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Solugenix - AI Technical Architect

Solugenix India Private Limited
8 - 10 Years
Hyderabad

Posted on: 29/05/2026

Job Description

Job Title : AI Technical Architect


Experience : 8+ years


Location : Hyderabad / Bengaluru


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 & Expertise :


- 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 (Sageker, Lambda, EC2, S3, CloudFormation).


- Architecture & Design : Proven ability to design scalable, secure, and high-performance systems.


- Experience : 8-10 years in software engineering, with at least 3-4 years in AI/ML solution architecture.


- Soft Skills : Strong communication, leadership, and problem-solving abilities.


- 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.


Education : BE/ BTech / BSC /MCA

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