Agentic AI Lead
1 day ago
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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