Director, Software Engineering | Enterprise AI Platforms, Infrastructure & Automation

Overview

Lead Cisco's Bangalore-based engineering pod for Enterprise AI Platforms & Infrastructure, acting as a hands-on player-coach for the MyAgent and Circuit agentic AI platforms, two levels below the VP.

What you'll do

• Act as the engineering escalation authority for MyAgent and Circuit, leading hands-on debugging, root-cause forensic analysis, and kernel/runtime patch development for complex production failures.
• Bridge SRE/L2 operational support and core platform architecture, delivering zero-regression hotfixes.
• Architect and build an end-to-end, agent-driven test automation harness, including LLM-as-a-judge scoring, multi-agent simulation loops, deterministic task verification, and golden dataset benchmarking.
• Maintain quality gates with >99% test pass rates across functional, regression, experimental, and safety workflows.
• Lead performance profiling, stress testing, and concurrency load and latency validation across on-premise GPU clusters and cloud runtimes.
• Optimize latency, token throughput, context cache utilization, and resource efficiency.
• Deliver modular, embeddable SDKs, React components, and headless APIs for thousands of Cisco software engineers.
• Recruit, mentor, and lead a high-density pod of 6–10 systems, AI, and test automation engineers in Bangalore through code reviews, technical design RFCs, and pair programming.
• Direct software systems development, application engineering, and software quality assurance for cloud-based and agentic AI platforms.

What you'll need

• Bachelor's degree (B.Tech / B.E. / B.S.) in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, Artificial Intelligence, or a related quantitative STEM discipline from an accredited institution.
• 10+ years of progressive software engineering experience.
• 3+ years leading high-performing technical engineering teams.
• 2+ years of hands-on production experience with LLMs, agentic workflows, or AI platforms.
• Expert-level fluency in Python and modern TypeScript/JavaScript.
• Strong working proficiency in Go, C++, or Rust for systems-level performance tuning.
• Deep practical experience with Model Context Protocol (MCP), LangGraph, LlamaIndex, vLLM, Triton Inference Server, PyTorch, and vector databases.
• Demonstrated track record of designing large-scale distributed test harnesses, performance testing tools (k6, Locust, JMeter), browser automation (Playwright), and AI evaluation frameworks (Ragas, DeepEval, Promptfoo, Eval Studio).

Nice to have

• Master's degree (M.Tech / M.S.) or Ph.D. in Computer Science, Artificial Intelligence, Distributed Systems, Machine Learning, or Software Engineering from a premier tier-1 engineering institution or top global research university.
• Solid understanding of GPU compute infrastructure, CUDA memory management, high-density server configurations, and container orchestration (Kubernetes, Docker).
• Academic, research, or open source contributions in distributed systems, compiler optimization, GPU parallel computing (CUDA/Triton), formal software verification, major contributions to tier-1 open-source AI frameworks/benchmarks, or recognized technical patents in AI/systems engineering.
• Proven ability to lead from the front, write production code, conduct deep architectural reviews, and inspire an elite engineering culture without relying on bureaucratic middle management.
• Excellent analytical, written, and verbal communication skills, with the ability to influence and present technical architectures across engineering, product, and executive leadership.

Details

• Location: Bangalore, India.