Job DescriptionJob Summary:Builds and implements end-to-end generative Artificial Intelligence (AI) solutions aligned with defined business objectives. Translates business requirements into scalable AI model designs and deployment strategies. Ensures reliability, security, and maintainability of AI solutions across the lifecycle. Collaborates with cross-functional stakeholders to drive measurable impact.
Key Responsibilities:Builds and refines end-to-end generative AI solutions aligned with defined business objectives .
Translates business requirements into AI model designs and technical implementation plans.
Implements best practices for model scalability, reliability, security, and maintainability.
Utilizes Python and related technologies to prepare, transform, and analyze data.
Collaborates with cross-functional stakeholders and communicates findings to technical and non-technical audiences.
Supports execution of AI integration initiatives aligned with enterprise roadmap.
Evaluates emerging AI capabilities and contributes to innovation initiatives.
Education Qualifications:Bachelor's degree in computer science, data science, engineering, or a related field, or equivalent experience required.
Work Experience:2-4 years of experience in machine learning, AI development, data science, or related field required.
Additional Job Description:- Standardize observability practices across AI/ML and data teams covering logging, metrics, tracing and model/AI agent performance
- Implement and maintain LLM/AI gateways, cost tracking controls, rate-limiting and security guardrails to efficiently manage LLM usage
- Build a secure, self-service framework for engineering teams to deploy AI agents, models and services independently
- Extend existing CI/CD pipelines for code-first infrastructure management and ML workflows
- Design and deploy containerized ML workloads, partnering with Infrastructure Engineering on cluster provisioning, scaling and tuning
