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Strong global brand, metro location, mid-level AI role, and high market demand create high competition.
Requires specialized AI, enterprise integration, and compliance experience, limiting cross-industry transferability.
Explicit 4–6 years plus mandatory LLM, MLOps, cloud, Python, and enterprise integration skills make filters highly stringent.
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Own full lifecycle development and deployment of AI models including large language models (LLMs) such as GPT-4, ensuring secure integration with enterprise platforms via APIs.
Develop and optimize data pipelines using structured and unstructured data, leveraging vector databases and cloud platforms (Azure, AWS, GCP) to scale AI workloads efficiently.
Lead prompt engineering, DevOps/MLOps practices, and compliance adherence to deliver reliable, secure, and impactful AI pilot projects and solutions aligned with business needs.
4-6 years of advanced experience in developing, deploying, and maintaining AI and machine learning solutions in enterprise environments.
Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.
Advanced proficiency in Python programming and AI frameworks; expertise with large language models (LLMs) and prompt engineering.
Experience with cloud platforms (Azure, AWS, or GCP), API integration, data pipeline engineering, security, and compliance (GDPR, HIPAA).
Technically deep AI practitioner skilled in full-stack software development, data engineering, and cloud-native AI deployments in regulated enterprise contexts.
Proven ability to translate complex business requirements into scalable, secure AI solutions, balancing innovation with ethical and compliance considerations.
Experienced in managing AI model lifecycle using MLOps/DevOps, with strong stakeholder engagement and communication skills to drive adoption of AI technologies.