About Armada

Armada delivers sovereign, industrial-grade AI infrastructure designed to operate where traditional cloud and centralized data center models fall short. Our platform includes Atlas as the control plane, Galleon modular edge data centers powered by the Armada Edge Platform, and Leviathan, Armada’s AI Factory, which partners with Bridge, our GPU-as-a-Service offering. Together, these capabilities enable enterprises and governments to deploy, operate, and scale AI workloads securely, efficiently, and close to where data is generated.

The ND8 region represents a strategically important market for Armada. Customers here are technically sophisticated, highly security-conscious, and often operate across multiple countries with strong expectations around data residency, sustainability, and operational excellence. Armada’s success in ND8 depends on senior engineers who can both execute deeply technical deployments and maintain long-term customer ownership.

Role Overview

The Senior Forward Deploy Engineer for ND8 is a hybrid role responsible for hands-on deployment execution and ongoing technical account ownership across the Nordic region. This role combines the execution depth of a Forward Deploy Engineer with the long-term ownership and customer leadership of a Technical Account Manager.

In the early phases of engagement, the Senior FDE leads platform bring-up, deployment execution, and initial workload onboarding. Once customers are live, the same engineer remains the primary technical owner, driving adoption, operational maturity, reliability, and expansion across multiple countries and sites.

This role reports into the Sr. Director of Customer Success & Delivery, EMEA & ANZ and is intentionally designed to avoid fragmented ownership between deployment and post-sale success. Success is measured by deployment quality, speed to production, customer confidence, platform adoption, retention, and expansion.

Key Responsibilities

Deployment execution and platform bring-up

• Lead end-to-end deployment of Armada platforms including Atlas, Galleon with AEP, and Leviathan AI Factory integrated with Bridge GPU-as-a-Service
• Execute deployments across the ND8 region, including multi-country and multi-site environments
• Own infrastructure bring-up, platform configuration, and production readiness validation
• Make real-time technical decisions across hardware, networking, Kubernetes, storage, and GPU layers

Technical account ownership and customer success

• Serve as the primary technical point of contact for assigned ND8 customers post go-live
• Own the technical success plan, adoption milestones, and operational maturity roadmap
• Build trusted, long-term relationships with customer engineering, platform, security, and data teams
• Lead technical governance discussions, roadmap planning, and platform optimization conversations

Joint Success Plan ownership

• Build, maintain, and actively drive Joint Success Plans (JSPs) for each assigned customer
• Align deployment milestones, platform adoption, and operational maturity to customer business objectives
• Use the Joint Success Plan as the primary framework for prioritization, execution, risk management, and value tracking
• Regularly review progress against success plans with customer stakeholders and Armada leadership
• Ensure JSPs inform deployment sequencing, adoption strategy, roadmap discussions, and expansion planning
• Surface risks, dependencies, and blockers early and drive resolution with clear ownership

Time-to-value acceleration and adoption

• Reduce time-to-try and time-to-value by unblocking workloads and accelerating early production use cases
• Drive adoption across new workloads, business units, and countries
• Identify expansion opportunities including additional Galleon deployments and Leviathan AI Factory capacity through Bridge GPUaaS

Operational excellence and reliability

• Ensure customer environments remain stable, secure, and production-ready
• Proactively identify scaling risks, architectural gaps, and technical debt
• Coordinate with Product, Engineering, and Support teams to resolve issues efficiently

Data residency, security, and regulatory execution

• Operate confidently within ND8 data residency, privacy, and security expectations including GDPR-aligned requirements
• Support customer security reviews, audits, and governance processes
• Balance global delivery standards with local regulatory nuance and customer expectations
• Maintain disciplined access control, documentation, and operational hygiene

Field leadership and mentorship

• Act as a senior technical presence for ND8 customers, setting the bar for execution and professionalism
• Mentor junior FDEs, TAMs, and delivery engineers as the region scales
• Contribute to deployment standards, runbooks, and repeatable best practices

Cross-functional collaboration

• Partner closely with the Sr. Director of Customer Success & Delivery, EMEA & ANZ on NB8 priorities and escalations
• Work with Sales on expansion planning while maintaining a trusted post-sale posture
• Provide structured feedback to Product and Engineering teams based on real-world ND8 customer usage

