Adactin - Senior Artificial Intelligence Engineer - AWS
5 days ago
Job title : Senior AI Engineer with AWS
Location : WFH, India
Experience : 10-15 years
About the role :
We are looking for an experienced AWS Data & AI Engineer to design and implement scalable data and AI solutions on AWS. The role involves building end-to-end data pipelines, developing Lakehouse architectures, and operationalizing ML models using services like S3, Glue, Redshift, and SageMaker. Youll work closely with cross-functional teams to ensure data reliability, performance, and security while driving innovation through cloud-based analytics and AI solutions.
Responsibilities :
- Design and implement end-to-end data architectures on AWS including ingestion, storage, transformation, and analytics pipelines.
- Build data lake and data warehouse solutions using services such as AWS S3, Glue, Redshift, Lake Formation, and Athena.
- Develop and maintain ETL/ELT pipelines using AWS Glue, Step Functions, Lambda, or EMR.
- Collaborate with data scientists to operationalize AI/ML models using Amazon SageMaker, integrating them with enterprise data sources.
- Implement real-time and batch data processing frameworks leveraging Kinesis, Kafka on AWS MSK, or Spark on EMR.
- Ensure data security and compliance through IAM, KMS, CloudTrail, and governance policies.
- Design CI/CD pipelines for data and AI solutions using CodePipeline, CodeBuild, or GitHub Actions.
- Monitor and optimize data workloads for cost efficiency, scalability, and performance.
- Work closely with business stakeholders to translate requirements into technical specifications and delivery roadmaps.
Required Skills & Experience :
- Proven experience with AWS cloud services for data and AI including S3, Glue, Redshift, Athena, SageMaker, Lambda, and EMR.
- Strong proficiency in Python, SQL, and PySpark for data transformation and ML workflows.
- Experience designing data Lakehouse architectures and integrating with BI tools (e.g., QuickSight, Power BI, Tableau).
- Familiarity with MLOps and DataOps practices (CI/CD, model deployment, monitoring, retraining).
- Solid understanding of data modelling, metadata management, and governance.
- Hands-on experience with infrastructure-as-code (IAC) tools like Terraform or AWS CloudFormation.
- Excellent problem-solving, communication, and stakeholder management skills.
Preferred Qualifications :
AWS Certifications such as :
- AWS Certified Data Analytics Specialty
- AWS Certified Machine Learning Specialty
- AWS Certified Solutions Architect Associate/Professional
- Experience with Databricks on AWS, Snowflake, or AI frameworks (TensorFlow, PyTorch, Hugging Face).
- Background in analytics enablement, data governance, or cloud cost optimization.
- Knowledge of GenAI, LLM fine-tuning, and AI agent integration using AWS Bedrock or SageMaker JumpStart.
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