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Lead AI Engineer

Exclusive opportunity

Onsite

Lead AI Engineer

LTM

Lead AI Engineer

Skills

Google Cloud PlatformSQL QueriesDeep LearningTypescriptPythonGolangJavaC#PyTorchTensorFlowMachine LearningAIGitHubFastAPI

20 days ago

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Important information


Contract type:

Permanent

Location:

Australia

Work mode:

Onsite

Published on:

6 October 2026

What they need


About the Role

As a Lead AI Engineer, you will lead the design and implementation of multi-agent AI architectures, working closely with customers, software engineers, data scientists, and domain experts to deliver scalable, production-grade AI solutions. You will be responsible for technical design, architecture decisions, coding standards, and the successful implementation of complex AI systems.

Key Responsibilities

  • Lead the design, development, and implementation of enterprise-scale multi-agent AI architectures.
  • Translate complex business requirements into scalable AI solutions.
  • Develop modular, maintainable, and high-quality code following software engineering best practices.
  • Define and communicate architecture decisions and technical design considerations.
  • Collaborate with cross-functional teams including customers, engineers, data scientists, and business stakeholders.
  • Document solution architecture, algorithms, workflows, and implementation details.
  • Design AI systems with a focus on performance, scalability, security, cost optimization, and accuracy.

Must-Have Skills

  • Strong hands-on programming expertise in Python .
  • Experience with PyTorch and/or TensorFlow .
  • Strong knowledge and hands-on experience with Google Cloud Platform (GCP) .
  • Experience building applications using Vertex AI , including:
  • Agent Builder
  • Search
  • Conversational Agents
  • Strong expertise in Generative AI, Machine Learning, Deep Learning, and Agentic AI patterns .
  • Experience designing and implementing multi-agent systems .
  • Hands-on experience with:
  • LangChain
  • LangGraph
  • LlamaIndex
  • LangSmith
  • Ragas
  • Experience building advanced Retrieval Augmented Generation (RAG) solutions, including Graph-based RAG.
  • Expertise in implementing AI guardrails, responsible AI controls, and hallucination mitigation strategies.
  • Experience in AI testing, evaluation frameworks (EvalOps), and solution optimization.
  • Experience designing AI solutions for enterprise-scale deployment with performance, cost, and accuracy considerations.

Preferred Technical Experience

  • Agent Development Kit (ADK)
  • Vertex AI Extensions
  • FastAPI
  • Pydantic
  • Spanner Graph / GQL
  • Chain-of-Thought (CoT) Engineering
  • Agentic Observability
  • Semantic Entity Mapping
  • Tool & Plugin Engineering
  • API development and integrations

Nice to Have

  • Gradio or Streamlit
  • BigQuery, Dataflow, Cloud SQL
  • Dialogflow CX or Gemini Enterprise CX
  • GitHub, CI/CD, DevOps
  • Cloud Run, GKE
  • Cloud Build
  • Pub/Sub
  • Cloud Tasks
  • Artifact Registry
  • Secret Manager

Software Engineering & Architecture

  • Clean Architecture and SOLID principles
  • 12-Factor Application design
  • OAuth2/OIDC, IAM, IAP
  • Secure software development practices
  • Asynchronous programming and distributed workflows
  • Application security and data privacy controls
  • Experience with another programming language such as Java, Go, C#, or TypeScript in addition to Python

LTM is proud to be an equal opportunity employer. We are committed to equal employment opportunity regardless of race, ethnicity, nationality, gender, gender-identity, gender expression, language, age, sexual orientation, religion, marital status, veteran status, socio-economic status, disability or any other characteristic protected by applicable law.

▶️ Watch the video: https://www.youtube.com/watch?v=5tTtIX92ipY

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