Qualifications and Experience

• 8+ years of experience in infrastructure, platform engineering, SRE, forward-deployed engineering, or technical account roles
• Proven ability to own both hands-on delivery and long-term customer technical relationships
• Deep technical expertise across Linux, networking, Kubernetes, storage, and GPU-accelerated compute
• Strong troubleshooting skills in live, production environments
• Experience supporting customers across multiple European countries
• Willingness to travel within the ND8 region as required
• Clear, confident communication style suited for executive and senior engineering audiences

Preferred Experience

• Experience with edge compute, modular data centers, or distributed infrastructure
• Familiarity with AI workloads, GPU clusters, and high-performance computing environments
• Exposure to regulated, sovereign, or government-adjacent environments
• Experience operating in Nordic or EU-regulated markets
• Comfort operating with ambiguity and owning outcomes end to end

What Success Looks Like

• ND8 customer environments reach production quickly and operate reliably
• The same engineer who deploys the platform remains the trusted technical owner long-term
• Adoption expands across workloads, sites, and countries without handoff friction
• Customers view Armada as a strategic AI infrastructure partner due to consistent technical ownership
  
  

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems.

About the Role

EnCharge AI is seeking a highly skilled and experienced AI Compiler Engineer to spearhead the efforts in developing and optimizing graph compilers tailored to cutting-edge AI and ML workloads. You will collaborate with hardware architects, and AI researchers to enhance performance, optimize computation graphs, and enable efficient model deployment on EnCharge’s Inference Accelerators. 

Responsibilities

• Architect, design, and implement optimizations for AI model execution on graph compilers to improve performance, reduce latency, and maximize hardware utilization.
• Work closely with ML researchers, hardware engineers, and software developers to design and deploy AI models, understanding and addressing hardware-specific challenges.
• Work on performance optimizations for neural network models, such as layer fusion, operator fusion, and graph-level transformations.
• Develop compiler optimizations and passes that convert high-level AI models (e.g., from TensorFlow, PyTorch) into intermediate representations (IR).
• Implement parsing, semantic analysis, and IR generation for deep learning frameworks.
• Research and integrate the latest advancements in compiler design, ML model optimizations, and hardware acceleration into graph compilers.
• Provide leadership, mentorship, and technical guidance to a team of engineers focused on graph compiler optimizations. 

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field (Ph.D. preferred).
• 3+ years in compiler development, with a strong focus on AI or ML graph compilers.
• Proficiency in AI graph compiler frameworks (e.g., MLIR, Torch-FX)
• Solid background in hardware architectures (e.g., GPUs, TPUs, ASICs) and optimization techniques such as fusion, quantization, and tiling.
• Familiarity with neural networks operators and code generation.
• Strong understanding of intermediate representations, code parsing, and semantic analysis in compiler design.
• Proficiency in C++, Python, or other programming languages commonly used in compiler development.
• Open-source contributions to AI software frameworks and libraries is a plus
• Demonstrated experience leading and mentoring engineering teams with successful project delivery. 

EnchargeAI is an equal employment opportunity employer in the United States.

The Ideal Candidate

You thrive in an environment of organised chaos. You can hold ownership of long‑running infrastructure projects, while also dropping everything to troubleshoot urgent network, system or application issues.

You are comfortable following strict procedures where required, and applying pragmatic judgement and creative problem solving when needed. You approach gaps in your knowledge with an “I don’t know yet” mindset, and you enjoy sharing knowledge and teaching skilled colleagues new approaches.

The Role

As a Senior Systems Administrator, you will be part of a small, highly capable team responsible for building and maintaining Entersekt’s infrastructure, deploying applications, and managing the databases and services that support them.

Your primary focus will be on network and datacentre operations. As these activities typically require only part of your time, you will also take on a broad range of systems administration responsibilities and provide support to internal teams and customers. This is a senior, hands‑on individual contributor role in a security‑critical environment.

Responsibilities

• Build, operate and maintain secure, scalable systems within Entersekt’s physical datacentres.
• Operate, maintain and monitor Java‑based application platforms across production and non‑production environments.
• Operate, maintain and troubleshoot a FreeBSD‑based server platform, ensuring availability, performance and security.
• Design, operate and maintain network and systems infrastructure, including both FreeBSD‑based and commercial (“off‑the‑shelf”) components.
• Manage, maintain and improve routing and network infrastructure, both internally and externally.
• Install, maintain and troubleshoot hardware in Entersekt datacentres and shared facilities.
• Support the operation and hardware maintenance of PCI‑regulated infrastructure within shared datacentre environments.
• Operate and support network resilience and availability services, including response to large‑scale traffic or availability incidents.
• Assist internal security teams with vulnerability scanning, penetration testing and other security and compliance‑related activities.
• Improve configuration management, package building and deployment mechanisms.
• Handle change requests, deployments and routine operational tasks across the business.
• Participate in change management planning, implementation and post‑change reviews, in line with internal controls and operational procedures.

