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Tier-1 brand and mid-level role increase applicants while AI deployment specialization moderately limits competition.
Requires production AI/ML deployment and enterprise integration experience, reducing cross-industry transferability.
Explicit 4–8 years requirement plus production AI/ML deployment and cloud/Kubernetes expectations create moderate shortlisting strictness.
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Partner with enterprise customers to understand technical requirements, design scalable AI solution architectures, and guide through production deployments.
Build integrations, prototypes, reusable tools, and lead technical workshops and troubleshooting to accelerate customer success.
Collaborate with Product and Engineering teams to share customer feedback and influence product enhancements, creating documentation and best practices for future deployments.
Bachelor's degree in Computer Science or related technical field (or equivalent experience).
4–8 years of software engineering experience building scalable, production-grade applications.
Experience with APIs, distributed systems, cloud platforms, or backend development.
Strong troubleshooting and problem-solving skills across multiple technology stack layers; excellent communication skills for direct enterprise customer interaction.
Experienced in deploying or supporting AI, Generative AI, LLM, or Machine Learning applications in production environments.
Proficient with Kubernetes, cloud infrastructure, observability tools, or MLOps, and building customer-facing technical solutions or integrations.
Demonstrated capability in technical consulting, solutions engineering, or customer success within enterprise settings, with focus on scalable, production-grade software.