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Mid-level cloud role, metro location, and strong employer brand increase applicant density.
Core cloud engineering skills transfer across industries despite GenAI and pharma compliance nuances.
Explicit six-year minimum, required cloud/AWS expertise and enterprise governance needs make filters stringent.
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Lead design and implementation of Generative AI applications including prompt engineering, fine-tuning, and orchestration of LLM workflows across business domains.
Own technical roadmap, architecture decisions, delivery, and integration of GenAI projects and cloud-native AI services within the enterprise.
Mentor software engineers and AI practitioners, ensuring best practices in model governance, code quality, scalability, and security for cloud applications.
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
Minimum 6 years of development experience with a focus on cloud computing.
Strong knowledge and hands-on experience with cloud platforms (AWS, Azure, or Google Cloud) and services like EC2, S3, Lambda, RDS, DynamoDB, API Gateway, CloudFormation.
Proficiency in programming languages such as Python, Java, or Node.js.
Experienced in leading complex GenAI and cloud-native AI projects with exposure to enterprise-wide AI tool integration and governance.
Operates effectively in cross-functional teams involving data scientists, MLOps, and product owners to deliver business-aligned AI solutions.
Has strong architectural and hands-on expertise in cloud infrastructure, microservices, APIs, serverless, containerization, and data pipelines with focus on security and scalability.