Skills and Experience

Successful candidates for this role will generally possess the following qualifications and skills:

• 6+ years of experience in a Systems Administrator, Infrastructure Engineer or Network Administrator role.
• Strong network management skills, including maintaining, developing and troubleshooting complex network architectures.
• Hands‑on experience with BGP and OSPF routing, GRE tunnels, IPSec and WireGuard VPNs, and FreeBSD‑based open-source firewall platforms.
• Strong troubleshooting capability, including packet capture analysis using tools such as Wireshark or termshark.
• Solid experience working in on‑prem or hybrid datacentre environments.
• Technical environment and domain experience (strongly preferred):
  • FreeBSD as a primary operating system.
  • MariaDB as a database engine, including experience with Galera clusters.
  • Extensive use of ZFS and FreeBSD jails.
  • Experience with network security scanning and related tooling.
  • Familiarity with Tomcat and Java servlet environments.
  • Fundamental understanding of security concepts, with a strong interest in secure system design.
  • Practical understanding of cryptography concepts, including correct and incorrect usage.

Personality Attributes

• Calm and decisive problem solver who handles urgent issues with composure.
• Curious and growth oriented, with a willingness to learn and share knowledge.
• Ownership driven, with a strong security first mindset.
• Comfortable working autonomously while collaborating closely with skilled peers.

Mission Brief 

As a Product Assurance Engineer, Launch Operations, you will join our team on the beautiful arctic island of Andøya to perform test and launch campaigns of our Spectrum launch vehicle. You will act as a control instance for the quality and compliance of ground equipment, processes, and procedures, while also closely working with our Quality department based in Germany to ensure the quality of the flight hardware.

To do so, you will carry out in-process and final inspections, document reviews, and follow-up non-conformance reports. You will be following established processes, but will also have the opportunity to introduce new frameworks tailored to this launch site.

Your Role in Our Space Mission: 

• Shape and advance framework for product control at the Andøya launch site
• Carry out in-process and final inspections or hardware and operations – involving ground and flight systems
• Be involved in and follow-up on acceptance testing of flight hardware
• Review processes and procedures, and enforce the applicable document management
• Follow-up on non-conformance reports and risks, including the mitigating actions
• Set-up and maintain calibration plans for tools, equipment and systems
• Ensure proper and continuous documentation

Qualification Checklist 

• Relevant engineering qualification or engineering bachelor’s or master’s degree
• Experience in quality inspections and assurance involving hardware (preferably including assemblies)
• Experience with document management
• Experience with non-conformity processes and root cause analysis
• Ability to perform in high-stress environments
• Highly organised, effective team player with high attention to detail
• Able to adjust self-sufficiently and quickly to a highly dynamic work environment
• Physical dexterity is required as working in confined spaces is necessary
• Fluency in English (Norwegian and German can be helpful)

Bonus Skills

• Experience with fluid systems and piping/tubing involving hazardous materials
• Knowledge rocket propulsion systems and/or structures
• Experience with risk management processes

Benefits 

• Employee Participation Program: Share in our success through our virtual company share program
• 6 weeks of vacation: Enjoy the days off to relax and recharge
• Subsidised lunch: Stay energised with delicious, subsidised lunches every day
• Relocation support: Benefit from our relocation bonus with deductible expenses up to an agreed amount
• Wellness allowance: Stay healthy and fit with our yearly allowance for wellness activities (e.g., Gym, Massages)
• Individual learning allowance: Grow your skills with an individual learning budget granted after the probation period
• Physical and mental well-being: Access via OpenUp the online support from certified psychologists and lifestyle experts at no cost to you and your family
• And Much More! Discover additional perks and benefits when you join our team.  

Who we are

We are Isar Aerospace and we are at the forefront of New Space building a modern space business to enable faster, better and cheaper access to space.

Our mission is to help democratise space and use it for good in order to improve life on Earth now and for the future generations.

We are a fast-growing company aiming to provide sustainable and environmentally friendly launch solutions for small and medium-sized satellites and constellations into Low Earth Orbit. The company is privately funded by world-leading technology investors with strong commitment and support and our team is made of driven and talented people with a real passion for space innovation.

