Job Description

JD for Azure Full stack:

Design and architect end-to-end solutions for complex business problems, considering scalability, performance, security, and cost-effectiveness.

Lead the design and implementation of microservices-based architectures, defining service boundaries, APIs, and interaction patterns. Architect and integrate Generative AI and Machine Learning models into applications, defining data pipelines, model deployment strategies, and inference mechanisms. Design and develop

Agentic AI solutions

that autonomously perform tasks across business processes. Build and orchestrate workflows using

LangGraph

and integrate with Azure services. Leverage

Azure AI Builder

to create and deploy intelligent models for document processing, prediction, and classification. Utilize

Azure Foundry

for scalable data engineering and model deployment. Collaborate with data scientists, ML engineers, and development teams to translate models into production-ready, scalable solutions. Define and enforce architectural standards, patterns, and best practices across application development teams. Evaluate and select appropriate technologies, frameworks, and tools for application development, microservices, AI/ML integration, and cloud deployment. Design and optimize solutions for deployment on at least one major cloud platform (AWS, Azure, or GCP), leveraging relevant cloud services (e.g., compute, storage, databases, AI/ML services, networking). Provide technical leadership and guidance to development teams throughout the software development lifecycle. Create and maintain technical documentation, including architectural diagrams, design specifications, and technical guidelines. Collaborate with stakeholders, including product managers, business analysts, and other architects, to understand requirements and translate them into technical designs. Stay abreast of the latest trends and advancements in microservices, GenAI, Machine Learning, cloud computing, and web technologies. Drive innovation by identifying opportunities to leverage new technologies and approaches to improve our applications and processes. Assess and mitigate technical risks. Support the implementation of DevOps and MLOps practices for seamless deployment and management of applications and models. Contribute to the development of the technical roadmap and strategy.

Required Qualifications:

Bachelor's degree in Computer Science, Engineering, or a related field; or equivalent practical experience. 12-17 years of experience in solution architecture, with a strong focus on application development. Proven experience in designing and implementing microservices architectures. Demonstrated experience with Generative AI concepts, models (e.g., LLMs), and their application in software solutions. Solid understanding of Machine Learning principles, workflows, and the integration of ML models into applications. Hands-on experience with at least one major cloud platform: AWS, Azure, or GCP. Proficiency in at least one modern programming language (e.g., Python, Java, Node.js, C#). Experience with web application development technologies and frameworks (frontend and/or backend). Strong understanding of database technologies (relational and/or NoSQL). Experience with API design and management. Familiarity with DevOps principles and CI/CD pipelines. Excellent communication, presentation, and interpersonal skills with the ability to explain complex technical concepts to both technical and non-technical audiences. Strong analytical and problem-solving skills.

Technical Skills:

Architectural Patterns:

Microservices, Event-Driven Architecture, API Gateway, etc.

Cloud Platforms:

AWS (EC2, S3, Lambda, Sagemaker, etc.), Azure (VMs, Blob Storage, Azure ML, etc.), GCP (Compute Engine, Cloud Storage, Vertex AI, etc.).

Programming Languages:

Python, Java, Node.js, C#, [any other relevant languages].

AI/ML:

Generative AI models (LLMs, Diffusion Models), Machine Learning algorithms, model training and inference, MLOps.

Databases:

SQL (e.g., PostgreSQL, MySQL), NoSQL (e.g., MongoDB, Cassandra).

Web Technologies:

[Specify relevant frontend/backend frameworks and technologies, e.g., React, Angular, Vue.js, Spring Boot, Node.js].

DevOps & MLOps Tools:

Git, Jenkins, GitHub Actions, GitLab CI, Docker, Kubernetes, [relevant ML lifecycle tools].

API Technologies:

REST, GraphQL.

Other:

Messaging queues (e.g., Kafka, RabbitMQ), Caching mechanisms, Monitoring and logging tools.

Role Overview:

As a Solution Architect with a focus on Application Development & you will be a key technical leader responsible for shaping the architecture of our next-generation applications. You will bridge the gap between business requirements and technical solutions, designing comprehensive and forward-thinking architectures that incorporate microservices, generative AI, machine learning models, and robust web interfaces hosted on leading cloud platforms. Your expertise will be crucial in guiding development teams, ensuring best practices, and driving innovation.

Job Types: Full-time, Permanent

Pay: Up to ?4,500,000.00 per year

Work Location: In person