Senior AI Solutions Architect

Job Summary:

We are looking for a highly skilled Senior AI Solutions Architect to design, develop, and implement AI-driven solutions that align with business objectives. This role requires expertise in artificial intelligence, machines learning, cloud computing, and software architecture to build scalable and efficient AI systems. The ideal candidate will collaborate with cross-functional teams to drive AI adoption across various applications.

Key Responsibilities:

1. AI Solution Design & Architecture

• Architect end-to-end AI solutions for enterprise applications, including machine learning models, data pipelines, and cloud-based infrastructure.
  
• Design and implement AI frameworks that are scalable, reliable, and cost-effective.
  
• Ensure AI models integrate seamlessly with existing software, databases, and APIs.
  

2. AI Model Deployment & Optimization

• Deploy machine learning and deep learning models on cloud platforms (AWS, Azure, GCP) and on-premise infrastructure.
  
• Optimize AI models for performance, efficiency, and scalability.
  
• Utilize MLOps (Machine Learning Operations) practices to automate model training, validation, and monitoring.
  

3. Cloud & Infrastructure Management

• Design AI solutions leveraging cloud-native technologies such as Kubernetes, Docker, and serverless computing.
  
• Implement data pipelines for real-time and batch AI processing.
  
• Work with DevOps teams to ensure CI/CD pipelines for AI deployments.
  

4. Cross-Functional Collaboration & Leadership

• Work closely with data scientists, software engineers, and business leaders to translate business challenges into AI-driven solutions.
  
• Act as the AI subject matter expert (SME) and provide technical leadership in AI strategy and implementation.
  
• Conduct AI solution workshops and training for teams.
  

5. AI Governance, Security, and Compliance

• Ensure AI models comply with ethical guidelines, data privacy regulations (GDPR, CCPA), and security best practices.
  
• Implement AI governance frameworks to monitor model fairness, interoperability, and performance.
  

Requirements

Required Qualifications & Skills:

1. Education & Experience:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  
• 8+ years of experience in AI, software architecture, and cloud solutions.
  
• Proven track record in designing and deploying AI solutions at an enterprise level.
  

2. Technical Skills:

• Programming: Proficiency in Python, Java, or C++.
  
• AI/ML Frameworks: Expertise in TensorFlow, PyTorch, Scikit-learn, and Hugging Face.
  
• Cloud Platforms: Hands-on experience with AWS SageMaker, Google Vertex AI, Azure ML.
  
• MLOps Tools: Experience with Kubeflow, MLflow, or Apache Airflow.
  
• Data Engineering: Familiarity with Big Data technologies (Spark, Hadoop, Databricks).
  
• API Development: Experience in RESTful APIs and GraphQL for AI service integration.
  

3. Soft Skills:

• Strong analytical and problem-solving skills.
  
• Excellent communication and stakeholder management abilities.
  
• Ability to drive AI adoption and evangelize AI best practices.
  

Preferred Qualifications:

• Certification in AWS Certified Machine Learning – Specialty, Google Professional Machine Learning Engineer, or Azure AI Engineer Associate.
  
• Experience in Generative AI, LLMs (GPT, BERT), and Computer Vision.
  
• Knowledge of Edge AI and IoT.