Ai Solution Consultant

This role involves close collaboration with business leaders, product owners, and engineering teams to understand organizational needs and then leverage your expertise in **LLMs, multi-agent orchestration, graph reasoning, or anomaly detection**to develop tailored, production-ready solutions grounded in real-world context.

Providing hands-on consulting and technical expertise across multiple use cases — from customer support automation to fraud risk detection and AI content workflows — will be central to your role. You'll also work with platform and infrastructure teams to ensure AI solutions are robust, reproducible, and scalable.

**Key Responsibilities**

**Solution Architecting**
- Work with business and technical leads to manage and deliver successful implementations of AI-powered solutions across multiple verticals (e.g., GenAI copilots, fraud prevention pipelines, agent orchestration, content automation).
- Propose solution architectures and manage deployment strategies according to complex organizational requirements and best practices.
- Translate business objectives into actionable AI-powered use cases by gathering requirements, auditing data readiness, and designing integration flows for models, tools, and systems.
- Interact with internal stakeholders to manage project scope, priorities, deliverables, risks, and timelines for successful AI solution rollout.

**Solution Engineering**
- Write clean, efficient code while optimizing for performance, cost, and latency across cloud and hybrid environments.
- Continuously evaluate and improve the performance, scalability, and efficiency of deployed solutions by incorporating new techniques and tooling.

**Education & Enablement**
- Collaborate with internal platform, product, and data teams to feed insights and learnings into roadmap design and reusable asset creation.
- Package successful approaches and best practices into internal methodologies, templates, and frameworks for broader enablement.
- Share your expertise through workshops, internal training sessions, and documentation to scale AI capabilities across the organization.
- Stay up-to-date with the rapidly evolving GenAI and applied AI landscape, proactively tracking emerging technologies in fields like large language models, graph ML, or adversarial behavior modeling.

**Required Qualifications**

**Enterprise Application Development**

**AI/LLM Proficiency**
- Familiarity with foundation models across providers (OpenAI, Claude, Gemini, Qwen, Mistral, etc.) and open-source ecosystems.

**Programming & Infrastructure**
- Proficiency in at least one major programming language (Python, JavaScript, Java, or C#).
- Experience with Git-based version control and deployment frameworks using Docker, Kubernetes, or serverless tools.

**Cloud & AI Ecosystem**
- Experience deploying AI workloads on AWS, Azure, GCP, or Aliyun cloud platforms.
- Familiarity with modern AI frameworks and orchestration tools (e.g., LangChain, LlamaIndex, Haystack, LangGraph).

**Domain & Data Experience**
- **Strong foundation in one or more of the following applied AI domains**:

- **Anti-Fraud**:Behavioral modeling, risk scoring systems, graph-based fraud detection, or transaction anomaly detection.
- **Agent Systems**:LLM-powered autonomous agents, multi-turn interaction design, decision orchestration using tool/function calling.
- **Content & Growth Automation**:Scalable content generation, AI-driven SEO optimization, personalized growth strategies using data and model-driven insights.
- Understanding of data pipelines and experience with relational and non-relational databases (e.g., SQL, NoSQL, vector DBs).

**Soft Skills**
- Excellent communication and interpersonal skills to align cross-functional stakeholders.
- Strong analytical and problem-solving abilities to address ambiguous challenges and drive structured innovation.
- Demonstrated ability to engage, influence, and align with cross-functional business stakeholders across departments (e.g. operations, marketing, risk, product).
- Able to use Chinese and English as working language to work with chinese speaking stakeholders

**Preferred Qualifications**
- A background in **management consulting, strategy, or enterprise solution delivery**is strongly preferred, reflecting the ability to synthesize complex business needs into actionable AI initiatives.
- Experience in user-facing systems where latency, trust, and explainability are critical.