Job Description & Scope
Job description Job Title: Senior Architect AI Platform & Engineering Location: Bangalore Mode: Work from Office Job Summary: We are seeking an experienced Senior Architect AI Platform & Engineering to lead the architectural design and technical strategy of our AI-driven platform. The ideal candidate will have a deep understanding of AI/ML frameworks, AI model deployment, cloud platforms, distributed computing, and solution architecture. This role demands a strong background in solution architecture and hands-on expertise in AI/ML technologies, ensuring the scalability, security, and efficiency of our AI products and platform. Key Responsibilities: 1. AI Platform and Product Architecture: • Define and design the end-to-end architecture of an AI-driven platform, ensuring scalability, reliability, and security. • • • • Architect and design AI/ML pipelines, inference engines, and model serving infrastructure. Develop microservices-based architecture to support AI workloads and data-driven applications. Ensure seamless integration of AI models into the platform and applications. Define and implement MLOps best practices to streamline AI/ML lifecycle management. 2. AI/ML Frameworks & Model Deployment: • Work with TensorFlow, PyTorch, Hugging Face, ONNX, and other AI frameworks to optimize model training and deployment. • • • Architect model-serving solutions using KServe, TensorFlow Serving or equivalent. Optimize AI model performance for low-latency, high-throughput inference. Implement AI governance and compliance frameworks for responsible AI practices. 3. Cloud & Infrastructure: • • • • Design AI platform solutions for AWS, OCI, GCP, and hybrid/multi-cloud environments. Leverage Kubernetes, Docker, and serverless computing to manage AI workloads efficiently. Implement data lake, feature store, and real-time analytics architectures. Design and optimize GPU/TPU-based infrastructure for AI workloads. 4. Solution Architecture & Engineering Leadership: • • Provide technical leadership in designing AI solutions, working closely with product managers, data scientists, and engineering teams. Collaborate with product management, data scientists, and engineering teams to align AI architecture with business objectives. • • • • Develop high-level and detailed solution architecture for AI-driven applications and platforms. Lead proof-of-concepts (PoCs) and pilot projects to validate AI-driven solutions. Provide technical mentorship and guidance to engineering teams. Conduct architectural reviews and ensure adherence to best practices and industry standards. 5. AI Security & Compliance: • • • Design AI architectures with a strong focus on data security, privacy, and compliance (GDPR, HIPAA, SOC2 etc.). Implement secure model training, explainability (XAI), and adversarial attack mitigation techniques. Ensure secure API integrations for AI models and services. Required Qualifications & Skills: Key Technical Skills: • • • • • • • AI/ML Architecture: Proven expertise in designing scalable AI/ML architectures, including deep learning, reinforcement learning, NLP, and computer vision. Cloud & Infrastructure: Hands-on experience with cloud-native architectures on AWS, Google Cloud, and Azure. Containerization & Orchestration: Proficiency in Docker, Kubernetes, and container orchestration for scalable AI/ML deployments. Data Engineering & MLOps: Strong understanding of data pipelines, big data management (Kafka, Spark, Hadoop), and MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI). Microservices & APIs: Skilled in designing high-performance, scalable, and maintainable microservices architectures. Security & Compliance: In-depth knowledge of AI security best practices, model governance, encryption, and access control in cloud and on-prem environments. DevOps & CI/CD: Experience with CI/CD pipelines, infrastructure as code (Terraform, CloudFormation), and automated AI/ML deployment workflows. • • LLMs & Generative AI: Exposure to Large Language Models (LLMs) and Generative AI ap
