Software Engineer

Overview

Join Cisco's Industrial IoT engineering team to build AI-native software for industrial networking, security, observability, and edge computing, collaborating across networking, cybersecurity, embedded systems, and edge AI.

What you'll do

• Build AI applications and agents, developing and evaluating industrial applications and agentic workflows using LLMs, SLMs, machine learning, computer vision, RAG, MCP, and tool calling.
• Apply AI to industrial networking and security, developing capabilities for smarter network operations, troubleshooting, observability, anomaly detection, and threat detection.
• Develop Edge AI, fine-tuning, optimising, and deploying ML models and SLMs on edge platforms, balancing model quality, memory, compute, and latency for reliable on-device inference.
• Practice AI-first product development, using coding agents and agentic workflows across design, implementation, debugging, testing, and review.
• Collaborate with domain and AI engineers to deliver reliable software, validating correctness, performance, and security.

What you'll need

• Bachelor's or Master's degree in Computer Science, Computer Engineering, AI/ML, or a related field, with 1–3 years of relevant experience.
• Strong Python skills and proficiency in another language such as C, C++, Go, or Java.
• Sound foundation in data structures, algorithms, software design, and debugging.
• Hands-on AI/ML or LLM/agent application development using tools such as PyTorch, TensorFlow, or Hugging Face, including model integration and evaluation.
• Experience using AI coding agents such as Codex, Cursor, Claude Code, or equivalent tools, with the judgment to validate generated code.

Nice to have

• Familiarity with networking domain such as TCP/IP or security protocols experience.
• Experience in development and validation of peripheral interfaces (e.g. PCI, PCIe, I2C, SPI, UART, GPIO, Ethernet).
• ML/DL and LLM foundations, with exposure to SLM adaptation (fine-tuning, LoRA/PEFT, distillation, quantization) and on-device inference using TensorFlow Lite or llama.cpp under resource constraints.
• Experience with RAG, MCP, or agent orchestration frameworks such as LangGraph; familiarity with A2A.
• Open-source AI contributions, research, hackathons, or independently developed applications.

Details

• Location: Bangalore, India.