional Machine Learning Engineer, or Professional Cloud Architect).
• Advanced Agent Deployments: Documented hands-on deployment experience utilizing the Gemini Enterprise Agent Platform to automate complex cross-functional business workflows.
• Production AI Experience: A proven history of scaling live, production-grade ML/AI systems out of the prototyping stage.
• Cross-Functional Ecosystem Exposure: Secondary familiarity with adjacent Google domains, such as Google Enterprise for Customer Experience (GECX/CCAI), Google Security Operations, or Gemini Enterprise for Workspace.

Prior Experience

• Minimum 7 years in hands-on, client-facing technology roles — you've built and delivered, not just managed.
• Minimum 5 years architecting and delivering on Google Cloud Platform, with deep expertise in application development, modernization, and cloud-native engineering.
• You've independently owned client engagements from technical design through go-live.
• Deep hands-on proficiency with GKE, Apigee, CI/CD pipelines, and modern application architecture — you can design a microservices platform, review a PR, and debug a broken deployment.
• Strong understanding of software engineering principles — clean code, testing strategies, observability, and operational excellence.
• Strong in both technical leadership and delivery management — architecture, scope, risk, stakeholders.

Preferred Experience

• Bachelor's in CS, Engineering, or related field — or 12 years equivalent experience.
• Google Cloud Professional certifications (Cloud Architect, Cloud Developer)
• Documented hands-on deployment experience utilizing the Gemini Code Assist for AI-augmented development workflows
• Proven history of scaling live, production-grade ML/AI systems out of the prototyping stage.
• Secondary familiarity with adjacent Google domains, such as Google Enterprise for Customer Experience (GECX/CCAI), Google Security Operations, or Gemini Enterprise for Workspace.

Travel

Travel may be required for this role. The amount of travel will vary from 25% to 100% depending on business need and client requirements.

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.