Technology Architect
2 weeks ago
Position Summary:
The Technology Architect designs and develops software applications/platforms, manages technical debts and decides technology roadmaps for existing platforms. He/She should have strong analytical, problem solving, Software programming, Software Database, and architecting skills with ability to evaluate pros/cons of each technology component and take a balanced call. He/She should have extensive implementation experience on building large-scale systems. Any exposure to AI/ML and Data science is an added advantage.
Responsibilities:
- Determine Technology Architecture for the group of applications
- Design / Own Development / Lead teams for large scale software application development
- Create and Own High Level Design, Low Level Design for each of the Software applications
- Define guidelines, coding best practices, automated testing strategies (unit testing, regression testing), for the team
- Define / setup CI/CD pipelines
- Clearly communicate status, updates and plan to project leadership
- Learn, acquire and get certified on new technologies as demanded by project
- Any exposure and experience in AI, ML and ML Ops is must.
Required Skill:
- Extensive Application design, Development, Maintenance, and Support skills with proven hands-on experience with the latest Java/MEAN/MERN technology stack. Specifically experience in multiple of the following technologies
- Java/.Net/Python/NodeJS
- Angular / React / ASP.Net
- RDBMS (Oracle/SQL Server/Postgre)
- SQL
- NoSQL databases like Mongo
- Extensive experience in Open-Source Technologies
- Preferable: Knowledge of database management tools like Liquibase / Hibernate
- Well-versed in Devops (e.g. Azure DevOps) and cloud PaaS.
- Good understanding of coding standards, ability to debug.
- Good Experience in Software development lifecycle and processes.
- Ability to work effectively in a cross-functional team.
- Familiarity with Docker and Git
- Exposure to AI/ML frameworks in Keras, Pytorch, libraries scikit-learn
- Knowledge and practical application of statistical analysis and mathematical modeling concepts and principles
- Extensive experience in Data Engineering and Management, including building and maintaining data pipelines, ensuring data governance, and compliance. Proven hands-on experience in:- Apache Spark / Kafka / AWS Glue - SQL / NoSQL (PostgreSQL, MongoDB) - Google BigQuery / AWS Redshift
- Expertise in AI, Machine Learning, and Specialized AI Domains like Generative AI, NLP, and Computer Vision. Experience in: - TensorFlow / PyTorch / scikit-learn - GPT / BERT / Llama/ Hugging Face Transformers - OpenCV / DALL·E / YOLO
- Cloud Computing and Scalable Architecture for designing and deploying AI systems with cloud-based solutions. Expertise in: - AWS SageMaker / Azure Machine Learning / Google Cloud AI - Docker / Kubernetes / NGINX - High-performance computing (NVIDIA GPUs / TPUs) - Cloud-based model deployment (AWS/Azure/GCP), performance monitoring, and troubleshooting.
- Strong background in CI/CD, DevOps, and MLOps, streamlining AI development and deployment processes. Hands-on experience with: - Jenkins / Terraform / Ansible / MLflow - Kubeflow / GitLab CI/CD - Experience with Jira / Git for project management and version control.
- Proficiency in data visualization (matplotlib, seaborn, tableau/Power BI (optional))
- Excellent collaboration and communication skills, with proven ability to work effectively in crossfunctional teams and translate AI insights into business outcomes.
POSITION SPECIFICATIONS
Bachelor’s degree in Computer Science, Information Technology, Electronics Communication. Other branches of engineering with proven skills through past experience / projects can also apply.
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