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Popular mid-level fullstack title with generalist requirements but niche LLM/agentic skills moderate competition.
Strong agentic LLM and Temporal/Vector-store requirements create high domain specificity and lower cross-industry transferability.
Mandatory 6+ years, specific LLM/agentic experience, and precise tech stack increase shortlisting strictness.
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Design, develop, and ship production-grade AI features end-to-end including backend services, data pipelines, LLM orchestration, and frontend integration.
Build and maintain reliable, maintainable AI agent workflows using OpenAI Agents SDK, Temporal orchestration, and vector store integrations with a focus on eval-driven development.
Own full-stack delivery spanning Python backend, React frontend, APIs (GraphQL, REST), and SQL analytics with responsibility for deployment, monitoring, and observability.
6+ years in Software Engineering or Data Science with strong engineering; 1–2 years hands-on experience building with LLMs/agentic AI.
Proficient in Python (primary), SQL, and TypeScript/JavaScript; experience with OpenAI Agents SDK and Temporal workflows.
Experience with backend/frontend stacks including GraphQL, MCP, REST APIs, React, and cloud platforms GCP (Kubernetes/GKE) and AWS (ECS, EC2).
Work Experience Required: 6+ years in Software Engineering or related fields explicitly stated.
Experienced software engineer who thinks in terms of system design and architecture with ownership of end-to-end AI features.
Practitioner of evals-first approach for AI agent design emphasizing measurable evaluation and iterative improvement.
Comfortable working independently across AI/ML programming, devops, full-stack development, and cloud observability in complex distributed systems.