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Mid-level AI role in metro with broad LLM and backend requirements increases applicant competition.
Medium - blends ML, speech, and backend engineering, transferable across AI-focused companies but domain-specific.
Medium - explicit 5-8 years and multiple mandatory engineering and cloud/LLM skills required.
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Design, build, deploy, and operate LLM-powered pipelines, speech processing systems, and AI agents processing millions of enterprise conversations at scale.
Develop high-throughput, reliable, multi-tenant backend services with end-to-end ownership including cost management and observability for AI workloads.
Mentor and lead a team of 4-6 engineers, owning code quality, design, and team output while collaborating with product, data, and platform teams.
Bachelor's or Master's degree in Computer Science or equivalent.
5-8 years of software engineering experience.
Proficiency in backend languages such as Python, Java, or Go, with strong fundamentals in data structures, algorithms, multi-threading, concurrency, and software engineering concepts.
Experience designing, building, and operating microservices, RESTful APIs, distributed systems, databases, caching, message brokers, and familiarity with major cloud platforms and container orchestration (Docker, Kubernetes).
Experienced in building and optimizing AI/ML pipelines, specifically with large language models and speech processing systems at scale.
Comfortable with end-to-end ownership in a high-autonomy environment, including cost tracking, self-hosting, and infrastructure monitoring.
Demonstrates engineering depth in distributed systems and distributed backend services with a focus on reliability, scalability, and multi-tenant SaaS solutions.