Technology Architect

Position:

Experience:

Location:

hands-on Technology Architect

• Architecture & Design

• Define and implement scalable, secure, and high-performing system architectures.
• Lead end-to-end product development from design to deployment.
• Create best practices, coding standards, and architectural frameworks.

• Full Stack Development

• Build backend services using

  Node.js

  and modern frameworks.
• Develop responsive

  front-end applications

  (React/Angular/Vue).
• Integrate APIs, third-party services, and AI/ML models into applications.

• AI/ML Expertise

• Apply AI/ML techniques (NLP, LLMs, predictive models, etc.) to real-world business problems.
• Deploy AI solutions into production-ready environments.

• Cloud, CDN & DevOps

• Architect and manage deployments on

  AWS / Azure / GCP

  .
• Hands-on expertise in

  Cloudflare, Akamai, and AWS CloudFront/CDN solutions

  for content delivery at scale.
• Ensure CI/CD pipelines, containerization (Docker, Kubernetes), and infrastructure-as-code practices.
• Optimize systems for

  performance, security, and cost efficiency

  .

• Leadership & Collaboration

• Collaborate with product managers, designers, and developers to deliver innovative solutions.
• Mentor engineering teams and ensure high-quality delivery.
• Evaluate new technologies and provide thought leadership on adoption.

• Proven experience in

  end-to-end app development and deployment

  (concept → production).
• Strong expertise in

  Node.js, JavaScript/TypeScript, and front-end frameworks (React/Angular/Vue)

  .
• Experience with

  AI/ML frameworks

  (TensorFlow, PyTorch, Hugging Face, OpenAI APIs, LangChain, etc.).
• Hands-on experience with

  cloud platforms

  (AWS, Azure, GCP) and microservices architecture.
• Working knowledge of

  CDNs (Cloudflare, Akamai, AWS CloudFront)

  and web performance optimization.
• Strong knowledge of

  databases

  (SQL, NoSQL, Graph DBs).
• Experience with

  DevOps tools

  (Docker, Kubernetes, Terraform, Jenkins, GitHub Actions).
• Solid understanding of system design, scalability, and security best practices.
• Excellent problem-solving, analytical thinking, and communication skills.

• Prior experience building

  AI-driven SaaS products

  .
• Exposure to

  MLOps and data engineering pipelines

  .
• Ability to work in

  startup / fast-paced environments

  .