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Remote role with mid-level/senior hiring and strong VC-backed startup increases candidate competition.
Requires specialized LLM, RAG, and production AI experience, limiting cross-industry transferability.
Explicit years plus mandatory LLM production, cloud, vector DB, and security requirements raise shortlisting strictness.
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Lead design, development, and deployment of generative AI and LLM-powered services including chatbots, AI recommendations, and workflow automation.
Build and optimize end-to-end RAG pipelines and develop multi-step LLM agentic systems incorporating planning and tool use.
Ensure production readiness by writing maintainable code with monitoring, deploying scalable AI components on AWS, and collaborating cross-functionally to integrate AI features.
3+ years (mid-level) or 5+ years (senior) backend engineering experience with Python and scalable API/service design.
Proven hands-on experience with LLMs, generative AI products, RAG pipelines, and agent development.
Strong AWS/cloud deployment skills including IaC (Terraform/CDK), security (PII handling, encryption), monitoring, and cost/latency optimization strategies.
Experience with LLM orchestration libraries (LangChain, LlamaIndex) and vector databases (Pinecone, Chroma, Milvus).
Experienced in building production-grade AI applications combining robust backend engineering with deep generative AI expertise.
Comfortable working in a fast-paced environment requiring rapid prototyping, cross-team collaboration, and autonomous troubleshooting across the AI stack.
Skilled at evaluating LLM model behavior, failure modes, and applying product-focused AI evaluation techniques (A/B testing, prompt unit tests).