Agentic AI Lead

1 day ago


Sydney, New South Wales, Australia N2S Full time $180,000 - $250,000 per year

Exp. Level
: 8-10 years

Location:
Sydney/Melbourne/AU offices

Job Description
:

We are looking for a hands-on and technically strong Technical Lead to drive the design, development, and deployment of evaluation frameworks for Agentic AI and Retrieval-Augmented Generation (RAG) solutions. This role is pivotal in enabling the deployment of scalable multi-agent AI architecture (20–30+ agents) in production, with a strong emphasis on Agent-Level and System-Level evaluation in compliance-heavy domains such as finance and banking.

Responsibilities:

  • Develop and implement framework leveraging advanced AI Agents using models such as OpenAI GPT, Anthropic Clude, Meta Llama2, Google Gemini etc. focusing on enhancing developer and business productivity.
  • Knowledge of mapping suitable LLMs according to agent roles (e.g., DevSecOps Agent with OpenAI).
  • Must have experience with Agentic AI frameworks like
    LangGraph, CrewAI, AutoGen etc.
  • Must have experience in framework evaluation tools and techniques such as AgentBench, RAGA and OpenAI Evals
    .
  • Develop the solution incorporating advanced techniques like Retrieval Augmented Generation (RAG), Prompt Engineering ensuring optimal performance and scalability.
  • Must know how to measure and benchmark the performance of the Agents.
  • Drive end-to-end implementation and deployment with extensive knowledge of Azure and AWS services.
  • Understanding and experience in LLMOps and AgentOps with multi-agent coordination and debugging.
  • Stay abreast of emerging trends, complex patterns, data dependencies, and advancements in AI architecture, contributing to the refinement and innovation of application development processes.

Qualifications:

  • Bachelor's degree or master's degree (or equivalent experience) or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, or Applied Math with 8+ years of experience, with at least 1.5 years of hand-on in GenAI.
  • Excellent programming skills in Python with strong fundamentals in programming, optimizations and software design.
  • Proven expertise in developing scalable evaluation systems for GenAI, RAG, or multi-agent architectures.
  • Experience with agentic AI frameworks (e.g., LangChain, CrewAI, AutoGPT), RAG pipelines and orchestration tools.
  • Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic matrix environment.


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