全职 AI Solution Architect 工作, 薪水, Elliott Moss Consulting 公司招聘中 - Ricebowl

We are looking for an experienced Solution / Technical Architect to provide technical leadership across strategic cloud, data, analytics, and AI-enabled initiatives. The role will own end-to-end solution architecture covering applications, data, integration, cloud platforms, security, observability, and operations, while supporting PoCs, MVPs, tenders, and customer-facing opportunities.

Key Responsibilities

• Translate business and customer requirements into secure, scalable, and practical solution architectures.
• Own end-to-end architecture across application, data, integration, cloud, security, observability, and operations.
• Lead solution shaping for new programmes, PoCs, MVPs, tenders, and customer opportunities.
• Assess feasibility, technical risks, dependencies, assumptions, estimates, and technology trade-offs.
• Design batch and streaming data pipelines, APIs, event-driven integrations, data warehouses/lakehouses, analytics, and reporting solutions.
• Design and guide AI/GenAI solutions, including RAG, agentic AI, model integration, evaluation, guardrails, observability, and LLMOps.
• Lead hands-on PoCs/MVPs to validate architecture and technology decisions before production implementation.
• Recommend platforms and technologies based on cost, performance, security, scalability, maintainability, and operational requirements.
• Embed security and privacy by design, including IAM, OAuth2/OIDC, secrets management, data protection, classification, compliance, and auditability.
• Guide engineering teams through technical designs, implementation reviews, code/design reviews, backlog elaboration, and technical governance.
• Develop architecture documentation, solution diagrams, reusable patterns, reference implementations, and technical decision records.
• Work closely with technical and non-technical stakeholders and communicate architecture options, risks, dependencies, and recommendations clearly.
• Manage multiple opportunities and maintain strong client relationships and expectations.

Must-Have Qualifications

• Bachelor’s degree or equivalent.
• 12+ years of enterprise application or data platform architecture experience.
• At least 2 years of production-grade GenAI architecture experience.
• Strong exposure to Data Science and Machine Learning.
• Minimum 3 years of hands-on experience in each of AWS, GCP, and Azure.
• At least 1 year of hands-on experience with GenAI / Agentic AI technologies.
• Strong experience with containers/Kubernetes or serverless and IaC tools such as Terraform or CloudFormation.
• Hands-on experience with at least one Agent/RAG framework, such as:
• LangChain / LangGraph
• DSPy
• OpenAI / Anthropic tool use
• Databricks Agents
• Equivalent technologies
• Practical LLMOps experience covering evaluation, tracing/observability, prompt/version management, and CI/CD for AI solutions.
• Strong lakehouse and data engineering knowledge, including Delta/Iceberg/Hudi, streaming technologies such as Kafka/Kinesis/Pub/Sub, and vector databases/search.
• Strong API and integration architecture experience across REST, gRPC, GraphQL, APIs, and event-driven architectures.
• Strong understanding of OAuth2/OIDC, JWT, mTLS, secrets management, data governance, lineage, access policies, and AI guardrails.
• Good understanding of mobile and web application architectures.
• Strong communication, stakeholder management, problem-solving, and client-facing skills.
• Ability to manage multiple opportunities and work effectively across organisational boundaries.

Required Certifications

• AWS / Azure / Google AI Certification
• AWS / Azure / Google Data Science Certification
• AWS / Azure / Google Solution Architect Certification
• TOGAF 9 – The Open Group
• Any other equivalent industry-standard architecture certification