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Mid-level popular software role in a metro hybrid setting with moderate brand and AI specialization.
Role demands LLM, agent frameworks, and vector DB expertise, reducing cross-industry transferability.
Explicit 2–4 year requirement plus mandatory LLM, cloud, language, and production experience increases filter strictness.
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Own the full stack development of AI-driven automation pipelines and AI agent systems, including API design, cloud infrastructure, and business logic.
Design and implement human-in-the-loop governance mechanisms such as confidence thresholds and approval gates for AI agents.
Monitor AI operations for issues like drift and hallucination, manage prompt/model versions, and instrument systems to tie performance to business metrics like productivity and cost.
Bachelor’s degree in Computer Science or related field.
2–4 years of software engineering experience building production systems.
Proficiency in Python, C#, or Java; experience building REST APIs.
Experience developing cloud-based applications (Azure preferred; AWS/GCP acceptable).
Experienced in developing AI-powered workflows using LLMs with hands-on prompt design and output validation.
Capable of re-engineering business processes before automation to improve efficiency and effectiveness.
Comfortable managing end-to-end AI system lifecycles including performance monitoring, prompt tuning, and cross-system integration.