We're making rockets in a way that hasn't been done before disrupting a traditional industry. If you are up for the challenge, want to work on cutting-edge projects and be part of a team changing the world for better, come, join us and launch your career!

Want to find out more about us?

Visit www.isaraerospace.com

Data Protection

We process your personal data for the purpose of managing the recruitment process and assessing your application. For detailed information on how your data is processed, including your rights, please refer to our Privacy Policy.

Disclaimer

Isar Aerospace SE is an equal-opportunity employer committed to fairness and inclusivity. We do not prioritize any specific religion, gender, nationality, or background. Due to security clearance requirements, affiliations with countries listed under § 13 para. 1 no. 17 SÜG may affect the application process. All qualified applicants are encouraged to apply.

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems.

About the Role

EnCharge AI is looking for an experienced AI Research Engineer to optimize deep learning models for deployment on edge AI platforms. You will work on model compression, quantization strategies, and efficient inference techniques to improve the performance of AI workloads. 

Responsibilities

• Research and develop quantization-aware training (QAT) and post-training quantization (PTQ) techniques for deep learning models.

• Implement low-bit precision optimizations (e.g., INT8, BF16).

• Design and optimize efficient inference algorithms for AI workloads, focusing on latency, memory footprint, and power efficiency.

• Work with frameworks such as PyTorch, ONNX Runtime, and TVM to deploy optimized models.

• Analyze accuracy trade-offs and develop calibration techniques to mitigate precision loss in quantized models.

• Collaborate with hardware engineers to optimize model execution for edge devices, and NPUs.

• Contribute to research on knowledge distillation, sparsity, pruning, and model compression techniques.

• Benchmark performance across different hardware and software stacks.

• Stay updated with the latest advancements in AI efficiency, model compression, and hardware acceleration. 

Qualifications

• Master’s or Ph.D. in Computer Science, Electrical Engineering, or a related field.

• Strong expertise in deep learning, model optimization, and numerical precision analysis.

• Hands-on experience with model quantization techniques (QAT, PTQ, mixed precision).

• Proficiency in Python, C++, CUDA, or OpenCL for performance optimization.

• Experience with AI frameworks: PyTorch, TensorFlow, ONNX Runtime, TVM, TensorRT, or OpenVINO.

• Understanding of low-level hardware acceleration (e.g., SIMD, AVX, Tensor Cores, VNNI).

• Familiarity with compiler optimizations for ML workloads (e.g., XLA, MLIR, LLVM). 

EnchargeAI is an equal employment opportunity employer in the United States.

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems.

About the Role

EnCharge AI is seeking an AI Runtime Engineer to develop and optimize the execution stack for our next-generation AI accelerator. In this role, you will work on low-latency, high-performance runtime software that enables efficient execution of deep learning models on specialized hardware. You will collaborate with hardware, compiler, and AI framework teams to deliver optimized AI inference and training performance across cloud and edge environments. 

Responsibilities

• Develop and optimize the AI runtime software stack for executing deep learning workloads on AI accelerators.
• Implement task scheduling, memory management, and kernel execution strategies for efficient computation.
• Optimize data movement between host and device using PCIe, DMA, shared memory.
• Design and implement high-performance APIs for AI Inference frameworks such as OpenVino, ONNX Runtime, vLLM
• Work on graph execution optimizations, including kernel fusion, pipelining, tensor tiling, and caching.
• Integrate runtime components with AI compilers (LLVM, MLIR, XLA, TVM) for optimized execution.
• Ensure scalability and reliability of the AI runtime for cloud-based and edge AI deployments. 

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
• 3+ years of experience in developing low-level runtime software for AI accelerators, GPUs, or HPC systems.
• Strong proficiency in C/C++ and low-level systems programming.
• Deep understanding of task scheduling, concurrency, and memory hierarchy.
• Experience with hardware-aware optimizations and dataflow architectures.
• Familiarity with deep learning execution frameworks (ONNX Runtime, TensorRT, TVM, OpenVINO).
• Experience with low-latency, high-throughput workload execution for AI models.
• Strong debugging and profiling skills for optimizing AI execution performance.
• Exposure to AI model deployment pipelines (Triton, TensorFlow Serving). 

EnchargeAI is an equal employment opportunity employer in the United States.

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems.

About the Role

EnCharge AI is seeking a highly skilled Device Driver Engineer to design and implement high-performance driver stack for our cutting-edge AI accelerator hardware. In this role, you will work closely with hardware, firmware, and AI software teams to develop low-latency, high-bandwidth communication between the host system and AI accelerator.

