Algotale-Solution Architect – AI

 Posted 5 months ago
  
 India
  
10+ years experience
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AI Summary

The Solution Architect will design and architect scalable AI solutions for enterprise applications and integrate AI/ML models into existing business workflows. They will lead the architecture across cloud platforms and ensure solutions meet performance and compliance requirements.

Job Title: Solution Architect – AI

Location: Hyderabad / Remote
Experience: 9+ Years (Relevant)
Company
- Algotale

Job Summary

We are looking for an experienced AI Solution Architect to design, build, and scale enterprise-grade AI solutions. The ideal candidate will have deep expertise in AI/ML engineering, cloud-native architectures, big data systems, and Kubernetes-based deployments, with hands-on experience integrating AI into real-world business workflows.

Key Responsibilities

  • Design and architect scalable, secure, and high-performance AI solutions for enterprise applications.

  • Integrate AI/ML models into business workflows and existing enterprise systems.

  • Lead end-to-end solution architecture across cloud platforms, data pipelines, and AI services.

  • Architect and optimize Big Data & distributed computing systems for AI workloads.

  • Design containerized AI solutions using Kubernetes and cloud-native services.

  • Collaborate with data scientists, ML engineers, DevOps, and business stakeholders.

  • Ensure solutions meet performance, scalability, security, and compliance requirements.

  • Evaluate and recommend AI platforms, tools, and frameworks, including NVIDIA AI Enterprise.

  • Provide technical leadership, architecture guidance, and best practices.

Mandatory Skills & Experience

  • 9+ years of experience with Solution Architecture, preferably in AI-driven systems.

  • Strong experience integrating AI into enterprise workflows and applications.

  • Expertise in AI/ML Engineering (model deployment, MLOps, inference pipelines).

  • Proven experience in Architecting scalable cloud solutions (AWS/Azure/GCP).

  • Hands-on experience with Big Data & Distributed Computing frameworks.

  • Strong knowledge of Kubernetes and container orchestration.

  • Experience with PCAI (Preferred Cloud AI) and/or NVIDIA AI Enterprise.

  • Strong understanding of microservices, APIs, and event-driven architectures.

Good to Have

  • Experience with MLOps tools and CI/CD for AI pipelines.

  • Exposure to GPU-based workloads and AI acceleration.

  • Prior experience in enterprise-scale AI transformations.

  • Strong stakeholder management and communication skills.


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