ASSISTANT MANAGER, AI ENGINEERING

Upper Spring Consulting Pte Ltd; Singapore; Presencial; SGD 180.000 - 240.000; Jornada completa

Descripción de la vacante

Upper Spring Consulting Pte Ltd is seeking an experienced AI Engineering professional (Assistant Manager) to act as the technical authority on AI agent design and LLM-powered applications. You will define platforms, frameworks and standards, guiding builders across the organisation and ensuring governance and best practices.

You will lead the architecture for multi-agent collaboration, agent mesh, and knowledge base strategies, while steering LLM ops tooling, model selection, and provider

Formación

• More than 8 years of engineering experience in AI/ML/LLM roles.
• Experience selecting, integrating, and governing AI platforms or LLM Ops tooling at enterprise scale.
• Strong understanding of LLM application architecture, including retrieval augmented generation, vector databases, and agent frameworks.
• Excellent written communication skills for standards, decision records, and reference patterns.
• Experience in enterprise knowledge bases and governance frameworks (ISO 27001, NIST AI RMF, model risk).
• Delivery experience in shipping or operations in logistics or supply chain sectors.

Responsabilidades

• Act as embedded AI technical authority on agent design, model selection, retrieval architecture, and integration patterns.
• Author and maintain AI engineering standards, frameworks, and reusable components.
• Design multi-agent architecture, including collaboration patterns and agent mesh.
• Lead the enterprise knowledge base design and rollout from architecture decisions to retrieval patterns.
• Define and govern the AI platform estate, including tools, LLM ops, and provider selection.

Conocimientos

Leadership & influence

Technical writing

Stakeholder management

Cross-team collaboration

Herramientas

LangGraph

LangChain

Semantic Kernel

Pydantic

OpenTelemetry

Langfuse

OPA

MCP

Descripción del empleo

We are representing our client in the marine sector to look for an experience AI practitioner to take on the role of AI Engineering (Assistant Manager) asthe technical authority for how AI agents and AI powered applications are built at the company. You will define the platforms, frameworks, standards, and architecture that builders develop with, and act as the embedded AI consultant across the organisation. The scope spans platform strategy, multi agent design, knowledge base architecture, governance partnership, and technical influence.

Responsibilities

• Act as the embedded AI technical authority on agent design, model selection, and retrieval architecture and integration patterns.
• Author and maintain the company's AI engineering standards, frameworks, and reusable components that builders develop with.
• Design the multi agent architecture, including agent collaboration patterns, the agent mesh, and discovery mechanisms.
• Lead the design and rollout of the enterprise knowledge base, from architecture decisions through to retrieval patterns.
• Define and govern the AI platform estate, including agent development tools, LLM Ops tooling, and LLM provider selection.

Requirements

• More than 8 years of engineering experience, including significant time in AI, ML, or LLM focused roles.
• Track record of selecting, integrating, and governing AI platforms or LLM Ops tooling at enterprise scale.
• Deep understanding of LLM application architecture, including retrieval augmented generation, vector databases, agent frameworks (LangGraph, LangChain, Semantic Kernel, or equivalent), and prompt engineering.
• Strong working knowledge of model evaluation, observability, and guardrail frameworks (e.g. Pydantic, OpenTelemetry, Langfuse, OPA or similar).
• Demonstrated ability to compare LLM providers and articulate tradeoffs across capability, cost, governance, and lock in.
• Excellent written communication skills. You will be writing standards, decision records, and reference patterns that other engineers rely on.
• Strong ability to influence without authority and earn technical credibility across multiple teams.
• Experience designing multi agent systems and agent orchestration patterns.
• Familiarity with the Model Context Protocol (MCP) and emerging agent interoperability standards.
• Experience across multiple enterprise LLM platforms and ecosystems, with the ability to compare and integrate them.
• Background in building or operating enterprise knowledge bases at scale.
• Exposure to AI governance and Responsible AI frameworks (ISO 27001, NIST AI RMF, model risk management).
• Experience in shipping, logistics, supply chain, or other operational industries.