AI Solution Architect - Principal

What will you do?


* Architect end-to-end AI/ML deployment solutions focusing on AWS services such as S3, Redshift, SageMaker, Bedrock, Lambda, and IAM, ensuring best practices in security, compliance, and scalability.


* Design and integrate data lakes, structured databases, and ML pipelines leveraging Databricks architecture for smooth data processing and AI workload orchestration.


* Lead solution design and orchestration for RPA and GenAI systems, incorporating conversational and agentic AI platforms like Copilot Studio, Agentforce, and Sierra.


* Drive architectural decisions, review technical approaches, and provide leadership to development teams on experimentation, prototyping, and solution delivery.


* Manage model development, deployment, and lifecycle on platforms such as SageMaker and Bedrock, implementing MLOps best practices.


* Implement end-to-end automation of ML pipelines with SageMaker and Databricks workflows, integrating models into scalable, cloud-native services.


* Utilize Kubernetes and container orchestration for scalable AI deployment alongside infrastructure as code tools such as Terraform and CloudFormation.


* Establish advanced monitoring, logging, and performance optimization for AI workloads, promoting high availability and reliability.


* Collaborate with business stakeholders to prioritize AI use cases and ensure architectural alignment with strategic objectives.


* Oversee data ingestion, transformation, and governance workflows to maintain data privacy, quality, and accessibility for AI and RPA workloads.


* Define and implement CI/CD pipelines tailored for AI/ML deployments, ensuring seamless and automated delivery cycles.


* Stay current on emerging AI technologies, especially in Generative AI and LLM domains, and drive integration of innovative solutions with existing platforms.

What skills and capabilities will make you successful?



* 8-10 years of hands-on solutions architecture experience, with significant focus on AI/ML cloud-native architectures and deployments.


* Deep expertise in core AWS services: S3, Redshift, SageMaker, Bedrock, Lambda, IAM, and associated AI services (Comprehend, Rekognition, Lex, Polly, Textract).


* Proven experience architecting data lakes, ETL pipelines, and managing data engineering workflows (AWS S3, Redshift, Databricks).


* Proficiency in advanced Python programming, Jupyter Notebooks, and machine learning libraries such as scikit-learn, TensorFlow, and PyTorch.


* Experience designing and deploying scalable ML models and pipelines, with strong knowledge of MLOps best practices including automation, containerization, and deployment.


* Expertise with Databricks architecture and integration within ML and AI ecosystems.


* Solid understanding of Kubernetes for container orchestration and infrastructure automation using Terraform or CloudFormation.


* Familiarity with conversational AI, age...