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Mid-level generalist title, 3–6 year band, and metro hiring increase applicant competition.
LLM and production ML infra skills transfer across industries but require specific applied-AI experience.
Multiple mandatory technical requirements and explicit 3–6 years experience make shortlisting highly selective.
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Develop and extend LangGraph-based agents and MCP tool servers integrating various domain APIs with strong security and multi-tenant support.
Design, deploy, and operate cloud-native services on AWS EKS using modern CI/CD pipelines, focusing on scalability, security, and observability.
Lead design reviews, mentor engineers, and contribute to platform libraries supporting unified commerce solutions at scale.
3 to 6 years of software engineering experience with strong Python skills in production environments using async frameworks (e.g., FastAPI) and Pydantic.
Hands-on experience with LLM-powered features including agent frameworks (LangChain/LangGraph or equivalent), tool/function calling, and prompt engineering.
Proficient in Kubernetes and Docker for service deployment and management, preferably on AWS EKS with Helm experience.
Experience with at least two of the following: Kafka, Snowflake, Postgres, Redis, Couchbase, or ClickHouse; and working knowledge of API security (OAuth2/JWT, mTLS).
Experienced in building and operating LLM-driven agent frameworks and multi-tenant SaaS architectures, comfortable with complex cloud-native service environments.
Proficient in observability tools and security-gated CI/CD processes, with demonstrated ownership in production including incident response.
Preferably has familiarity with advanced LLM infrastructure components such as vLLM, GPU inference, tool interfaces, and guardrails engineering.