Agentic Ai Engineer / Senior Engineer

Job Summary

We are seeking a highly motivated Agentic AI Engineer to build next-generation AI-powered engineering solutions that automate and accelerate software development workflows. The role combines expertise in Agentic AI, Large Language Models (LLMs), and AI-driven automation with strong fundamentals in embedded systems, device drivers, operating systems, computer architecture, and SoC platform enablement.

You will develop intelligent AI agents and workflows spanning the entire software development lifecycle, from requirements analysis and code generation to testing, debugging, validation, release management, and engineering productivity optimization.

Key Responsibilities

• Design, develop, and deploy Agentic AI solutions for engineering automation and productivity.
• Build AI agents and multi-agent systems for:
  • Code generation, review, and analysis
  • Build and CI/CD automation
  • Test generation, execution, and validation
  • Failure triage and root-cause analysis
  • Release automation and engineering knowledge management
• Develop AI applications leveraging LLMs, RAG, agent orchestration frameworks, and MCP-based tool ecosystems.
• Integrate AI solutions with source control, issue tracking, test infrastructure, and engineering workflows.
• Design human-in-the-loop and autonomous workflows with appropriate governance and safety controls.
• Collaborate with software, hardware, architecture, and infrastructure teams to identify high-impact AI opportunities.

Minimum Qualifications

• Bachelor’s degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
• OR Master’s degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience.
• OR PhD in Engineering, Information Systems, Computer Science, or related field.
• 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.

Embedded Systems Expertise

• Strong experience in embedded Linux, Android, RTOS, Zephyr, QuRT, or similar platforms.
• Hands-on experience in device driver development and debugging for PCIe, USB, I2C, SPI, UART, GPIO, DMA, storage, and networking peripherals.
• Deep understanding of ARM and/or RISC-V architectures, including boot flows, exception handling, interrupts, memory management, cache coherency, power management, and multicore systems.
• Experience with BSP development, SoC bring-up, platform enablement, and hardware/software integration.
• Proficiency in system-level debugging using crash dumps, kernel logs, traces, JTAG, and performance analysis tools.
• Strong knowledge of OS internals, virtualization, concurrency, synchronization, security architecture, and performance optimization.
• Experience in pre-silicon and post-silicon development environments.

Preferred Qualifications

• Experience with LangGraph, AutoGen, CrewAI, Semantic Kernel, LangChain, or similar agent frameworks.
• Experience deploying production AI solutions using GPT, Claude, Gemini, or open-source LLMs.
• Experience developing AI-powered developer productivity, testing, debug, or automation tools.
• Familiarity with cloud-native architectures, distributed systems, AI governance, and workflow automation platforms.
• Experience with Linux kernel, Android platform development, Secure Boot, TrustZone, Hypervisors, and firmware architectures.
• Exposure to Snapdragon platforms, emulation, simulation, virtual platforms, or FPGA-based development environments.

Ideal Candidate

The ideal candidate combines deep expertise in AI, Agentic Systems, and LLMs with strong experience in embedded software, device drivers, operating systems, ARM/RISC-V architecture, and SoC platform development. They are passionate about applying AI to transform engineering workflows and accelerate platform development through intelligent automation.

Impact

You will play a key role in defining the future of AI-driven engineering by building autonomous systems that significantly improve software quality, engineering productivity, development velocity, and product execution across the organization.