AI Solutions Architect (AI Operations & Analytics)

USER EXPERIENCE RESEARCHERS PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

USER EXPERIENCE RESEARCHERS PTE. LTD. is seeking an AI Solutions Architect to drive the integration of Generative AI into workflow tools at the application layer. You will build high-impact market-analysis tools, automate complex decision processes, and design the AI evolution roadmap.

You will bridge cutting-edge LLM capabilities with business efficiency, starting as a key individual contributor with potential to shape the firm’s AI strategy.

Qualifications

• 3+ years of AI application development with a strong focus on LLMs and NLP.
• Proficiency in Python and orchestration frameworks (LangChain, LlamaIndex, Haystack).
• Experience building Agentic Workflows and integrating them into production environments.
• Familiarity with Vector Databases (Pinecone, Milvus, Weaviate) and API integrations (REST/GraphQL).
• Practical experience with PEFT/LoRA and local model deployment (Ollama, vLLM).

Responsibilities

• Design and deploy RAG frameworks to transform internal reports, market news, and unstructured data into actionable insights for trading and risk teams.
• Develop AI Agents and autonomous workflows to streamline repetitive high-value tasks with human-in-the-loop concepts.
• Build and maintain the middleware/orchestration layer to connect LLMs with internal databases and APIs.
• Evaluate and implement fine-tuning strategies for open-source models when off-the-shelf APIs do not meet requirements.
• Develop a technical AI roadmap identifying high-ROI opportunities and scalable production plans.

Skills

AI application development

LLMs

NLP

Strategic thinking

Self-starter

Tools

Python

LangChain

LlamaIndex

Haystack

Agentic Workflows

REST/GraphQL

Ollama

vLLM

PEFT/LoRA

Vector Databases

Job description

Role Overview

We are looking for a pragmatic and results-drivenAI Solutions Architectto lead the integration of Generative AI and advanced automation into our department's workflows. Unlike a research-heavy role, this position focuses on theApplication 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 deployRAG (Retrieval-Augmented Generation)frameworks to transform internal reports, market news, and unstructured data into actionable insights for the trading and risk teams.
• Workflow Automation:DevelopAI Agentsand 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 onLarge Language Models (LLMs)andNatural Language Processing (NLP).
• The Orchestration Stack:Proficiency inPythonand deep experience with orchestration frameworks such asLangChain, LlamaIndex, or Haystack.
• Automation Mastery:Proven track record of buildingAgentic Workflows(e.g., AutoGPT, CrewAI) and integrating them into production environments.
• Data & Infrastructure:Familiarity withVector Databases(e.g., Pinecone, Milvus, Weaviate) and experience handling API integrations (RESTful, GraphQL).
• Model Layer (Bonus):Practical experience inParameter-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.