AI Solutions Architect (AI Operations & Analytics)
Summary
Design and deploy AI systems that automate market analysis and decision-making using LLMs, RAG, and agentic workflows for a fintech team in Singapore.
We are looking for a pragmatic and results-driven
AI Solutions Architect
to lead the integration of Generative AI and advanced automation into our department’s workflows. Unlike a research-heavy role, this position focuses on the
Application Layer : building high-impact tools for intelligent market analysis, automating complex decision-making processes, and architecting the roadmap for our AI evolution.
You will be the bridge between cutting-edge LLM capabilities and practical business efficiency, starting as a key individual contributor with the potential to shape our future AI strategy.
Key Responsibilities
Intelligent Analysis Systems:
Design and deploy
RAG (Retrieval-Augmented Generation)
frameworks to transform internal reports, market news, and unstructured data into actionable insights for the trading and risk teams.
Workflow Automation:
Develop
AI Agents
and autonomous workflows to streamline repetitive high-value tasks, moving from manual processes to "human-in-the-loop" automated systems.
AI Application Development:
Build and maintain the middleware/orchestration layer (using frameworks like LangChain or LlamaIndex) to connect LLMs with our internal databases and APIs.
Model Optimization:
Evaluate and implement fine-tuning strategies for open-source models (e.g., Llama 3, DeepSeek) when off-the-shelf APIs do not meet specific accuracy or privacy requirements.
Strategic Roadmap:
Develop a technical AI roadmap that identifies high-ROI opportunities within the department and outlines the transition from pilot projects to scalable production systems.
Technical Qualifications
Core AI Engineering:
3+ years of experience in AI application development with a strong focus on
Large Language Models (LLMs)
and
Natural Language Processing (NLP) .
The Orchestration Stack:
Proficiency in
Python
and deep experience with orchestration frameworks such as
LangChain, LlamaIndex, or Haystack .
Automation Mastery:
Proven track record of building
Agentic Workflows
(e.g., AutoGPT, CrewAI) and integrating them into production environments.
Data & Infrastructure:
Familiarity with
Vector Databases
(e.g., Pinecone, Milvus, Weaviate) and experience handling API integrations (RESTful, GraphQL).
Model Layer (Bonus):
Practical experience in
Parameter-Efficient Fine-Tuning (PEFT/LoRA)
and local model deployment (Ollama, vLLM).
Preferred Attributes
Strategic Thinking:
Ability to distinguish between AI "hype" and actual business value, prioritizing projects based on feasibility and impact.
Collaborative Mindset:
Effective at working across teams (IT, Risk, Trading) to understand domain-specific pain points.
Self-Starter:
Comfortable working independently to build prototypes while maintaining a vision for long-term scalability.
Why Join Us? This is a unique opportunity to build an AI ecosystem from the ground up in a high-stakes, data-rich environment. You will have the autonomy to choose the best tools for the job and see your work directly impact the efficiency of our global operations.
AI Solutions Architect
to lead the integration of Generative AI and advanced automation into our department’s workflows. Unlike a research-heavy role, this position focuses on the
Application Layer : building high-impact tools for intelligent market analysis, automating complex decision-making processes, and architecting the roadmap for our AI evolution.
You will be the bridge between cutting-edge LLM capabilities and practical business efficiency, starting as a key individual contributor with the potential to shape our future AI strategy.
Key Responsibilities
Intelligent Analysis Systems:
Design and deploy
RAG (Retrieval-Augmented Generation)
frameworks to transform internal reports, market news, and unstructured data into actionable insights for the trading and risk teams.
Workflow Automation:
Develop
AI Agents
and autonomous workflows to streamline repetitive high-value tasks, moving from manual processes to "human-in-the-loop" automated systems.
AI Application Development:
Build and maintain the middleware/orchestration layer (using frameworks like LangChain or LlamaIndex) to connect LLMs with our internal databases and APIs.
Model Optimization:
Evaluate and implement fine-tuning strategies for open-source models (e.g., Llama 3, DeepSeek) when off-the-shelf APIs do not meet specific accuracy or privacy requirements.
Strategic Roadmap:
Develop a technical AI roadmap that identifies high-ROI opportunities within the department and outlines the transition from pilot projects to scalable production systems.
Technical Qualifications
Core AI Engineering:
3+ years of experience in AI application development with a strong focus on
Large Language Models (LLMs)
and
Natural Language Processing (NLP) .
The Orchestration Stack:
Proficiency in
Python
and deep experience with orchestration frameworks such as
LangChain, LlamaIndex, or Haystack .
Automation Mastery:
Proven track record of building
Agentic Workflows
(e.g., AutoGPT, CrewAI) and integrating them into production environments.
Data & Infrastructure:
Familiarity with
Vector Databases
(e.g., Pinecone, Milvus, Weaviate) and experience handling API integrations (RESTful, GraphQL).
Model Layer (Bonus):
Practical experience in
Parameter-Efficient Fine-Tuning (PEFT/LoRA)
and local model deployment (Ollama, vLLM).
Preferred Attributes
Strategic Thinking:
Ability to distinguish between AI "hype" and actual business value, prioritizing projects based on feasibility and impact.
Collaborative Mindset:
Effective at working across teams (IT, Risk, Trading) to understand domain-specific pain points.
Self-Starter:
Comfortable working independently to build prototypes while maintaining a vision for long-term scalability.
Why Join Us? This is a unique opportunity to build an AI ecosystem from the ground up in a high-stakes, data-rich environment. You will have the autonomy to choose the best tools for the job and see your work directly impact the efficiency of our global operations.