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Mid-level backend role with AI/LLM focus in Bangalore increases applicant competition.
Backend and model-serving expertise is moderately transferable across industries with AI infrastructure needs.
Explicit 6–10 years plus mandatory Python, Kubernetes, and model-serving skills enforce strict shortlisting.
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Lead the production systems for Context Services by turning complex AI/ML/LLM analytical solutions into reliable, production-grade software services.
Design and develop robust, low-latency APIs and system architectures supporting thousands of concurrent users with sub-second responses.
Act as a technical liaison with Platform Engineering to integrate core infrastructure and build scalable AI pipelines and workflows.
6–10 years of experience in Software Engineering, Backend Engineering, or Systems Engineering with exposure to AI, ML, or LLM-based production systems.
Strong proficiency in Python and experience with building high-concurrency applications, asynchronous programming, or REST/gRPC APIs.
Experience with containerization technologies (Docker) and deployment environments such as Kubernetes or cloud platforms.
Work Experience Required: 6–10 years in relevant fields as described above.
Experienced in architecting and scaling complex AI-driven backend systems with real-time, high-concurrency requirements.
Ability to collaborate cross-functionally with product, architecture, and AI/ML teams to translate complex data problems into scalable software solutions.
Comfortable bridging between AI/ML applied science teams and platform engineering, with familiarity in AI lifecycle components like model serving and vector databases.