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Bengaluru senior GenAI role at a pre-Series A startup attracts moderate applicant density given niche senior specialization.
High because deep GenAI, agent orchestration, and security-domain experience are strongly domain-specific.
High due to explicit 10+ years requirement plus mandatory hands-on Generative AI and specific tech stack.
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Own design and architecture of end-to-end Generative AI and agentic systems integrating LLM-backed services with the company’s security platform.
Build and improve agentic workflows using LangChain, LangGraph, MCP, RAG pipelines, and vector databases on AWS/GCP cloud infrastructure.
Lead model-selection strategy balancing quality, latency, cost, security, and data-handling; mentor engineers and raise engineering standards for AI services in production.
10+ years overall engineering experience, including 3+ years hands-on Generative AI / LLM-based solutions.
Proven experience designing and architecting AI solutions with personal ownership of built systems.
Deep expertise with agent orchestration frameworks (LangChain/LangGraph), MCP, RAG, vector databases, multiple LLMs/SLMs, and GenAI platforms like AWS Bedrock or Google Vertex AI.
Strong fundamentals in scalable, reliable distributed services; working knowledge of cloud (AWS/GCP) and cloud security fundamentals.
Role based in Bengaluru, India.
Senior-level engineer comfortable owning system architecture end-to-end in an early-stage startup environment with wide technical scope.
Expertise with agentic GenAI stacks and security-sensitive AI product contexts preferred.
Hands-on builder with strong judgment on architecture trade-offs, able to work closely with product and engineering leadership to translate ambiguous problems into robust AI solutions.