Lead AI Engineer

LTM; Australia; On-site; AUD 180,000 - 260,000; Full time

Job summary

LTM in Australia is seeking a Lead AI Engineer to architect and deliver enterprise-scale multi-agent AI solutions. You will translate complex business needs into scalable architectures, guide design decisions, and ensure production-grade quality across the stack.

You will collaborate with customers, software engineers, data scientists, and domain experts, setting standards, documenting technical designs, and guiding implementation.

Qualifications

• Python programming expertise
• Hands-on PyTorch or TensorFlow experience
• Strong knowledge of and hands-on experience with Google Cloud Platform (GCP)
• Experience with Vertex AI including Agent Builder, Search, and Conversational Agents
• Expertise in Generative AI, ML, DL, and Agentic AI patterns
• Experience designing and implementing multi-agent systems
• Hands-on experience with LangChain, LangGraph, LangSmith, Ragas
• Experience building advanced Retrieval Augmented Generation (RAG) solutions including Graph-based RAG
• Expertise implementing AI guardrails and responsible AI controls
• Experience in AI testing, EvalOps, and solution optimization
• Experience designing enterprise-scale AI solutions focusing on performance, cost, and accuracy

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, high-quality code following software engineering best practices
• Define and communicate architecture decisions and technical design considerations
• Collaborate with customers, engineers, data scientists, and business stakeholders
• Document solution architecture, algorithms, workflows, and implementation details
• Design AI systems focusing on performance, scalability, security, cost optimization, and accuracy

Skills

Python

Generative AI

Machine Learning

Deep Learning

Multi-agent systems

Agentic AI patterns

AI testing

Security and privacy

Performance optimization

Tools

PyTorch

TensorFlow

Google Cloud Platform (GCP)

Vertex AI

LangChain

LangGraph

LangSmith

Ragas

Retrieval Augmented Generation (RAG)

Graph-based RAG

CoT Engineering

FastAPI

Pydantic

Spanner Graph / GQL

API development

Job description

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
• 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

• Vertex AI Extensions
• FastAPI
• Pydantic
• Spanner Graph / GQL
• Chain-of-Thought (CoT) Engineering
• Agentic Observability
• Semantic Entity Mapping
• API development and integrations

Nice to Have

• Gradio or Streamlit
• Dialogflow CX or Gemini Enterprise CX
• GitHub, CI/CD, DevOps
• Cloud Run, GKE
• Pub/Sub

Software Engineering & Architecture

• Clean Architecture and SOLID principles
• OAuth2/OIDC, IAM, IAP
• 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.

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