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Remote, mid-level AI role with broad LLM, infra, and backend requirements attracts many applicants.
Role requires niche LLM/VLM production expertise and specific infrastructure skills, limiting cross-industry transferability.
Explicit 3–5 years plus mandatory LLM/VLM production experience and specific tech stack increases filter strictness.
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Maintain and optimize production LLM/VLM pipelines responsible for content generation, compliance scoring, and campaign testing on the Sootra SaaS platform.
Manage and scale Flask/FastAPI microservices along with Dramatiq queues to ensure high uptime, low latency, and asynchronous AI workflows.
Build and maintain feedback loops including human-in-the-loop scoring and automated quality checks to improve AI model outputs continuously.
3–5 years of experience as AI Engineer or Python Backend Engineer working with production AI systems.
Strong proficiency in Python with experience in production-grade codebases using Flask and optionally FastAPI.
Hands-on experience with LLM and VLM technologies, including prompt engineering, fine-tuning, and evaluation.
Experience with microservice architecture, REST API design (authentication, rate limiting), and production deployment using Docker, CI/CD, and monitoring.
Experienced in designing and maintaining robust AI-driven SaaS platforms integrating LLM/VLM models at scale, beyond prototype development.
Skilled in managing AI infrastructure components like OpenRouter or equivalent for routing and fallback to balance cost, latency, and output quality.
Proficient operating in asynchronous microservice environments with expertise in queues/workers (Dramatiq or similar) and deployment using cloud services (AWS/GCP preferred).