"The person who dreams in S-parameters and wakes up debugging field solvers."

We need a hardcore HFSS expert who is equally excited about artificial intelligence. You will be the quality backbone of Design Forge — the person who knows whether our AI copilot is producing correct, useful, and elegant electromagnetic designs. If you’ve ever wished HFSS could read your mind, this is your chance to build that future.

You will own product quality, validate every release, and become the living encyclopedia of RF/EM best practices that powers our knowledge base.

What You'll Do

• Own end-to-end quality validation of Design Forge’s AI-generated HFSS outputs — geometry, materials, boundary conditions, mesh settings, and post-processing accuracy.
• Build and curate the Design Forge Knowledge Base: canonical design patterns, simulation templates, gotchas, and reference benchmarks that train our AI to think like a senior RF engineer.
• Test every major release (V8 and beyond), surface bugs, log detailed reproduction steps, and work directly with engineering to close the loop.
• Record high-quality demo content — walkthroughs, tutorials, and comparison studies — that showcases what Design Forge can do and educates our user community.
• Propose and evaluate new features by translating real-world RF design workflows into product requirements the engineering team can act on.
• Validate data correctness across simulation types (driven modal, eigenmode, transient) and flag discrepancies before they reach users.

Must-Haves

• Deep HFSS expertise (5+ years). You should have practical experience working with HFSS in any of our core end markets: Aerospace and Defense, Signal/Power Integrity, and Semiconductor/IC.
• AI-forward mindset. You actively use AI tools in your daily engineering work — prompt engineering, copilot-assisted scripting, AI-driven design exploration. As AI evolves and improves, you will as well.
• Excellent written and verbal communication — you’ll be producing demos, internal reports, and customer-facing content.
• Self-starter mentality. We are a small, fast team. You will own your domain from Day 1.

Nice-to-Haves

• Experience with other EDA Tools and solvers (AWR Microwave Office, ADS, CST, Virtuoso RF, etc).
• Familiarity with “vibe coding” and the evolving AI software development paradigm: building quick, deployable internal tools using AI-assisted development.
• Contributions to open-source RF/EM projects or published research.

Why Design Forge?

You will be the single most important voice shaping the accuracy and usability of an AI platform that thousands of RF engineers will rely on. This isn’t a support role — it’s a technical leadership position where your HFSS mastery directly determines product quality. If you want your expertise to have outsized impact, this is the seat. Career growth and opportunities will be available to those who create significant value. 

"The strategist who turns user pain into a product roadmap — and then makes sure we ship it."

Design Forge is at the inflection point every startup dreams about: working product, early traction, and a massive market waiting to be captured. We need a Product Manager who can set the strategic direction, ruthlessly prioritize our pipeline, and ensure every feature we build moves us closer to product-market fit.

This role is critical. You will own the “what” and “why” of our product — managing the app team and the PM function and reporting to the CEO. You’ll be the bridge between our users, our engineers, and our business goals.

What You'll Do

• Define and own the product roadmap. Prioritize the pipeline across current features (Projects, Memory Pipeline, Forge Trail, Script Library) and future bets.
• Drive product-market. Build and engage with the early adopter user community. Engage in  continuous user research, feedback loops, and data-driven decision-making. Talk to users weekly — not quarterly.
• Manage and structure the app/PM group, establishing clear processes, sprint cadences, and accountability so that execution is predictable and transparent.
• Generate and evaluate new feature ideas by synthesizing user requests, competitive intelligence, and technical feasibility.
• Own go-to-market coordination for new features — working with engineering on release plans and with marketing on positioning and launch.

Must-Haves

• Proven PM experience (4+ years) in a technical product, ideally B2B SaaS or developer tools. You understand the difference between shipping features and solving problems.
• AI-native product thinking. You use AI tools daily and can articulate how AI changes product strategy, UX paradigms, and competitive moats. AI competency is a baseline expectation for every role at Design Forge in 2026.
• Exceptional prioritization instincts. You can look at a list of 50 feature requests and identify the three that will move the needle.
• Strong communication skills — written strategy docs, verbal stakeholder alignment, and the ability to say “no” with clarity and empathy.
• Comfort with ambiguity and speed. We are pre-Series A. You will build the PM playbook as you go.

Nice-to-Haves

• Domain knowledge in engineering simulation, CAD/CAE tools, or the RF/EM ecosystem.
• Experience with AI-powered products or LLM-based applications.
• Technical background (CS, engineering) that lets you speak credibly with developers and our deep domain customers.
• Startup drive — especially at the 5–30 person stage where process meets chaos.

Why Design Forge?

You will shape the product strategy of a platform that is redefining how engineers interact with simulation software. This is a ground-floor opportunity with direct CEO partnership, high autonomy, and the rare chance to build a PM function from scratch at a company with real technology and real users.

