GenAI Architect with Java

TechDigital Group; San Leandro (CA); On-site; USD 120,000 - 150,000; Full time

Job summary

A leading technology firm located in California is seeking an experienced professional for an integration role. The ideal candidate will bring over 10 years of experience, especially in implementing GeAI use cases for virtual assistants, and have practical knowledge of technologies including Java, Python, and LLMs. Familiarity with GenAI concepts and the ability to articulate contributions in projects are essential for this position.

Qualifications

• 10+ years of experience required.
• Prior experience implementing GeAI use cases for virtual assistants.
• Experience with LLMs, particularly Gemini.

Responsibilities

• This is an integration role requiring hands-on experience.
• Practical application of listed technologies is crucial.
• Candidate should articulate contributions clearly.

Skills

Java

Python

Flink (DAG)

GeAI use case implementation

LLM (Large Language Models)

Job description

Overview

Experience: 10+ YOE

Qualifications

• Prior experience of implementing GeAI usecases for Virtual Assistant
• Experience with LLM's and Gemini in particular
• Consulting mindset, worked with teams, played an architect role
• Skills : Java, Python, Flink (DAG)

Responsibilities

This is an integration role which requires the person to be hands-on.

• Hands-on experience: Practical application of listed technologies is crucial in key areas relevant to the role, including:
  • RAG (Retrieval Augmented Generation)
  • Function Calling/Tools
  • Langchain
  • Vector databases
• Clear articulation of contributions: Candidates should be able to explain their involvement and impact in specific projects.
• Deep understanding of GenAI concepts: Beyond surface-level knowledge, a strong grasp of core concepts, including non-functional requirements (safety filter, data security, prompt injection, grounding), is essential.
• Familiarity with emerging trends: Keeping up to date with the latest advancements in GenAI is highly desirable.