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Remote Mask Designer Jobs in Chicago, IL (NOW HIRING)

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Remote Mask Designer information

What is a remote mask designer?

A Remote Mask Designer is a professional who creates photomasks used in semiconductor manufacturing, such as for integrated circuits or microchips, while working from a remote location. They use specialized design software to lay out patterns that will be transferred onto silicon wafers during chip fabrication. Remote Mask Designers collaborate with engineers and fabrication teams, often communicating via digital tools to ensure that the mask designs meet technical specifications and manufacturing standards. Their role is crucial in the electronics industry, as precise mask design directly impacts the performance and yield of semiconductor devices.

How does a remote mask designer typically collaborate with fabrication teams to ensure design accuracy and manufacturability?

As a Remote Mask Designer, you will frequently interact with fabrication engineers and process specialists through virtual meetings, shared design platforms, and collaborative tools. Clear communication is essential to address design specifications, resolve layout challenges, and incorporate feedback promptly. You may be expected to review manufacturing constraints, participate in design reviews, and make iterative adjustments to mask layouts. This collaborative approach helps ensure that the final photomask designs meet both technical and production requirements while minimizing costly errors.

What are the key skills and qualifications needed to thrive as a remote mask designer, and why are they important?

To thrive as a Remote Mask Designer, you need a strong background in semiconductor physics, photolithography, and layout design, typically supported by a degree in electrical engineering or a related field. Expertise with CAD tools such as Cadence, Mentor Graphics, or KLayout, along with knowledge of design rule checking (DRC) and layout-versus-schematic (LVS) verification, is essential. Attention to detail, problem-solving abilities, and effective remote communication are vital soft skills in this role. These skills ensure the creation of accurate and manufacturable mask designs critical for chip fabrication and timely project delivery in a remote work environment.

What is the difference between Remote Mask Designer vs 3D Mask Modeler?

AspectRemote Mask Designer3D Mask Modeler
Required SkillsDesign software proficiency, creativity, understanding of mask materials3D modeling, sculpting, software like ZBrush or Blender
Work EnvironmentRemote, design studios, costume shopsRemote, 3D modeling studios, special effects companies
Industry UsageFashion, cosplay, theatrical costumesFilm, theater, special effects

Remote Mask Designers focus on creating visual mask designs using graphic tools, often for fashion or cosplay. 3D Mask Modelers specialize in sculpting detailed 3D models for manufacturing or special effects. Both roles require creative skills, but differ in technical tools and industry applications.

What are the most commonly searched types of Mask Designer jobs in Chicago, IL?

The most popular types of Mask Designer jobs in Chicago, IL are:

Remote Mask Designer jobs near you

Senior AI Engineer / Senior AI Platform Engineer - Agentic AI

Stratedge IT Consulting INC

Chicago, IL • On-site, Remote

$82/hr

Contractor

Posted 8 days ago

Key responsibilities

  • Design and develop multi-agent AI systems and autonomous workflows for enterprise use cases.

  • Build reusable AI platform capabilities, including governance, operational controls, and API-driven services.

  • Design and implement orchestration frameworks for agent communication, memory architectures, and knowledge systems.

Job description

Job Title : Senior AI Platform Engineer - Agentic AI
Location : Chicago, IL 
Client: TCS
Rate: $82/hr on W2
Positions: 2
JD :
Job Description
Senior AI Engineer - Agentic AI Platform
Location
Chicago, IL (Hybrid)
· 3 days onsite (Tuesday to Thursday)
· Remote Monday and Friday
Position Summary
We are seeking a highly skilled Senior AI Engineer to help design and build an enterprise-scale Agentic AI platform that enables multiple business domains to develop, deploy, monitor, and govern autonomous AI agents.
This role goes beyond traditional LLM application development and requires hands-on expertise in agent orchestration, AI platform architecture, model governance, memory management, observability, cost attribution, multi-agent systems, and scalable cloud-native AI solutions.
The ideal candidate will have experience building production-grade AI systems using Azure AI Foundry, LangChain, LangGraph, vector databases, API gateways, and modern AI engineering practices. The individual should be comfortable making architecture decisions, evaluating technology trade-offs, and designing enterprise-ready solutions that support security, scalability, monitoring, and cost control.
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Key Responsibilities
Agentic AI Solution Development
· Design and develop sophisticated multi-agent AI systems for enterprise use cases.
· Build autonomous and semi-autonomous AI workflows using Agentic AI patterns.
· Implement supervisor-worker, sequential, orchestration, choreography, ReAct, Planner-Executor, and Writer-Critic agent architectures.
· Develop scalable agent communication and execution frameworks.
· Design closed-loop AI workflows with validation, retry, evaluation, and feedback mechanisms.
Enterprise AI Platform Engineering
· Build reusable AI platform capabilities consumed by multiple business teams.
· Implement enterprise-grade AI governance and operational controls.
· Design API-driven AI service architecture with:
o Rate limiting
o Quota management
o Multi-tenant usage tracking
o Cost attribution
o Authentication & authorization
o Audit logging
· Enable structured onboarding and lifecycle management of AI agents.
Multi-Agent Orchestration
· Design orchestration frameworks where agents communicate through:
o Direct calls
o Event-driven architectures
o Message queues
o Publish-subscribe patterns
· Implement choreography and conductor-based execution models.
· Evaluate technologies such as Kafka, Azure Durable Functions, Service Bus, and event-driven workflows.
AI Memory & Knowledge Systems
· Design short-term and long-term memory architectures.
· Implement:
o Vector databases
o Semantic caching
o Conversation memory
o Agent state persistence
o Retrieval-Augmented Generation (RAG)
· Develop knowledge orchestration frameworks supporting agent collaboration.
Ontology & Graph-based Intelligence
· Work with graph databases and enterprise knowledge models.
· Support ontology-driven AI applications.
· Build knowledge graphs that enable relationship-based reasoning and signal generation.
· Design systems that combine structured, unstructured, and graph-based knowledge sources.
Model Governance & FinOps
· Implement AI consumption governance across business domains.
· Track:
o Token usage
o Model consumption
o API utilization
o Operational costs
· Create chargeback/showback mechanisms for enterprise teams.
· Support AI FinOps reporting and capacity planning.
Reliability, Monitoring & Observability
· Design observability frameworks for AI applications.
· Monitor:
o Agent executions
o Tool usage
o Latency
o Hallucinations
o Failure rates
o Model quality
· Create dashboards and operational metrics for enterprise AI workloads.
Responsible AI & Security
· Implement:
o Guardrails
o Safety controls
o Prompt protection
o Data masking
o PII protection
o Human-in-the-loop validation
· Ensure compliance with enterprise security and governance policies.
· Build secure agentic systems handling sensitive business data.
AI Evaluation & Optimization
· Develop frameworks for:
o Agent evaluation
o Tool evaluation
o Response quality measurement
o Closed-loop evaluation
o Hallucination detection
· Apply advanced AI engineering techniques including:
o Context engineering
o Prompt engineering
o Retrieval optimization
o Agent tuning
o AI system benchmarking