Principal Solutions Architect (Consultancy, AI-Native SDLC & Agentic Systems)

JustOneGalaxy Recruitment Limited; Hong Kong Island; On-site; HKD 900,000 - 1,300,000; Full time

Job summary

JustOneGalaxy Recruitment Limited seeks a Principal Solutions Architect to join its AI-Centric Delivery practice. The role focuses on AI-native SDLC, agentic systems, and enterprise architectures that embed AI as a core engineering capability.

The position blends strategic architecture with hands-on delivery, building prototypes and guiding client teams through security, integration, and governance requirements. Cantonese and English fluency are required.

Qualifications

• Senior-level software/solutions architect experience in enterprise contexts.
• Hands-on Generative AI / LLM implementation and tooling.
• Experience in agentic workflows, tool usage, memory management, and human-in-the-loop controls.
• Solid knowledge of cloud platforms (AWS/Azure/GCP) and API-driven architectures.

Responsibilities

• Design and validate AI-native, agentic SDLC architectures for enterprise use.
• Lead end-to-end enterprise architecture design with security, integration, and observability in mind.
• Deliver prototypes on tight timelines and guide engineering teams through implementation.
• Advise clients on cost, latency, risk, and governance considerations.
• Collaborate with product owners and engineering leads to align with business goals.

Skills

Architectural

LLM Expertise

Agentic Workflows

Cloud & Microservices

API Design

Bilingual

Tools

LangChain

LlamaIndex

Hugging Face

CrewAI

AutoGen

LangGraph

Job description

Principal Solutions Architect (Consultancy, AI-Native SDLC & Agentic Systems)

(Principal) Solutions Architect (Consultancy; AI-Native SDLC & Agentic Systems; Cantonese needed)

A global provider of digital platform engineering and software development services is looking for a Solutions Architect to join its AI-Centric Delivery practice. This execution-oriented position focuses on designing and implementing enterprise solution architectures where AI functions as a core engineering capability. The role combines strategic architecture with hands-on application to construct AI-augmented software development lifecycle (SDLC) workflows, agentic systems, and LLM-powered delivery tooling.

Key Responsibilities

AI-SDLC Integration: Design, build, and validate developer agents and multi-agent orchestration workflows to boost automation and throughput across version control, CI/CD, testing, code review, and documentation.

Architecture & Strategy: Lead the end-to-end design of enterprise architectures integrating agentic systems, LLM workflows, and RAG pipelines while advising client stakeholders on business alignment, latency, cost, observability, and risk.

Hands-on Execution: Deliver functional prototypes on short timelines to demonstrate AI-native value and partner with engineering teams during implementation to define technical direction.

Governance & Governance Alignment: Collaborate with product owners, engineering leads, and enterprise architecture teams to ensure solutions satisfy security, integration, and compliance requirements.

Required Qualifications

Architectural & Engineering Background: Proven experience as a senior software engineer or solutions architect delivering complex, enterprise-scale projects.

Generative AI & LLM Expertise: Hands-on experience with major foundation models (OpenAI GPT, Anthropic Claude, Google Gemini), prompt engineering, model selection, context management, and production performance/cost optimization.

Agentic Workflows: Background in designing agentic systems incorporating tool usage, memory management, multi-step reasoning, and human-in-the-loop controls.

Enterprise Architecture Core: Solid foundation in cloud platforms (AWS, Azure, or GCP), microservices, API design, data architecture, and integration patterns.

Prototyping & Communication: Ability to communicate design decisions clearly and validate architectural choices through functional prototypes.

Preferred Experience

Frameworks & Orchestration: Familiarity with orchestration tools (CrewAI, AutoGen, LangGraph) and AI development frameworks (LangChain, LlamaIndex, Hugging Face).

Observability & Guardrails: Knowledge of LLM evaluation, guardrails, and monitoring tools like LangSmith or Arize.

Data & Vector Technologies: Exposure to vector databases (FAISS, Pinecone, Qdrant, Chroma, Weaviate) and broader integration platforms (event-driven architecture, data mesh).

Tooling Scale & Languages: Experience deploying enterprise-wide AI code generation tools; fluency in Cantonese and English.