Gen AI Technical Architect - Day 1 onsite

Overview

On Site
Contract - W2
Contract - 30 day((s))

Skills

Azure
AWS
GCP
Gemini
PaLM
LLM models (Falcon
Llama2)
Google (PaLM

Job Details

We are hiring seasoned GEN AI Technical architect who has hand on coding exprienc in python for our client in Temple terrace,FL. This is W2/1099 role, No c2c are allowed.
Candidate needs to be in onsite on Day 1 if out of state candidate then client will provide 2 weeks time to relocate.
Expected from Candidate:
worked in conceptualizing and implementing GenAI applications tailored for Telecom Network scenarios.
Ideal candidate possesses a proven track record of successful project deliveries across a diverse tech spectrum.
Should be adept at hands-on implementation, whether in proof-of-concept (POC) or full-scale deployment.

Design AI Solutions

Architect and design scalable, reliable, and high-performance AI solutions leveraging the capabilities of Multi-Cloud Platforms (Google Cloud Platform, Azure, AWS). Design, develop, and implement Generative AI models and algorithms LLM models (Falcon, Llama2), Google (PaLM, Gemini), Open AI

LLM Ops

Productionize models model training, model deployment, model serving, and model monitoring. Optimize Generative AI models for improved performance, scalability, and efficiency.

Client Consultation

Conduct thorough consultations with clients to comprehend their business goals, challenges, and requirements.

Act as a trusted advisor, providing insights into how Gen AI solutions can drive value and enhance business processes.

Prototyping and Proof of Concept

Develop prototypes and proof of concept demonstrations to showcase the feasibility and potential impact of proposed Gen AI solutions.

Iterate on prototypes based on client feedback and technical feasibility.
  • Proficiency in the following languages, frameworks, and tools is preferred:
  • Programming and scripting languages: Python, C/C++, Make, Java, JSP, Perl, Shell, JavaScript, TypeScript
  • Structured and NoSQL databases: Informix, Oracle, PostgreSQL, MongoDB, Cassandra
  • Modernization of monolithic applications and legacy app migrations to microservices architecture
  • Database and dataset migrations, SQL conversion scripting
  • Virtualization tools: VMware, Vagrant, Docker, Podman
  • Containerization tools: Kubernetes (K8s), OpenShift, Amazon EKS, Helm
  • Cloud platforms: AWS, Google Cloud Platform (Google Cloud Platform), Microsoft Azure
  • CI/CD tools: Jenkins, GitCI, Argo