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We are looking for an experienced Assistant Manager, AI Engineering for one of our global shipping clients. He/she will serve as the technical authority for the development of AI agents and AI-powered applications across the company and will be responsible for defining the platforms, architectures, frameworks and engineering standards that enable teams to build reliable, scalable and governed AI solutions.
The ideal candidate would have relevant work experience in acting as an embedded AI consultant to the organisation, advising on agent design, platform strategy, knowledge base architecture, model selection and integration patterns. The role requires strong technical depth, architectural judgement and the ability to influence engineering practices across teams.
Key Responsibilities
Requirements
We regret that only shortlisted candidates will be notified. Thank you for your understanding!
Job ID: 149416589
Skills:
model selection , Iso 27001, OPA, LLMOps tooling, NIST AI RMF, agent development tools, AI engineering standards, Responsible AI frameworks, LangGraph, technical frameworks, retrieval architecture, model evaluation, agent design, OpenTelemetry, Langfuse, Pydantic, integration patterns, agent mesh concepts, LangChain, agent collaboration patterns, multi-agent architecture, Model Context Protocol, discovery mechanisms, guardrail frameworks, reference architectures, Semantic Kernel, AI governance
Skills:
Machine Learning, ML Ops, DevOps practices, generative AI, cloud-based AI platforms, modern software engineering practices, enterprise AI deployment frameworks, AI technologies
Skills:
OPA, LangChain, AI platforms, guardrail frameworks, vector databases, agent frameworks, Semantic Kernel, prompt engineering, LangGraph, retrieval augmented generation, model evaluation, OpenTelemetry, LLM Ops tooling, Langfuse, Pydantic, LLM application architecture
Skills:
Iso 27001, LangChain, OPA, agent collaboration patterns, NIST AI RMF, AI engineering standards, guardrail frameworks, multi agent architecture, Responsible AI frameworks, prompt engineering, Semantic Kernel, LangGraph, OpenTelemetry, LLM Ops tooling, Langfuse, Pydantic, LLM provider selection
Skills:
Apis, system integration, Python, Airflow, deployment practices, RAG embeddings, data pipelines, n8n, vector databases, make, Zapier, knowledge retrieval, workflow automation tools, LLM workflows, AI agents, AI inference-layer design
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