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Mid-level SDE title, metro Bangalore location, and common experience band increase candidate competition.
Highly domain-specific platform and LLM orchestration skills limit cross-industry transferability.
Mandatory stack and niche platform expertise (Go, Temporal, LLM orchestration) create stringent screening.
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Own and develop key components of the orchestration platform that manages stateful, long-running AI workflows for enterprise-scale use.
Design and build durable, observable, and recoverable workflow systems using Temporal and LangGraph orchestration with enterprise-grade reliability under production load.
Implement reliability and failure handling including interrupt-and-resume patterns for human-in-the-loop workflows, and build comprehensive observability pipelines using Langfuse and Arize Phoenix.
Work Experience Required: Experience building backend or infrastructure systems; specific years not explicitly mentioned in the JD.
Strong proficiency in Go and Python programming languages.
Hands-on experience with durable execution engines (Temporal, Cadence, or similar), LLM orchestration, self-correcting AI systems, distributed systems fundamentals, observability and tracing systems, gRPC and service mesh architectures, and state management in distributed environments.
AI-native velocity as a default mode of working is mandatory.
Proven ability to take ownership of complex technical projects and deliver them end to end in production environments.
Experienced working with enterprise-grade infrastructure in highly regulated or mission-critical contexts, combining startup agility with operational rigor.
Comfortable driving engineering rigor including code reviews and design discussions, with a focus on reliability, observability, and AI-native development practices.