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Added 3 hours ago
J
Head of Platform & Infrastructure Engineering
Jobgether
Remote, United States
- $340,000 to $400,000 USD / year
We are looking for an experienced engineering leader to oversee and scale Platform & Infrastructure Engineering, ensuring the performance, reliability, and scalability of a rapidly growing…
Added 6 hours ago
Director, Software Engineering
VIOC
Remote, United States
The Director also grows engineering talent and establishes development standards, continuing the adoption of cloud-native solutions and augmenting teams with agentic frameworks to deliver…
Added 6 hours ago
Principal AI translation architect 200 languages
Travoom
Remote, United States
OleOle is being built as a native Rust platform focused on:
Added 14 hours ago
B
Lead Product Designer
Brightplan
Remote, United States
- $165,000 to $195,000 USD / year
You’ll be the hands-on design lead for App 2.0, translating product strategy, customer needs, and engagement goals into intuitive, accessible experiences across desktop and mobile-optimized…
Added 15 hours ago
Solutions Architect (US only)
Bolder Apps
Remote, United States
5+ years in software engineering, with at least 2 years designing systems as a solutions architect, technical lead or similar
Added 17 hours ago
Product Owner, AI Platforms | Financial Services
BIP Capital
Remote, United States
Demonstrated, hands-on experience building AI-native products or features, not simply using AI tools like Claude or ChatGPT for personal productivity. You should be able to speak to…
Added 23 hours ago
Sales Strategy & Operations, Enterprise
Bask Health
Remote, United States
…visibility, and make our sales organization more effective. Share AI-native workflows, prompts, and processes across Revenue Operations so we raise the bar…
Added 23 hours ago
Head of AI Engineering (Architecture & Agents)
GoOpti B.V.
Remote, United States
We have decided to become an AI-native company. Not a chatbot bolted onto the website - a business where agents do real work in every department, safely, measurably, and connected to the…
Added 23 hours ago
Vice President of Technology
WorldVia
Remote, United States
Lead the technology organization, including software engineering, travel technology, IT infrastructure, information security, project delivery, and AI workflow automation.
Added 1 day ago
CR
GenAI Forward Deployed Engineer (client facing) - Financial Services
Continuum Resource Network
Remote, United States
- $150,000 to $200,000 USD / year
Background at an AI-native company, enterprise AI lab, or as an AI or engineering practitioner within a Financial Services firm.
Added 1 day ago
CR
GenAI Forward Deployed Engineer (client facing) - Financial Services
Continuum Resource Network
Remote, United States
- $150,000 to $200,000 USD / year
Background at an AI-native company, enterprise AI lab, or as an AI or engineering practitioner within a Financial Services firm.
Added 1 day ago
Director, Quality Engineering and Automation -Information technology
ServiceLink
Remote, United States
ServiceLink is seeking an experienced Director of Quality Engineering and Automation to lead our quality engineering transformation. This leader will be responsible for defining and…
Added 1 day ago
AI / ML Developer
Peraton
Remote, United States
…MLOps practices. The Software Engineer will work closely with engineering and product teams to evaluate emerging tools, build technical demonstrations, document integrations, and…
Added 2 days ago
CU
Part-Time Online Course Facilitator: AI/ML Technology and Architecture
Cornell University
Remote, United States
- Part-time
Applied machine learning, from data preparation and feature engineering through training, evaluating, and improving common models such as regression, decision trees, and ensembles.
Added 2 days ago
Senior Backend Cloud Engineer
Halcyon
Remote, United States
As a remote-native, completely distributed global team, we recognize great talent can exist anywhere. We invite you to apply to a job you’re interested in and we'll work a plan to meet your…
Added 2 days ago
TA
Senior Software Engineer (Platform Engineering)-Remote, USA
Tempus AI, Inc.
Remote, United States
- $130,000 to $150,000 USD / year
…migration, microservices adoption, and CI/CD maturity across the engineering organization. It safeguards architectural coherence, actively mitigates technical debt, and provides the senior…
Added 2 days ago
Senior DBA -1 (Database Reliability Engineer)
LexisNexis Risk Solutions FL Inc. Company
Remote, United States
Our Database Engineering team is focused on building and supporting secure, scalable, and highly available database platforms in a cloud-first environment. Working collaboratively with…
Added 2 days ago
Consulting/Principal DBA
LexisNexis Risk Solutions FL Inc. Company
Remote, United States
Our Database Engineering team is focused on building and supporting secure, scalable, and highly available database platforms in a cloud-first environment. Working collaboratively with…
Added 2 days ago
F
Senior Software Engineer, Stablecoin Payments
Flex
Remote, United States
- $170,000 to $280,000 USD / year
…already runs. That means real ownership, direct access to the engineering lead and product, and work that customers…
Added 2 days ago
Head of Product - Beamable
FIRY
Remote, United States
…identity, analytics, meta-game systems, virtual economies, and AI-native tooling: all integrated into a single platform that eliminates the point-solution stitching that has defined game…
Added 2 days ago
Senior Growth Marketer (Veterinarians)
Roo
Remote, United States
AI-native builder. You ship landing pages, tools, agents and automations yourself with Claude Code, Cursor, n8n, Webflow or similar, without waiting on engineering. You can show us…
Added 2 days ago
GL
Principal - Forward Deployed Engineer
GlaxoSmithKline LLC
Remote, United States
- $205,425 to $342,375 USD / year
GSK's Enterprise AI team builds AI solutions that prove value fast and scale to production. Forward Deployed Engineering is the front of the Enterprise AI delivery pipeline - proving AI…
Added 2 days ago
Staff - Forward Deployed Engineer
GlaxoSmithKline LLC
Remote, United States
GSK's Enterprise AI team builds AI solutions that prove value fast and scale to production. Forward Deployed Engineering is the front of the Enterprise AI delivery pipeline - proving AI…
Added 2 days ago
Product Manager, Workload Connectivity
Tailscale
Remote, United States
You'll work closely with engineering, design, and go-to-market teams to make Tailscale the obvious choice for workload connectivity, from a developer's first integration to production…
Added 2 days ago
Product Manager, Workload Connectivity
Tailscale
Remote, United States
You'll work closely with engineering, design, and go-to-market teams to make Tailscale the obvious choice for workload connectivity, from a developer's first integration to production…

