Principal Architect, Simulation Platform at Karman in Remote

Karman is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically orchestrate power and unlock more compute capacity from existing energy infrastructure. For over a decade, we have applied AI to the electric grid — bringing real-time visibility and power-flow control to complex energy infrastructure. Our Karman platform, built on a custom NVIDIA module, brings that same capability to AI data centers, giving operators a way to better use the power already available to them.

We are building the Karman Digital Environment (KDE), a simulation platform that will evolve how Karman is developed, verified, and brought to market. Today, Karman is developed and verified against shared physical systems, including custom NVIDIA-based edge compute units that process sub-millisecond power waveform data and issue real-time control signals to GPU infrastructure. This is a hardware constraint that limits how fast teams can iterate. KDE will remove that constraint, enabling simulation-driven development at scale across every layer of fidelity, from rapid experimentation to high-confidence system validation. This is a technical leadership role reporting to the VP, AI & Applications, with company-wide impact across architecture, product, and customer-facing teams.

Responsibilities

• Own the end-to-end architecture of KDE as the simulation platform for developing, testing, and validating Karman before production deployment.
• Architect systems spanning heterogeneous time domains — from sub-millisecond control paths to system-level orchestration — with coherent time management and deterministic behavior across both.
• Design and evolve the core simulation platform: time synchronization across paced (real-time SIL) and unpaced (batch) execution modes, signal routing and data flow orchestration, deterministic replay and scenario execution, and the platform APIs and data contracts consumed by algorithm, QA, product, and GTM teams.
• Define and maintain the platform's performance envelope — latency, jitter, throughput, and fidelity — and lead optimization across the full stack.
• Serve as the technical authority for simulation and validation methodology, partnering with algorithm, QA, product, hardware, firmware, and GTM teams to align platform capabilities with real-world Karman deployments.
• Build and lead an engineering team spanning real-time systems, simulation infrastructure, power systems modeling, and GPU calibration, while remaining deeply hands-on in architecture and critical technical decisions.
• Represent KDE on a standing cross-functional council with Algorithms, Product, GTM, and QA, arbitrating priorities across the platform's customers and maintaining architectural direction with senior peers.

Minimum Qualifications

• Bachelor's or advanced degree in Electrical Engineering, Computer Engineering, Computer Science, Robotics, Physics, or a related field
• 10+ years in systems architecture, simulation platforms, real-time or hardware-in-the-loop systems, embedded systems, or high-performance distributed platforms
• Experience as a hands-on player-coach leading small, high-performing engineering teams
• A proven track record designing and delivering simulation platforms or large-scale test systems that other engineering teams treat as production hardware, including data ingestion, telemetry, and playback at production scale, and the ability to design platform APIs and data contracts used by multiple teams
• Deep expertise in system-level behavior — scheduling, concurrency, memory access patterns, latency budgets, jitter measurement, and determinism at sub-millisecond scale
• Substantive fluency in the physics of the simulated domain — for this role, AC power distribution, control-loop dynamics, and electrical protection systems — is sufficient to make architectural decisions independently. Candidates from adjacent domains (automotive powertrain, aerospace propulsion, grid simulation, robotics dynamics) who've reached comparable depth will also be considered
• Experience leading or contributing to a novel modeling problem in the platform's domain
• Strong communication skills, with the ability to translate complex system designs for technical and non-technical stakeholders alike
• Willingness to travel up to 25% of time

Enhanced Qualifications (Nice to Have)

• Experience with GPU-based systems or other accelerators, including power and performance tradeoffs
• Experience in data center power infrastructure or hyperscaler energy-aware computing
• Familiarity with AI inference serving systems (vLLM, TensorRT-LLM, Triton) sufficient to reason about workload-driven power dynamics

Salary Range: $200,000 to $240,000 base compensation depending on experience and level, plus stock options. This role spans multiple job levels; final level and compensation will be determined based on the candidate's experience.

Location: This position can be performed remotely from within the United States. Preference will be given to candidates based in or around the Bay Area (CA) or Ann Arbor, MI. Periodic travel to the company’s HQ in Ann Arbor, MI is required.

Our Commitments: Karman values the diversity of our team. We provide equal employment opportunities without regard to race, color, religion, creed, sex, gender, sexual orientation, gender identity or expression, national origin, age, physical disability, mental disability, medical condition, pregnancy or childbirth, sexual orientation, genetics, genetic information, marital status, or status as a covered veteran or any other basis protected by applicable federal, state and local laws.

We are committed to:

• Creating a diverse and inclusive workplace that is welcoming, supportive, affirming and respectful
• Empowering employees to solve problems and work together to make a difference
• Providing mentorship and growth opportunities as part of a collaborative team
• A flexible work environment with flexible paid time off
• Competitive compensation and benefits, including health, dental, vision, and employer-match 401k