Lead AI Solution Architect

Position Objective

Lead the design and delivery of enterprise-grade AI and Generative AI solutions using Google Cloud and Vertex AI capabilities. Translate customer and business objectives into secure, scalable architectures; guide engineering teams through implementation; and ensure that research and proof-of-concept work becomes reliable, supportable production service.

Key Responsibilities

• Own end-to-end architecture for AI, GenAI, data, integration, and cloud-native solutions in Google Engineer business engagements.

• Translate business requirements and customer priorities into reference architectures, solution blueprints, estimates, delivery roadmaps, and technical decisions.

• Design production-ready LLM, RAG, agent, multimodal, document intelligence, and workflow automation solutions.

• Apply Google Cloud and Vertex AI services such as Gemini, BigQuery, Cloud Storage, Cloud Run, GKE, Pub/Sub, Dataflow, Vertex AI Pipelines, Model Registry, IAM, and observability services where appropriate.

• Define non-functional requirements for security, privacy, reliability, scalability, latency, maintainability, and cost efficiency.

• Lead architecture reviews, design reviews, technical proposals, code-quality governance, and production-readiness assessments.

• Guide the transition from research or PoC to production, including evaluation, guardrails, CI/CD, monitoring, incident readiness, and operational ownership.

• Mentor AI, cloud, and software engineers; facilitate technical decisions; and remove engineering blockers across distributed teams.

• Communicate technical trade-offs clearly to customers, delivery leaders, and non-technical stakeholders.

• Identify delivery risks, dependencies, and opportunities for reusable platforms, accelerators, and engineering standards.

Essential Qualifications

Successful candidates will demonstrate the following combination of education, experience, and technical capability:

• Bachelor’s degree or higher in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline.

• At least 8 years of professional experience in solution architecture, software engineering, AI/ML engineering, cloud architecture, or a closely related field, including significant technical leadership experience.

• Proven hands-on delivery of enterprise AI or Generative AI solutions from architecture and PoC through production operation.

• Strong Google Cloud experience, including practical use of Vertex AI and related services; working knowledge of Gemini, BigQuery, Cloud Run or GKE, IAM, networking, data services, and observability.

• Deep understanding of LLM application patterns, RAG, embeddings, vector search, agent orchestration, prompt engineering, model evaluation, safety controls, and AI governance.

• Strong software engineering fundamentals in Python and API or microservice design, with the ability to review implementation quality and operational readiness.

• Experience leading customer-facing technical discussions, architecture workshops, solution proposals, and delivery decisions in an international environment.

• Professional English communication skills and the ability to collaborate effectively with distributed engineering and stakeholder groups.

Preferred Qualifications

• Google Cloud Professional Cloud Architect, Professional Machine Learning Engineer, or equivalent certification.

• Experience with Google Agent Development Kit, TensorFlow, JAX, LangChain, LangGraph, or comparable frameworks.

• Experience with responsible AI, security architecture, data governance, FinOps, and regulated enterprise environments.

• English language proficiency or experience working with APAC-based stakeholders.

Success Measures

• Production solutions meet agreed reliability, security, quality, latency, and cost targets.

• Architecture decisions are documented, reusable, and aligned with Google Cloud engineering standards.

• PoCs are converted into viable production services with clear operational ownership.

• Customer and delivery stakeholders receive timely, evidence-based technical guidance.

• Engineering capability improves through mentoring, reusable assets, and consistent review practices.

Benefits and Working Conditions

• Competitive compensation package, with 100% salary during probation, subject to company policy and the employment offer.

• Full social insurance contribution based on the applicable salary basis.

• Annual performance bonus and salary review in line with company policy.

• Premium healthcare insurance for employees and eligible family members from probation, subject to policy.

• Annual health check-up and access to company-sponsored training, professional courses, and certification examinations.

• Paid leave and public holidays in accordance with Vietnamese regulations and NTT DATA Vietnam policy.

• Hybrid working model, flexible start time with manager approval, and a global environment with international collaboration.

• Clear career development opportunities in cloud engineering, AI delivery, solution architecture, and technical leadership.

Work Schedule

• Monday to Friday, 08:00–12:00 and 13:00–17:00.

• Flexible start time between 07:45 and 09:00 with manager approval.

Work Locations

• Hanoi: HITC Building, 239 Xuan Thuy Street, Hanoi, Vietnam.

• Ho Chi Minh City: Opal Office Tower, 92 Nguyen Huu Canh Street, Ho Chi Minh City, Vietnam.