Ansys, Inc.
Job Overview
We are @ Synopsys, we are transforming IT by building intelligent, agentic systems that think, act, and adapt. Supporting some of the world's most demanding engineering environments—from chip design to high‑performance computing—we are reimagining how infrastructure and operations function through the lens of AI. Our team pioneers the development of agentic IT: AI‑powered agents deeply integrated with infrastructure platforms, observability systems, and automation pipelines, reshaping how issues are detected, resolved, and prevented—enabling faster, smarter, and more autonomous operations across the enterprise.
What You'll Be Doing
Architect and develop agentic IT capabilities that enhance infrastructure operations, workload orchestration, and user‑facing automation.
Build LLM‑powered agents that integrate reasoning, context‑awareness, and real‑time data from telemetry and operational sources.
Design orchestration flows using frameworks like LangGraph, CrewAI, or LangChain, enabling agents to collaborate across tasks and systems.
Implement grounding strategies using retrieval‑augmented generation (RAG) tied to internal documentation, logs, metrics, and CMDBs.
Work closely with infrastructure, observability, and automation teams to embed agents within existing systems and tools.
Lead design patterns and technical guidance for agent lifecycle management, service reliability, and platform governance.
Drive the evolution of infrastructure automation from reactive scripting to proactive, intelligent, and adaptive systems.
Skills & Experience Required
7+ years of experience in AI/ML, software engineering, or intelligent systems, with at least 2 years in LLM‑based or agentic AI development.
Proficiency in Python, with experience building backend systems, APIs, and containerized services.
Hands‑on experience with LLM platforms such as OpenAI, Azure OpenAI, or Anthropic, and techniques like RAG and prompt engineering.
Familiarity with agent orchestration tools (LangGraph, CrewAI, LangChain, AutoGen, etc.).
Experience working with infrastructure data (logs, metrics, traces) and integrating with observability or monitoring systems.
Knowledge of cloud, Linux‑based infrastructure, job schedulers (e.g., LSF), or other large‑scale systems.
Preferred experience includes: Workflow automation tools (e.g., Airflow) for connecting agents into end‑to‑end operational flows; graph‑based context modeling (e.g., Neo4j, CMDB integration) for improving agent reasoning; background in engineering compute environments (EDA, HPC) or experience with storage‑intensive, high‑throughput systems; applying observability feedback loops to drive continuous learning and adaptive agent behavior; exposure to AI service deployment practices such as MLOps, reliability engineering, and platform governance.
Who You Are
A strategic and pragmatic engineer who balances vision with execution.
A strong communicator who can operate across AI, IT, and infrastructure domains.
Highly organized and detail‑oriented, with the ability to manage complex system interactions.
A collaborative team player with a passion for solving real problems through intelligent automation.
Committed to ethical, explainable AI design and responsible deployment practices.
The Team You’ll Join You’ll join a lean, high‑impact team operating in startup mode within IT building new AI capability from the ground up. Our focus is on applying agentic AI to drive transformation across infrastructure, observability, and service delivery. We work closely with platform teams, SREs, cloud architects, and enterprise systems to create reusable, scalable AI capabilities. Our culture is rooted in innovation, autonomy, and a shared mission to design intelligent systems that improve how we build, support, and scale our digital 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. In addition to the base salary, this role may be eligible for an annual bonus, equity, and other discretionary bonuses. The actual compensation offered will be based on a number of job‑related factors, including location, skills, experience, and education. The base salary range for this role is across the U.S.
Equal Employment Opportunity At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.
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What You'll Be Doing
Architect and develop agentic IT capabilities that enhance infrastructure operations, workload orchestration, and user‑facing automation.
Build LLM‑powered agents that integrate reasoning, context‑awareness, and real‑time data from telemetry and operational sources.
Design orchestration flows using frameworks like LangGraph, CrewAI, or LangChain, enabling agents to collaborate across tasks and systems.
Implement grounding strategies using retrieval‑augmented generation (RAG) tied to internal documentation, logs, metrics, and CMDBs.
Work closely with infrastructure, observability, and automation teams to embed agents within existing systems and tools.
Lead design patterns and technical guidance for agent lifecycle management, service reliability, and platform governance.
Drive the evolution of infrastructure automation from reactive scripting to proactive, intelligent, and adaptive systems.
Skills & Experience Required
7+ years of experience in AI/ML, software engineering, or intelligent systems, with at least 2 years in LLM‑based or agentic AI development.
Proficiency in Python, with experience building backend systems, APIs, and containerized services.
Hands‑on experience with LLM platforms such as OpenAI, Azure OpenAI, or Anthropic, and techniques like RAG and prompt engineering.
Familiarity with agent orchestration tools (LangGraph, CrewAI, LangChain, AutoGen, etc.).
Experience working with infrastructure data (logs, metrics, traces) and integrating with observability or monitoring systems.
Knowledge of cloud, Linux‑based infrastructure, job schedulers (e.g., LSF), or other large‑scale systems.
Preferred experience includes: Workflow automation tools (e.g., Airflow) for connecting agents into end‑to‑end operational flows; graph‑based context modeling (e.g., Neo4j, CMDB integration) for improving agent reasoning; background in engineering compute environments (EDA, HPC) or experience with storage‑intensive, high‑throughput systems; applying observability feedback loops to drive continuous learning and adaptive agent behavior; exposure to AI service deployment practices such as MLOps, reliability engineering, and platform governance.
Who You Are
A strategic and pragmatic engineer who balances vision with execution.
A strong communicator who can operate across AI, IT, and infrastructure domains.
Highly organized and detail‑oriented, with the ability to manage complex system interactions.
A collaborative team player with a passion for solving real problems through intelligent automation.
Committed to ethical, explainable AI design and responsible deployment practices.
The Team You’ll Join You’ll join a lean, high‑impact team operating in startup mode within IT building new AI capability from the ground up. Our focus is on applying agentic AI to drive transformation across infrastructure, observability, and service delivery. We work closely with platform teams, SREs, cloud architects, and enterprise systems to create reusable, scalable AI capabilities. Our culture is rooted in innovation, autonomy, and a shared mission to design intelligent systems that improve how we build, support, and scale our digital 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. In addition to the base salary, this role may be eligible for an annual bonus, equity, and other discretionary bonuses. The actual compensation offered will be based on a number of job‑related factors, including location, skills, experience, and education. The base salary range for this role is across the U.S.
Equal Employment Opportunity At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.
#J-18808-Ljbffr