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Senior, niche founding AI role at a small Bengaluru startup reduces applicant density.
High because role requires specialized LLM-native app and production distributed-systems expertise.
High due to explicit 8+ years and mandatory production LLM, distributed systems, and security experience.
Own and improve production systems that ensure autonomous AI agents are trustworthy and reliable, including model steering, memory architecture, orchestration, latency optimization, deployment, and operator tooling.
Enhance agent memory systems, runtime and scheduling reliability, and add new capabilities and tools to deployed agents, including live system debugging and benchmarking models for price, latency, and quality.
Operate in a fast-changing startup environment addressing evolving customer needs with hands-on ownership of distributed and stateful AI agent systems.
8+ years of software engineering experience with real production ownership of distributed or stateful systems and demonstrated incident response and resolution.
Strong experience building on LLMs beyond demos, including agent frameworks, tool integration, context management, and evaluation.
Proficiency in Python and shell scripting in production; comfort with TypeScript/Node.js; emphasis on writing testable, maintainable code using standard libraries.
Solid systems design knowledge including append-only logs, idempotent reconciliation, event folding state machines, and read-only debugging tools.
Technical operator accustomed to debugging, benchmarking, and enhancing complex AI-driven production systems with attention to reliability and predictability.
Experienced in combining classic software engineering with LLM-driven native application design and understands the failure modes beyond demo success.
Disciplined engineer who prioritizes automated testing, evidence-based decision making, and maintains high code quality and documentation standards.