Experience Level 10+ years (with at least 2-3 years in AI/ML/GenAI)
Primary Skill Amazon Bedrock, AWS
Responsibilities
- AI & Solution Architecture
* Design scalable, secure, and high-performance AI/ML architectures aligned with organizational goals.
* Build reference architectures, solution blueprints, and reusable frameworks for AI workloads.
Evaluate and select appropriate AI tools, technologies, and platforms.
- Model Development & Deployment
* Partner with data scientists and engineers to operationalize machine learning models at scale.
* Design model training, validation, testing, deployment, and monitoring workflows.
* Define and implement MLOps best practices, including CI/CD automation for AI systems.
- Data Architecture & Integration
*Architect data pipelines and feature stores that support model training and real-time inference.
* Ensure high-quality data ingestion, transformation, governance, and lineage tracking.
Collaborate with data engineering teams to optimize data accessibility and performance.
- Governance, Security & Compliance
* Establish AI governance principles, including responsible AI, model explainability, and auditability..
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
- 7+ years of experience in architecture, software engineering, or AI/ML solution delivery.
- Strong knowledge of machine learning principles, deep learning techniques, and generative AI.
- Hands-on experience designing and deploying AI systems in cloud or hybrid environments.
- Proficiency in Python or similar languages used in AI/ML development.
- Deep understanding of data architectures, APIs, microservices, and distributed systems.
Preferred Qualifications
- Experience with cloud-native AI services (e.g., model hosting, autoML, vector search, GPU workloads).
- Familiarity with MLOps tools (MLflow, Kubeflow, SageMaker Pipelines, Azure ML Pipelines, etc.).
- Experience with LLM architectures, RAG pipelines, and production-grade GenAI implementations.
- Certifications in AI, cloud architecture, or data engineering.
