AI Technical Architect

E-Solutions United State
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AI Summary

Design and develop large-scale GenAI applications and machine learning solutions. Lead engineering teams and make critical architectural and technical decisions. Deliver high-quality, scalable, and secure AI-driven solutions.

Key Highlights
GenAI applications
Machine learning solutions
Cloud-native infrastructure
Key Responsibilities
Architect, lead, and actively contribute to the development of GenAI applications and machine learning solutions
Design scalable cloud-native infrastructure and data engineering pipelines
Make critical architectural and technical decisions for enterprise-scale applications
Technical Skills Required
Python JavaScript Java TensorFlow PyTorch scikit-learn spaCy RESTful APIs GraphQL GCP Data Engineering DevOps
Benefits & Perks
Hybrid work arrangement
Visa sponsorship available
14+ years of hands-on experience in Software Engineering

Job Description


Role: AI Technical Architect-Mandatory Requirement:

• Minimum 3+ years of Architect / Leadership experience

Location: Raritan (Hybrid)

Visa: All Visa Types Accepted


Job Details:

14+ years of hands-on experience in Software Engineering

• Strong leadership experience managing cross-functional teams across GenAI, Machine Learning, and Cloud Infrastructure

• Hands-on experience designing and developing large-scale systems including GenAI applications, API architectures, data systems, ML pipelines, and cloud-native applications

• Strong programming expertise in Python, JavaScript, Java, or other backend technologies

• Experience with RESTful APIs and GraphQL

• Extensive experience building and deploying ML models using TensorFlow, PyTorch, scikit-learn, and spaCy

• Hands-on experience integrating ML models into GenAI applications

• Strong experience in GCP, Data Engineering, and DevOps

Responsibilities:

• Architect, lead, and actively contribute to the development of GenAI applications and machine learning solutions

• Design scalable cloud-native infrastructure and data engineering pipelines

• Make critical architectural and technical decisions for enterprise-scale applications

• Lead engineering teams while remaining hands-on with coding, technical design, and problem-solving

  • • Deliver high-quality, scalable, and secure AI-driven solutions


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