AI Architect

We Are:

At Synopsys, we drive the innovations that shape the way we live and connect. Our technology is central to the Era of Pervasive Intelligence, from self-driving cars to learning machines. We lead in chip design, verification, and IP integration, empowering the creation of high-performance silicon chips and intelligent software systems. Join us to transform the future through continuous technological innovation.

As part of our Generative AI / Agentic AI initiatives, we are building next-generation intelligent applications powered by LLMs, workflows, tools, memory, and autonomous decisioning. Our team is focused on delivering scalable, production-grade AI full-stack solutions that create measurable business impact.

You Are:

You are a hands-on senior engineering leader with a passion for building production-grade  agentic AI systems and  AI full-stack applications . You thrive in fast-paced, collaborative environments and enjoy solving complex problems across orchestration, memory, reasoning, backend systems, and user experience. You bring strong technical depth in modern AI application development, combined with the leadership skills to guide teams, mentor engineers, and drive delivery excellence.

You are excited by the challenge of developing workflow-driven agentic systems using frameworks such as  ADK, NAT, and other agent orchestration frameworks , and you understand how to combine LLMs, tools, memory, retrieval, and guardrails into reliable applications. You balance innovation with engineering rigor and are committed to building secure, scalable, and responsible AI solutions.

What You’ll Be Doing:

• Design, build, and deploy  agentic AI platforms, applications and  AI full-stack solutions using frameworks such as  ADK, NAT, and similar agent/workflow platforms .

• Develop intelligent workflows for planning, reasoning, task decomposition, tool execution, reflection, and multi-step orchestration.

• Implement and optimize  memory architectures , including  Semantic memory, Procedural memory, Episodic memory, Working/session memory etc.

• Build integrations with enterprise tools, APIs, knowledge bases, databases, search systems, and external services using  tool calling ,  function calling , and  MCP/equivalent connector patterns where applicable.

• Develop backend services, orchestration layers, APIs, and supporting full-stack components for AI applications, including human-in-the-loop experiences and operational dashboards.
• Implement  RAG pipelines , vector search, knowledge retrieval, prompt orchestration, and contextual grounding for agents.
• Design robust agent state management, persistence, retry, fallback, and recovery mechanisms for workflow-driven systems.
• Establish evaluation frameworks for agent quality, memory relevance, tool-use success, trajectory quality, hallucination reduction, latency, cost, and safety.
• Build observability and monitoring for agentic systems, including tracing, logging, prompt/version tracking, workflow telemetry, and incident analysis.
• Apply guardrails, policy controls, validation layers, and secure design practices to ensure safe and responsible AI behavior.
• Mentor engineers, drive design reviews, establish best practices, and contribute to engineering standards for agentic application development.
• Collaborate with product managers, designers, researchers, platform teams, and business stakeholders to translate requirements into scalable AI solutions.

The Impact You Will Have:

• Accelerate Synopsys’ adoption of  agentic AI through scalable, workflow-driven applications.
• Enable delivery of robust AI systems that combine LLMs, tools, memory, and orchestration to solve high-value business problems.
• Improve engineering productivity and business efficiency through reusable agentic patterns, platform components, and best practices.
• Raise the technical maturity of the team through mentorship, code quality, architecture guidance, and knowledge sharing.
• Help establish Synopsys as a leader in responsible, enterprise-grade AI application development.

What You’ll Need:

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, AI/ML, or related field. PhD is a plus.

• Minimum 10 years of software engineering experience , including strong hands-on experience in building and shipping production systems.

• Proven experience delivering  AI/ML, GenAI, or agentic AI applications in production environments.
• Strong proficiency in  Python and at least one of  TypeScript/JavaScript, Java, C++, or Go .
• Experience with  ADK, NAT, LangGraph, AutoGen, CrewAI, Semantic Kernel, or similar agentic development frameworks .
• Strong understanding of:

  • OpenAI API Specification

  • LLM application design

  • Workflow orchestration
  • Prompt engineering
  • Tool/function calling
  • RAG architectures
  • Memory systems for agents
  • Multi-agent collaboration patterns
• Experience with  vector databases , search systems, embeddings, and knowledge retrieval pipelines.
• Experience building  AI full-stack applications , including backend APIs/microservices and frontend or user-facing AI experiences.
• Familiarity with cloud platforms such as  AWS, GCP, or Azure , and container/orchestration technologies such as  Docker and Kubernetes .
• Experience with  CI/CD , Git-based development, testing, and Agile/Scrum practices.
• Strong understanding of observability, evaluation, guardrails, security, privacy, and responsible AI practices.
• Experience in semiconductor, EDA, developer productivity, or enterprise software domains is a plus.

Who You Are:

• A strong systems thinker and pragmatic problem solver.
• A hands-on technical leader who can move between architecture and implementation.
• An effective communicator who can explain complex AI concepts to diverse audiences.
• A collaborative team player who values inclusion, curiosity, and continuous learning.
• A mentor who raises the bar for engineering quality and technical excellence.
• Ethical, detail-oriented, and committed to responsible AI deployment.