Job Description

We are seeking a highly skilled

Senior Technical Architect

to lead the design and implementation of robust, scalable, and secure solutions across cloud, on-premise, and AI-driven ecosystems. The ideal candidate will have deep expertise in

cloud architecture (AWS, Azure, GCP)

,

on-prem platforms (e.g., SUSE Rancher)

,

containerization

,

data engineering

, and

generative AI

technologies. You will play a pivotal role in driving technical strategy, mentoring engineering teams, and ensuring best practices in system design, DevOps, and security.

Requirements

Design and implement scalable, secure, and resilient

cloud-native

and

on-premise architectures

. Lead solution architecture using

AWS, Azure, GCP

, and

SUSE Rancher

for hybrid cloud environments. Develop and scale

microservices architectures

using

Docker

and

Kubernetes

. Drive adoption of

DevOps and CI/CD

pipelines to enhance engineering efficiency. Architect and implement

data pipelines

,

ETL workflows

, and

data engineering

solutions. Lead the integration of

machine learning

and

generative AI

models using

TensorFlow, PyTorch

, and platforms like

OpenAI

and

Hugging Face Transformers

. Provide technical leadership and mentorship across teams, ensuring code quality and architecture alignment. Collaborate cross-functionally with product, data, and engineering teams to align technical strategy with business goals. Define and enforce

security best practices

, compliance requirements, and risk management protocols. Drive innovation and strategic thinking to anticipate technological trends and future-proof systems. Proven experience in designing and leading large-scale architecture for cloud and on-prem environments. Expertise with

cloud platforms

: AWS, Azure, and GCP. Hands-on experience with

SUSE Rancher

or equivalent on-prem orchestration platforms. Strong programming experience in

Python

, with a focus on data and ML applications. Deep knowledge of

machine learning

and

generative AI

ecosystems (e.g., OpenAI API, Hugging Face, TensorFlow, PyTorch). Solid background in

data engineering

,

ETL design

, and scalable

data pipelines

. Strong understanding of

microservices design

,

API development

, and

container orchestration

. Experience with

CI/CD

,

DevOps tools

, and modern infrastructure automation. In-depth knowledge of

cybersecurity principles

, identity & access management, and data protection. Excellent problem-solving, communication, and leadership skills. Ability to align technical decisions with strategic business goals. Certifications in AWS, Azure, GCP, or Kubernetes (CKA/CKAD). Experience in multi-cloud or hybrid cloud deployments. Background in MLOps and real-time inference systems. * Familiarity with event-driven architectures and streaming platforms (e.g., Kafka).