Forward Deployed Engineer, UIUX (Contract)

Argyll Scott; Singapore; Sur place; SGD 120 000 - 180 000; Plein temps

Résumé du poste

Argyll Scott is seeking an experienced Forward Deployed Engineer to work with business units in Singapore on a 12-month contract. You will deliver AI and automation solutions, prototype rapidly, and hand over to production teams with strong governance and observability.

You will design AI workflows, build backend services and integrations, and collaborate with users to shape outcomes. A production-ready mindset and 5+ years of software experience are essential.

Qualifications

• 5+ years of software engineering, from discovery to production support.
• Backend engineering with Python and API design.
• Experience with data pipelines, relational databases, and data modeling.
• Hands-on with LLM-enabled apps, RAG, and tool-calling workflows.
• Experience deploying cloud-native apps on AWS, Bedrock or similar.
• Strong communication to collaborate with non-technical users.
• Comfortable in ambiguous environments and driving adoption.

Responsabilités

• Embed with business units to understand workflows and translate needs into use cases.
• Build prototypes quickly, validate with users, and iterate toward production.
• Design reliable AI workflows and agents using Python-based tools.
• Develop backend services, APIs, integrations, and lightweight UIs as needed.
• Ingest, transform, and retrieve data across enterprise systems and APIs.
• Design relational data models and ensure data quality and access control.
• Define evaluation datasets, test quality, latency, and observability.
• Apply secure engineering practices and governance aligned to risk.

Connaissances

5+ years experience

Backend engineering

Stakeholder comms

Delivery mindset

Outils

Python

FastAPI

PostgreSQL

LangGraph

LangChain

LlamaIndex

n8n

Flowise

AWS

Bedrock

OpenSearch

Description du poste

Forward Deployed Engineer, UIUX (Contract)

Location: Singapore

Contract Type: 12 months contract (Extendable & Convertible)

Company/Role Overview

We are looking for an experienced, product-minded Engineer to work directly with business units and use our established enterprise GenAI platform to deliver high-impact AI and automation solutions. In this forward-deployed role, you will partner closely with business users to understand their workflows, translate often ambiguous needs into well-scoped solutions, and own delivery from discovery and rapid prototyping through production rollout, adoption, and handover.

Key Responsibilities

• Business Discovery & Solution Shaping: Embed with business units to understand operational workflows, pain points, data, constraints, and intended outcomes. Facilitate discovery sessions, challenge assumptions, and translate needs into prioritised use cases, user stories, solution designs, and measurable success criteria.
• Rapid Prototyping & Iterative Delivery: Build working prototypes quickly, validate them with users, and iterate based on evidence. Balance speed with maintainable engineering and take viable solutions through production deployment.
• Agentic Workflow Engineering: Design and implement reliable AI workflows and agents using Python-based frameworks and orchestration tools such as LangGraph, LangChain, n8n, or equivalent technologies. Combine deterministic steps, LLM reasoning, tool calling, state management, human approvals, and exception handling as appropriate.
• Custom Application Development: Build fit-for-purpose applications around business use cases, including backend services, APIs, integrations, authentication, workflow logic, and lightweight user interfaces where needed.
• Data & Knowledge Integration: Design robust data ingestion, transformation, and retrieval pipelines. Integrate enterprise systems, databases, document repositories, APIs, and search or vector services while maintaining data quality, lineage, and access controls.
• Backend & Database Engineering: Develop secure, scalable backend services and APIs, and design relational data models using technologies such as Python, FastAPI, and PostgreSQL. Diagnose complex integration, performance, and state-management issues.
• AI Quality, Evaluation & Observability: Define evaluation datasets and acceptance criteria; test solution quality, reliability, latency, cost, and tool-call success; implement tracing and monitoring; and continuously improve prompts, retrieval, workflows, and safeguards.
• Security, Governance & Responsible AI: Apply secure engineering practices, least-privilege access, data protection, prompt-injection defences, output controls, auditability, and human oversight in line with government policies and the risk profile of each use case.
• Deployment, Adoption & Handover: Own production readiness, testing, rollout, documentation, user enablement, support, and knowledge transfer. Track adoption and business outcomes and incorporate field learnings into reusable patterns and improvements to the core platform.

Job Requirements

Essential Requirements

• Experience: 5+ years of software engineering experience, including demonstrated ownership of production applications from ambiguous requirements through deployment and support.
• Backend Engineering: Strong proficiency in Python or another modern backend language, API design, asynchronous processing, integration patterns, testing, debugging, and system architecture.
• Database & Data Engineering: Strong experience with relational databases, preferably PostgreSQL, including data modelling and query optimisation; practical knowledge of data pipelines, search, and vector retrieval is also required.
• GenAI & Agentic Systems: Hands-on experience building LLM-enabled applications, RAG solutions, tool-calling agents, or automated workflows using frameworks such as LangGraph, LangChain, LlamaIndex, n8n, or equivalent.
• Cloud & Production Delivery: Practical experience deploying and operating cloud-native applications. Familiarity with AWS and services such as Bedrock and OpenSearch is preferred, although equivalent Azure or GCP experience is acceptable.
• Stakeholder Partnership: Strong communication and facilitation skills, with the ability to work directly with non-technical users, clarify business needs, explain trade-offs, manage expectations, and drive adoption.
• Delivery Mindset: Comfortable working in ambiguous environments, learning unfamiliar business domains quickly, and balancing user value, delivery speed, security, reliability, and maintainability.

Additional Attributes

• Forward Deployment: Experience in consulting delivery, solutions engineering, internal product delivery, or another role involving direct collaboration with users and end-to-end implementation.
• Workflow Automation: Experience with visual workflow builders such as n8n or Flowise, including custom nodes, integrations, credential handling, and operational support.
• Evaluation & Observability: Experience with LLM evaluation, tracing, observability, red-teaming, or quality assurance tools and methods.
• Regulated Environments: Experience delivering applications subject to stringent data privacy, cybersecurity, accessibility, or government requirements, including IM8 policies.