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Tier-1 employer, metro hiring and mid-level role but GenAI/MLOps specialization limits applicant density.
Specialized GenAI and MLOps platform experience makes background fit highly domain-specific.
Explicit 5+ years plus mandatory GenAI, MLOps, AWS and responsible AI experience increases shortlisting strictness.
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Lead adoption and integration of enterprise AI-assisted software engineering practices to improve code quality, delivery speed, and operational outcomes.
Develop, troubleshoot, and maintain secure, scalable AI/ML platform code and Gen AI use cases including LLM fine tuning and multi-agent orchestration using platform engineering.
Apply expertise in software development lifecycle tools and practices to automate processes and ensure continuous integration within agile team environments.
5+ years of applied software engineering experience with formal training or certification.
Proven experience leading adoption of approved AI-assisted development tools (coding, code review, test acceleration, troubleshooting).
Strong expertise in responsible AI use including data sensitivity, security, and compliance within engineering workflows.
Hands-on experience with Python, AWS services (EKS, EMR, ECS), and AIML lifecycle development.
Experienced in managing and coaching teams on secure, compliant AI-assisted software development practices.
Proficient in generative AI technologies, agent development, and AI platform engineering in production environments.
Comfortable working within agile frameworks focusing on automation, continuous integration, and scalable AI/ML service delivery.