3 hours ago
Responsibilities
- Own the shared AI platform architecture, including the agent runtime, orchestration, shared services, and reusable abstractions.
- Define the technical roadmap, sequence platform work, make build-versus-buy decisions, and communicate tradeoffs to engineering and business leadership.
- Write production-grade reference implementations that other engineers can extend and specialize.
- Establish coding, evaluation, security, cost, and observability standards through libraries and templates.
- Personally solve difficult scaling, latency, cost, reliability, non-determinism, and cross-agent coordination problems.
- Design platform-level guardrails, approval gates, autonomy limits, human-in-the-loop patterns, and other safe-autonomy primitives.
- Review critical designs and pull requests, mentor engineers through code, and raise engineering quality through influence.
- Measure and communicate the platform’s impact on delivery speed, operating cost, and reliability.
Requirements
- Deep fundamentals in algorithms, data structures, distributed systems, and system design.
- Track record of owning platforms or frameworks that other engineers build on.
- Production experience shipping and operating LLM or agent systems for real users.
- Strong object-oriented programming experience with Python, C#, or Java.
- Experience with REST and event-driven API design, asynchronous and concurrent systems, Azure Functions or App Service, Service Bus, SQL, data modeling, Git, CI/CD, testing, and scalable system design.
- Experience with Azure OpenAI or LLM APIs, agent runtime and orchestration design, LangChain or LangGraph, Semantic Kernel, tool use or function calling, RAG at scale, MCP servers and tools, multi-agent patterns, and A2A protocols.
- Knowledge of AI security and robustness, guardrail frameworks, human-in-the-loop design, drift and hallucination monitoring, prompt and model version management, token cost control, evaluation and regression frameworks, and outcome instrumentation.
- Strong technical judgment, ability to simplify complex platforms, tolerance for AI non-determinism, and clear executive communication.
- Preferred experience includes vector database internals, LLM observability, fine-tuning, multimodal AI, Salesforce, Dynamics 365, Gainsight, infrastructure as code, Azure Data Factory, TypeScript, and Node.js.
- Candidates are encouraged to provide a GitHub repository, deployed system, or detailed write-up of a shipped project.
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About Commvault
Commvault (NASDAQ: CVLT) is a leader in unified resilience at enterprise scale. In a constantly evolving threat landscape, Commvault keeps customers ready by unifying data security, identity resilience, and cyber recovery, on one cloud-native, AI-enabled platform. Customers trust Commvault to conduct the fastest, most complete recoveries – not just their data, but their entire business. Purpose-built for the agentic enterprise, Commvault also enables organizations to safely embrace AI while protecting against AI-driven threats.