Closed listing

Jobgether

Senior Forward Deployed Solution Engineer

Remote, United States

This opening has closed.

The original listing is kept below for reference.

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Job details

Posting language: English
Posted: Oct 30, 2026

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Original job description

Archived listing. The details below describe a past opening.

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Forward Deployed Solution Engineer based in the United States.

The Senior Forward Deployed Solution Engineer will lead complex customer deployments, translating strategic business and mission objectives into reliable, production-ready technical solutions. This hands-on engineering role combines software development, Kubernetes infrastructure, cloud and bare-metal systems, networking, and AI infrastructure. You will work directly with customer engineering teams, operators, and executives to design architectures, build automation, troubleshoot systems, and guide deployments from initial discovery through operational handoff. The scope spans cloud-native platforms, edge environments, GPU infrastructure, high-performance networking, and AI data and model workflows. You will collaborate with other forward-deployed engineering resources and internal Product and Engineering teams to turn deployment experience into reusable capabilities and standardized practices. This is an opportunity for an experienced technical leader who enjoys solving ambiguous problems and delivering solutions that customers can operate and scale independently.

Accountabilities

You will serve as a senior technical lead throughout complex customer engagements, taking responsibility for translating requirements into deployable architectures and ensuring that solutions deliver lasting operational and business value.

• Lead technical discovery with customers, translating business objectives, operational constraints, and mission requirements into practical technical architectures and deployment plans.

• Design, deploy, upgrade, and troubleshoot production Kubernetes clusters and cloud-native applications across public cloud, bare-metal, datacenter, and edge environments.

• Build automation, integrations, infrastructure tooling, and maintainable software to support repeatable deployments and reliable operations.

• Guide customer implementations from initial working capabilities through production readiness, scaled adoption, and operational handoff.

• Work across Kubernetes platforms, cloud infrastructure, Linux systems, GPU-enabled environments, data pipelines, and high-performance networking technologies.

• Design and support infrastructure for AI workloads, including GPU provisioning, drivers, container runtimes, Kubernetes scheduling, telemetry, and workload frameworks.

• Support the implementation and operation of AI data and model workflows, from data ingestion and preparation through deployment, inference, monitoring, and feedback.

• Troubleshoot complex distributed systems and networking issues, including routing, switching, DNS, load balancing, overlays, latency, bandwidth, congestion, and packet-level problems.

• Apply infrastructure-as-code, configuration automation, CI/CD, and GitOps practices to improve deployment consistency and operational efficiency.

• Address Kubernetes security and multi-tenancy requirements, including access controls, network policies, admission controls, resource quotas, secrets management, and tenant isolation.

• Collaborate with customer engineers, operators, technical leaders, and executives, clearly communicating architectural decisions, tradeoffs, delivery status, and emerging risks.

• Work closely with other forward-deployed engineering resources and deployment strategy stakeholders to coordinate technical execution and customer outcomes.

• Identify delivery risks early, communicate changes directly, and prioritize work to maintain progress in complex or evolving environments.

• Document architectures, configurations, operational procedures, and lessons learned to support customer independence and future deployments.

• Share implementation feedback with Product and Engineering teams, helping improve platform capabilities, automation, reference architectures, and deployment practices.

• Travel onsite to customer locations when needed for discovery, deployment, testing, and key operational milestones.

Requirements

The ideal candidate combines strong Kubernetes and infrastructure engineering expertise with software development skills and sound customer-facing judgment. You should be comfortable moving between code, architecture, infrastructure, networking, and stakeholder discussions while maintaining a clear focus on customer outcomes.

• Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or a related technical discipline, or equivalent practical experience.

• At least 6 years of professional experience in software engineering, platform engineering, site reliability engineering, DevOps, infrastructure engineering, solutions engineering, or a comparable customer-facing technical role.