Responsibilities

• Develop, optimize, and maintain Linux/Windows PCIe device drivers for AI accelerators.
• Implement low-level hardware interactions, DMA, memory management, and interrupt handling.
• Work on driver optimizations to reduce latency and improve throughput for AI workloads.
• Debug and troubleshoot PCIe protocol, kernel panics, crashes, and performance bottlenecks.
• Collaborate with hardware, firmware, and AI software teams to define driver interfaces.
• Ensure compliance with PCIe standards (Gen4/Gen5), SR-IOV, BAR memory mapping, and IOMMU.
• Support virtualization (VFIO, SR-IOV, DPUs) and containerized environments (Kubernetes, Docker, etc.).
• Develop tools for profiling, debugging, and monitoring driver performance.
• Contribute to open-source kernel modules if applicable. 

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
• 3+ years of experience in device driver development for Linux and/or Windows.
• Strong experience with PCIe-based hardware, including BAR regions, DMA, interrupts, and MMIO.
• Proficiency in C/C++ and kernel-mode programming (Linux Kernel, Windows WDDM/WDF/MCDM).
• Experience with AI-specific accelerators (e.g., GPUs, NPUs, TPUs) is a plus.
• Knowledge of low-level debugging tools (gdb, perf, ftrace, dmesg, PCIe analyzers). 
• Understanding of multi-threading, synchronization, and memory management in kernel space.
• Familiarity with high-performance AI/ML workloads is a plus.
• Experience in hypervisor interactions, VFIO, and passthrough solutions.
• Knowledge of secure boot, firmware updates, and trusted execution environments (TEE). 

 EnchargeAI is an equal employment opportunity employer in the United States.

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems.

About the Role

EnCharge AI is looking for an Embedded SW Engineer to develop the firmware for our Edge AI processors. The candidate must possess an excellent understanding of computer architecture and operating system concepts including, but not limited to, memory management, virtualization and PCIe address space. The role includes designing and developing the core Firmware for various parts of the SOC. The candidate must possess strong communication skills to interface with Runtime, Architecture and H/W teams. 

Responsibilities

• Develop the critical pieces of EAI Firmware used to deploy inference jobs on EAI processors
• Validate different IP blocks on the SOC
• Evaluate and integrate third-party device drivers to interface with EnCharge’s SW stack
• Work closely with the Runtime, Hardware and Architecture teams define the driver architecture 

Qualifications

• Bachelors in EE/CS
• Advanced programming skills in C/C++ for operating system kernel & systems development
• Understanding of RISC-V architecture is a plus
• Exposure to PCIe BAR and IOMMU architecture
• Exposure to virtualization and hypervisor technologies
• Deep understanding of operating systems concepts, data structures, x86-64 and accelerator architectures
• Experience with low-level debug tools as well as emulators and simulators
• Experience running, analyzing, and tuning system performance benchmarks
• Excellent verbal and written communication skills 

EnchargeAI is an equal employment opportunity employer in the United States.

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems.

About the Role

EnCharge AI is seeking an LLM Inference Deployment Engineer to optimize, deploy, and scale large language models (LLMs) for high-performance inference on its energy efficient AI accelerators. You will work at the intersection of AI frameworks, model optimization, and runtime execution to ensure efficient model execution and low-latency AI inference.  

Responsibilities

• Deploy and optimize LLMs (GPT, LLaMA, Mistral, Falcon, etc.) post-training from libraries like HuggingFace
• Utilize inference runtimes such as ONNX Runtime, vLLM for efficient execution.
• Optimize batching, caching, and tensor parallelism to improve LLM scalability in real-time applications.
• Develop and maintain high-performance inference pipelines using Docker, Kubernetes, and other inference servers. 

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field.
• Experience in LLM inference deployment, model optimization, and runtime engineering.
• Strong expertise in LLM inference frameworks (PyTorch, ONNX Runtime, vLLM, TensorRT-LLM, DeepSpeed).
• In-depth knowledge of the Python programming language for model integration and performance tuning.
• Strong understanding of high-level model representations and experience implementing framework-level optimizations for Generative AI use cases
• Experience with containerized AI deployments (Docker, Kubernetes, Triton Inference Server, TensorFlow Serving, TorchServe).
• Strong knowledge of LLM memory optimization strategies for long-context applications.
• Experience with real-time LLM applications (chatbots, code generation, retrieval-augmented generation). 

EnchargeAI is an equal employment opportunity employer in the United States.