GenAI Architect

Impetus; Indore District; On-site; INR 223,200 - 334,800; Full time

Job summary

A technology company seeks a talented GenAI proficient lead with strong expertise in Google Cloud Platform (GCP) and Python. This role involves designing, developing, and deploying generative AI solutions to solve complex business challenges. The ideal candidate will have over 10 years of professional experience, with a deep understanding of GCP's AI services and the ability to collaborate effectively with cross-functional teams. This position offers an opportunity to significantly contribute to the advancement of AI capabilities within the organization.

Qualifications

• 10+ years of professional experience in software development.
• Expert proficiency in Python and its relevant libraries.
• Strong hands-on experience with Google Cloud Platform (GCP), including Vertex AI and GenAI APIs.

Responsibilities

• Design, develop, and implement generative AI applications using Python and GCP.
• Collaborate with cross-functional teams to translate requirements into technical specifications.
• Stay updated on advancements in generative AI and related technologies.

Skills

Python

Google Cloud Platform (GCP)

RESTful APIs

Problem-solving skills

Analytical thinking

Collaboration skills

Exposure to Large Language Models (LLMs)

LangChain

Tools

Vertex AI

Google Kubernetes Engine

BigQuery

Cloud Functions

Cloud Storage

Job description

We are seeking a talented and passionate GenAI proficient lead with strong expertise in Google Cloud Platform (GCP) and Python to design, develop, and deploy cutting-edge generative AI solutions. The ideal candidate will be instrumental in leveraging GCP's AI services to build scalable, robust, and performant GenAI applications that solve complex business problems. You will work on the full lifecycle of GenAI projects, from ideation and prototyping to deployment and optimization, contributing to the advancement of our AI capabilities.

Key Responsibilities:

Design, develop, and implement generative AI applications using Python and GCP's AI/ML services (e.g., Vertex AI, GenAI APIs, Google Kubernetes Engine, Cloud Functions, BigQuery).

Collaborate with product managers, data scientists, and other engineers to understand requirements and translate them into technical specifications for GenAI solutions.

Stay up-to-date with the latest advancements in generative AI, large language models (LLMs), and related technologies.

Develop and integrate APIs and services for seamless interaction between GenAI models and existing systems.

Participate in code reviews, contribute to architectural discussions, and promote best practices within the team.

Document technical designs, processes, and model specifications.

Required Skills & Qualifications:

10+ years of professional experience in software development.

Expert proficiency in Python and its relevant libraries

Strong hands-on experience with Google Cloud Platform (GCP), specifically with Vertex AI, GenAI APIs (Gemini), Cloud Storage, Cloud Functions / Cloud Run, BigQuery / BigQuery ML, Cloud Logging / Monitoring

Experience with RESTful APIs and microservices architecture.

Strong problem-solving skills, analytical thinking, and attention to detail.

Excellent communication and collaboration skills.

Exposure to Large Language Models (LLMs)

Experience with Retrieval-Augmented Generation (RAG) frameworks and implementations

Familiarity with LangChain

Design, develop, and implement generative AI applications using Python and GCP's AI/ML services (e.g., Vertex AI, GenAI APIs, Google Kubernetes Engine, Cloud Functions, BigQuery).

Collaborate with product managers, data scientists, and other engineers to understand requirements and translate them into technical specifications for GenAI solutions.

Stay up-to-date with the latest advancements in generative AI, large language models (LLMs), and related technologies.

Develop and integrate APIs and services for seamless interaction between GenAI models and existing systems.

Participate in code reviews, contribute to architectural discussions, and promote best practices within the team.

Document technical designs, processes, and model specifications.