Senior Staff AI Engineer

We Are:

At Synopsys, we’re transforming IT operations by embedding intelligence into the core of infrastructure systems. From compute clusters to observability stacks, we are building agentic AI capabilities that automate operational tasks, enhance system reliability, and accelerate decision-making.

You Are:

You are a passionate AI/ML engineer or software developer who thrives at the intersection of artificial intelligence and real-world infrastructure. You bring a deep understanding of Python and a curiosity for system-level challenges, eager to build intelligent agents that automate, optimize, and revolutionize IT operations at scale. You excel at translating complex ideas into robust, production-grade solutions and enjoy collaborating with architects, SREs, and platform teams to bring innovative concepts to life. You take ownership of your work, value clean, maintainable code, and are motivated by the impact your solutions have on business outcomes.

You are energized by the opportunity to work with large language models (LLMs), telemetry, and automation logic, transforming them into sophisticated agents that deliver tangible value. You are experienced in integrating AI with real-time infrastructure signals and are excited by the challenge of orchestrating agents within complex automation workflows. You keep pace with emerging technologies and frameworks, and you are as comfortable deploying and iterating on solutions in production as you are designing elegant architectures. Your collaborative mindset, strong communication skills, and openness to feedback drive you to continuously learn and push the boundaries of what’s possible.

Above all, you are a builder who relishes turning visionary ideas into reliable, impactful systems. You are organized, self-directed, and thrive in a fast-paced, high-impact environment where your work helps redefine the future of IT through intelligent automation.

What You’ll Be Doing:

• Design, build, and maintain intelligent agent systems that automate IT functions such as health diagnostics, workload tuning, ticket triage, and cost visibility.
• Implement agent orchestration patterns using frameworks like LangGraph, CrewAI, or LangChain to enable collaborative and scalable agent behaviors.
• Integrate agents with infrastructure signals (logs, metrics, APIs) and embed them seamlessly into existing automation workflows.
• Develop grounding pipelines with retrieval-augmented generation (RAG) techniques to contextualize LLM behavior using internal knowledge, telemetry, and documentation.
• Collaborate closely with Principal Engineers, architects, and cross-functional teams to refine agent designs and ensure robust, scalable deployments.
• Deploy, monitor, and iterate on AI agents in both cloud and on-premises production environments, ensuring reliability and performance.
• Write clean, maintainable Python code and contribute to a growing internal library of agentic capabilities and best practices.
  
  

The Impact You Will Have:

• Drive the transformation of traditional IT operations through intelligent automation, reducing manual effort and increasing operational efficiency.
• Accelerate incident response and problem resolution by empowering AI agents to analyze, reason, and act on real-time infrastructure data.
• Enhance visibility and decision-making across compute, cloud, and storage environments with data-driven insights generated by intelligent agents.
• Shape the next generation of agentic AI services that fundamentally improve infrastructure monitoring, support, and optimization.
• Contribute to a culture of innovation by collaborating on new architectures, frameworks, and methodologies for AI-powered IT automation.
• Establish Synopsys as a leader in intelligent infrastructure by delivering solutions that are reliable, scalable, and impactful at enterprise scale.
  
  

What You’ll Need:

• 5+ years of hands-on experience in AI/ML engineering, backend systems, or automation development, with recent exposure to LLMs or intelligent agents.
• Expertise in Python, with a proven track record of building APIs, automation workflows, or scalable backend services.
• Familiarity with modern LLM platforms (OpenAI, Azure OpenAI, Anthropic) and experience with RAG or prompt engineering techniques.
• Working knowledge of agent orchestration frameworks such as LangGraph, LangChain, CrewAI, or related tools.
• Experience integrating observability signals (logs, metrics, traces) into automation and agentic systems.
• Comfort working in Linux-based environments and with large-scale compute or storage systems.
• Preferred: Experience with orchestration tools like Airflow, exposure to graph modeling (Neo4j, CMDBs), or experience in context-aware systems.
• Preferred: Understanding of MLOps, DevOps practices, or AI service deployment pipelines, and background in EDA, HPC, or enterprise IT support environments.
  
  

Who You Are:

• A builder who thrives on turning ideas into reliable, running code.
• Comfortable operating across AI, infrastructure, and automation domains.
• Collaborative, communicative, and values open feedback and iteration.
• Organized, self-directed, and driven to execute with excellence in a dynamic environment.
• Curious and passionate about intelligent systems and their transformative potential for IT.
  
  

The Team You’ll Be A Part Of:

You’ll join a lean, high-impact team operating in startup mode within enterprise IT. Our mission is to build foundational agentic AI capabilities that span compute, cloud, storage, and service management—reshaping how infrastructure is monitored, supported, and optimized at scale. You’ll work closely with Principal Engineers, platform teams, SREs, and automation experts to define and deliver the future of intelligent infrastructure.

Rewards and Benefits:

We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.

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