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AI Engineer

AI Engineer

Siemens

8 - 10 years

0 Lacs

bengaluru karnataka india

Posted:1 week ago| Platform: Foundit logo

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Skills Required

aws bedrock cloud-native architecture mlflow network performance analysis security and compliance standards sagemaker pipelines azure openai gcp vertex ai kubeflow scalability improvements mlops tools latency optimization

Work Mode

On-site

Job Type

Full Time

Job Description

Experience: 8-10yrs

Location: Bangalore

Job Overview:

We are seeking a highly skilled AI Engineer with strong expertise in AWS application development and a passion for building scalable, high-performance cloud-native applications. This role involves designing and deploying serverless architectures, integrating AI/ML models including LLMs, and optimizing system performance in a dynamic and collaborative environment.

Key Responsibilities:

Design, develop, and deploy serverless applications using AWS services such as Lambda, API Gateway, Route 53, and optionally Fargate.
Build and maintain RESTful APIs using FastAPI for scalable, high-performance applications.
Collaborate with cross-functional teams to integrate AI/ML models and LLMs into production systems.
Analyze system performance, identify latency bottlenecks, and implement improvements for scalability and reliability.
Monitor and troubleshoot network infrastructure issues, including timeouts and connectivity problems.

Required Skills:

Hands-on experience with AWS, particularly:
AWS Lambda
API Gateway
Route 53
(Fargate is a plus)
Proficiency in FastAPI for API development.
Strong understanding of cloud-native architecture and microservices.

Preferred/Bonus Skills:

Experience with network performance analysis, latency optimization, and scalability improvements.
Familiarity with AI/ML models, especially Large Language Models (LLMs) and their deployment in production.
Knowledge of containerization and orchestration tools such as Docker, ECS, and Kubernetes.

Preferred Qualifications:

Bachelor's or master's degree in computer science, Data Science, Engineering, or a related field.
Certifications in AWS (e.g., AWS Certified Machine Learning Specialty, AWS Certified Solutions Architect).
Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker Pipelines.
Exposure to cloud-native AI services like AWS Bedrock, Azure OpenAI, or GCP Vertex AI.
Understanding security and compliance standards (e.g., GDPR, HIPAA) in AI deployments.
Experience working in agile, cross-functional teams and contributing to production-grade AI systems.

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AI Engineer