
AI Engineer
2 days ago
This role involves leading the development of end-to-end cloud-based AI solutions, ensuring best practices in deployment, security, and scalability.
Key Responsibilities:
- Design and implement scalable architectures on AWS for AI applications.
- Architect multi-tenant enterprise-grade AI solutions using SageMaker, Lambda, API Gateway, DynamoDB, ECS, S3, OpenSearch, and Step Functions.
- Lead full lifecycle development of AI solutions from PoC to production ensuring reliability and performance.
- Define and implement best practices for MLOps, DataOps, and DevOps on AWS.
Award-winning Experience:
- 5+ years of experience handling multiple clients, leading technical teams, and designing end-to-end cloud-based AI solutions with an overall experience of 9-12 years.
- 4+ years of experience architecting AI/ML/GenAI-driven applications ensuring best practices in cloud deployment, security, and scalability while collaborating with cross-functional teams.
Desired Skills:
- AWS Services: Bedrock, SageMaker, Lambda, API Gateway, DynamoDB, S3, ECS, Fargate, OpenSearch, RDS.
- MLOps: SageMaker Pipelines, CI/CD (CodePipeline, GitHub Actions, Terraform, CDK).
- Security: IAM, VPC, CloudTrail, GuardDuty, KMS, Cognito.
The Ideal Candidate Should Possess:
- Excellent technical leadership skills.
- Strong expertise in AI/ML & GenAI models like Claude, Mistral, Llama, Titan.
- Ability to design conversational AI, RAG (Retrieval-Augmented Generation), and Generative AI architectures.
- Understanding of vector DBs: OpenSearch, Pinecone, FAISS.
- Proficiency in ML frameworks: TensorFlow, PyTorch, LangChain, Hugging Face.
What We Offer:
- Competitive salary and benefits package.
- Opportunity to work on cutting-edge AI projects.
- Collaborative and dynamic work environment.
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