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Mid-level role with broad ML+DevOps requirements and reputable financial brand increases applicant competition.
Platform and cloud skills transfer across industries but ML-platform specifics require domain experience.
Explicit 3–5 years plus mandatory platform, AWS, Dataiku, IaC, and CI/CD skills drives high shortlisting strictness.
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Operate and support enterprise AI/ML platforms including Dataiku and Amazon SageMaker ensuring availability, performance, and compliance.
Design, develop, and deploy scalable AI/ML solutions leveraging AWS native services such as SageMaker, Bedrock, AgentCore, and related platforms.
Develop and maintain CI/CD pipelines, automation scripts, and infrastructure-as-code for enterprise AI/ML workloads while enabling governance, monitoring, and security.
3–5 years of experience in platform engineering, cloud engineering, DevOps, data engineering, or AI/ML platform support.
Hands-on experience with Dataiku platform operations and Amazon SageMaker including managing notebooks, models, pipelines, and endpoints.
Proficiency with AWS AI/ML services (SageMaker, Bedrock, AgentCore, Amazon Q, QuickSight) and DevOps tools such as Git, Jenkins, Bash scripting, CloudFormation, Terraform.
Ability to work onsite in India office minimum three days per week; full-time role with timings from 2:00 PM to 10:30 PM India Standard Time.
Experienced in enterprise AI/ML platform support combining platform engineering, cloud operations, and automation with cross-functional collaboration.
Skilled in operating and scaling AI/ML platforms securely and reliably in AWS with knowledge of governance and compliance requirements.
Capable of delivering production-ready AI/ML solutions and automation tooling that support both experimental and production workloads within an enterprise environment.