AI Architect- design, implement, and optimize enterprise-grade AI solutions
- Source: LinkedIn
- Technogen, Inc.
- On-site
- Hyderabad
- Full-Time
- Mid level
Job Description
We are seeking an experienced AI Technical Architect to design, implement, and optimize enterprise-grade AI solutions. The ideal candidate will have a strong background in AI frameworks, backend development (Node.js), and cloud architecture (AWS). This role requires both hands-on technical expertise and the ability to provide architectural leadership across teams.
Key Responsibilities
Architect AI Solutions: Design scalable AI/ML systems leveraging modern frameworks (TensorFlow, PyTorch, Hugging Face, etc.).
Backend Development: Lead backend solution design and development using Node.js, ensuring performance, security, and maintainability.
Cloud Integration: Define and implement cloud-native architectures on AWS, including compute, storage, and AI/ML services.
Technical Leadership: Guide engineering teams on best practices, code reviews, and architectural decisions.
Innovation & Strategy: Evaluate emerging AI technologies and frameworks to recommend adoption strategies.
Collaboration: Work closely with product managers, data scientists, and DevOps teams to deliver end-to-end AI solutions
Required Skills:
Experience: 10 years in software engineering, with at least 3–4 years in AI/ML solution architecture.
AI/ML Frameworks: Proficiency in TensorFlow, PyTorch, Scikit-learn, Hugging Face, or similar.
Backend Development: Strong expertise in Node.js, RESTful APIs, and microservices architecture.
Cloud Awareness: Hands-on experience with AWS services (SageMaker, Lambda, EC2, S3, CloudFormation).
Architecture & Design: Proven ability to design scalable, secure, and high-performance systems.
Desired Skills:
Exposure to MLOps practices (CI/CD for ML, model deployment pipelines).
Knowledge of data engineering concepts (ETL, data lakes, streaming).
Experience with containerization (Docker, Kubernetes).
Familiarity with security best practices in AI and cloud environments
- Soft Skills: Strong communication, leadership, and problem-solving abilities.
Skills
- Tensorflow
- PyTorch
- hugging-face
- NodeJS
- amazon-web-services
- Scikit-learn
- amazon-sagemaker
- aws-lambda
- amazon-ec2
- amazon-s3
- aws-cloudformation
- Docker
- Kubernetes