• Production experience designing, deploying, upgrading, and troubleshooting Kubernetes clusters and cloud-native applications.

• Strong Linux and distributed-systems fundamentals, including processes, networking, storage, identity, certificates, resource management, and failure analysis.

• Proficiency in at least one modern programming language, preferably Go or Python, with the ability to develop maintainable, tested, production-quality code.

• Hands-on experience with infrastructure as code and configuration automation tools such as Terraform, Ansible, Cluster API, Helm, and Kustomize, or equivalent technologies.

• Experience implementing CI/CD or GitOps workflows using tools such as GitHub Actions, GitLab CI, Jenkins, Argo CD, or Flux.

• Working knowledge of Kubernetes security and multi-tenancy, including RBAC, namespaces, network policies, admission controls, quotas, secrets, pod security, and tenant isolation.

• Experience with at least one major public cloud provider and at least one datacenter deployment model, such as bare metal, VMware, KubeVirt, Proxmox, or OpenStack.

• Working knowledge of GPU-enabled infrastructure, including firmware, drivers, CUDA, container runtimes, Kubernetes scheduling, device plugins, telemetry, and workload frameworks.

• Understanding of the AI data and model lifecycle, from data ingestion through model deployment, inference, monitoring, and feedback.

• Strong networking fundamentals, including TCP/IP, routing, switching, DNS, BGP, load balancing, overlays, MTU, latency, bandwidth, congestion, and packet-level troubleshooting.

• Familiarity with high-performance AI networking concepts such as RDMA, RoCE, InfiniBand, SR-IOV, GPUDirect, and collective communication.

• Excellent communication skills, with the ability to explain architecture, technical tradeoffs, project status, and risks to engineers, operators, executives, and nontechnical stakeholders.

• Demonstrated ability to navigate ambiguous requirements, prioritize effectively, and deliver incremental value in a fast-moving environment.

• Willingness and ability to work onsite with customers for discovery, deployment, testing, and operational milestones.

• Authorization to work in the United States and ability to meet customer-specific access requirements.

The following qualifications are considered strong advantages:

• 8 or more years of relevant experience, including ownership of complex production deployments or strategic customer programs.

• Direct experience with Palette, PaletteAI, Cluster API, Kubernetes fleet management, edge Kubernetes, or declarative full-stack lifecycle platforms.

• Current CKA, CKS, CKAD, or relevant cloud, networking, security, or NVIDIA certifications.

• Production experience designing or operating NVIDIA Cloud Partner (NCP) or comparable multi-tenant GPU cloud environments.

• Deep expertise in tenant isolation across bare-metal infrastructure, virtual machines, Kubernetes control planes, GPU resources, storage, and high-performance networks.

• Hands-on experience with NVIDIA GPU Operator, Network Operator, DCGM, MIG, vGPU, NIM, Triton, TensorRT-LLM, vLLM, NCCL, or NVIDIA AI Enterprise.

• Experience with GPU schedulers and AI platform technologies such as Run, Slurm, Volcano, KAI, Ray, Kubeflow, or ClearML.

• Experience with distributed training or high-throughput inference using H100, H200, B200, GB200, GB300, or other modern accelerator platforms.

• Hands-on experience designing or operating NVIDIA Spectrum-X Ethernet fabrics, Quantum InfiniBand, ConnectX adapters, BlueField DPUs or SuperNICs, DOCA, or comparable high-speed, low-latency networking technologies.

• Experience configuring or troubleshooting GPUDirect RDMA, GPUDirect Storage, RDMA, RoCE, PFC, ECN, ECMP, SR-IOV, Multus, InfiniBand partitions, and topology-aware scheduling.

• Experience building or operating SONiC or Cumulus Linux leaf-spine fabrics, including FRR, BGP, EVPN/VXLAN, VRF, zero-touch provisioning, automated validation, upgrades, and telemetry.

• Experience integrating BlueField in DPU or restricted modes for network, security, storage, isolation, or telemetry offload, as well as familiarity with DPU provisioning, BMC, Redfish, attestation, and lifecycle management.

• Experience with high-performance storage and AI data platforms, including object storage, NVMe-oF, parallel file systems, data lakes, streaming, feature stores, vector databases, model registries, and metadata or lineage systems.

• Experience working in disconnected, air-gapped, sovereign, regulated, safety-sensitive, or classified environments.

• A record of contributing reusable software, open-source projects, reference architectures, technical publications, or customer enablement materials.

Benefits

• Fully remote position within the United States.

• Opportunity to work on advanced technologies spanning Kubernetes, cloud infrastructure, GPU systems, AI platforms, and high-performance networking.

• Direct involvement in complex, high-impact customer deployments and strategic technical initiatives.

• Broad technical ownership and the opportunity to influence customer architectures and operational outcomes.

• Close collaboration with experienced Field Engineering, Product, and Engineering teams.

• Opportunity to contribute to reusable software, automation, reference architectures, and improvements to future customer deployments.

• A collaborative, diverse, and fast-paced work environment that encourages innovation, professional growth, and meaningful technical contributions.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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