We're hiring a Full Stack AI Engineer to lead the design, development, and deployment of production-grade LLM and autonomous agent systems — while also owning the full stack application that delivers them to users. This is a hands-on, high-ownership role for someone who has shipped both AI systems and production software and wants to define technical foundations from the ground up.

You will own core AI architecture decisions, build and maintain our desktop application and its real-time backend, and work closely with leadership on product direction. We're building systems that operate reliably at scale — not demos or experiments, but production software that integrates with professional engineering APIs.

If you've built real LLM systems, understand their failure modes, can architect a full stack application end to end, and want to push agent-based AI into production — this role is for you.

This role is US-based only. We are a fully remote company but only accepting applicants currently residing in the United States.

What You'll Do

AI & Agent Systems

• Custom code generation agents that understand API semantics and reason about correctness before generating code, including autonomous debugging agents that analyze failures and self-correct

• Multi-agent systems with orchestration patterns, communication protocols, and shared memory for complex multi-step tasks

• Context engineering infrastructure: retrieval systems over technical documentation, context assembly strategies that give LLMs the right information at the right time, and extraction of complex project state

• Model Context Protocol (MCP) servers that expose domain-specific tooling to LLMs

• Evaluation infrastructure — metrics, benchmarks, test harnesses — that drives accuracy from "good enough" to "production reliable"

• Scalable, reliable AI system architectures (inference, orchestration, monitoring)

Full Stack Application & Infrastructure

• An Electron + React desktop application serving as the primary interface for our AI-powered product

• Real-time communication layers using WebSockets for streaming responses, live updates, and event-driven UI

• Data engineering pipelines: ingestion, transformation, and storage of domain-specific data, user telemetry, and model performance metrics

• Python FastAPI backend services including session management, authentication, and integration with the AI orchestration layer

• CI/CD, build tooling, and packaging for cross-platform desktop releases

What We're Looking For

Strong candidates typically have:

• 9+ years of software engineering experience, with demonstrated depth across the full stack — you're an engineer first, not just an AI specialist

• 5+ years AI/ML engineering with production LLM systems (not just research or internal demos)

• Strong experience with Electron and React (or equivalent desktop/web hybrid frameworks)

• Production WebSocket integration for real-time, event-driven applications

• Data engineering experience: building pipelines for ingestion, transformation, storage, and retrieval at scale

• Experience building and deploying multi-agent architectures and agentic AI patterns

• LLM fine-tuning for code generation, and strong background in context engineering, RAG, and retrieval systems

• Deep Python expertise and comfort with complex API integrations (FastAPI, async patterns, subprocess orchestration)

• Ability to reason clearly about tradeoffs (latency, cost, accuracy, reliability)

Strong Plus

• Experience building custom code generation agents or AI coding assistants

• Hands-on work with Model Context Protocol (MCP)

• Background in engineering, CAD, or simulation software domains

• RLHF/RLAIF, or advanced agent frameworks

• Experience designing evaluation frameworks for LLMs and agents

• Windows desktop application development and packaging (installers, code signing, CI/CD for desktop)

• Contributions to open-source ML/AI tooling or infrastructure

• Prior founding-engineer or early-stage startup experience

Startup Mentality Required

We're an early-stage company. There's no playbook, no established processes, and no large team to fall back on. We need someone who thrives in that environment — not someone who tolerates it.

That means:

• You don't wait for specs. You see a gap, you propose a solution, you build it.

• You wear multiple hats without complaint. On Monday you're debugging a WebSocket race condition, on Tuesday you're rearchitecting an agent pipeline, on Wednesday you're reviewing a PR and deploying a hotfix.

• You move fast and ship. Perfection is the enemy. You get it working, get it in front of users, and iterate.

• You're comfortable with ambiguity. Requirements change. Priorities shift. You adapt without losing momentum.

• You want ownership, not just a seat. This isn't a job where you execute someone else's vision — you're shaping the product and the company.

• You've done this before. Prior founding-engineer or early-stage startup experience is a strong signal. You know what "early" really means and you're energized by it, not intimidated.

If you need structure, well-defined roles, or a stable roadmap to do your best work — this isn't the right fit. If chaos is where you come alive, let's talk.

What You Get

• Founding-level ownership of the company's AI stack and application platform

• Real impact on product direction and system design

• High autonomy and technical decision-making authority

• Competitive salary + equity

• Professional development budget

• Remote-friendly, high-performance workstation

• The rare chance to build something from near-zero to production scale

Who This Role Is Not For

• AI-only candidates without substantial software engineering and full stack experience — we need someone who can own the entire product, not just the model layer

• Candidates focused solely on prompt engineering without systems experience

• Those without production deployment experience

• Research-only backgrounds with no shipping responsibility

• Anyone who needs a fully defined scope to be productive — this is a startup, and the scope is "whatever it takes"