# Senior Sales Engineer at Ddn

> Remote · Sweden · Senior · Software engineering · open. Source: https://alderhq.app/jobs/ashby%3Addn%3Abc40c079-340b-40e9-b013-030fc150bcf9 (read 2026-11-03).

## Facts (observed)

- Company: [Ddn](https://alderhq.app/companies/ddn)
- Location text: Remote - Sweden
- Where it can be done from (inferred): Remote · Sweden (evidence: "Location: Remote - Sweden")
- Posted: 2026-07-22 (104 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-03
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/ddn/bc40c079-340b-40e9-b013-030fc150bcf9
- Skills listed (inferred): Kubernetes

## Pay and sponsorship

- Posted pay: not posted

## Description (the employer's text)

As a Sales Engineer, you'll architect high-performance storage solutions that enable customers to achieve their boldest ambitions. Work across finance, pharmaceuticals, education, and physical AI—designing systems that power real-time trading, accelerate drug discovery, enable groundbreaking research, and fuel autonomous systems.

You'll translate complex customer requirements into elegant technical solutions, demonstrate capabilities through POCs and benchmarks, and serve as a trusted advisor throughout the sales cycle.

### What You'll Do

### Customer Engagement

Partner with customers to understand their critical data challenges—high-frequency trading, genomics processing, AI model training, or autonomous vehicle sensor fusion

Translate technical requirements into elegant, scalable storage solutions that exceed expectations

Act as trusted technical advisor throughout the sales cycle

### Solution Design

Architect storage for AI/ML training, HPC simulations, data analytics, and GPU-accelerated workloads

Design for reliability, resilience, security, and scale—balancing performance with data protection

Create BOMs, system architectures, and technical proposals for complex RFPs

Conduct live demos, POCs, and performance benchmarking

Integrate with GPU clusters, Kubernetes, cloud platforms, and AI frameworks

### Innovation & Growth

Stay current on AI infrastructure and storage technology trends

Collaborate with Product and Engineering teams using field insights

Mentor team members and contribute to technical thought leadership

Shape product direction based on customer needs

### What You Bring

### Technical Foundation (All Levels)

Strong understanding of storage and data architectures: SAN, NAS, object storage, parallel file systems

Knowledge of architectural patterns for reliability, resilience, security, and scale

Understanding of storage and data protocols: S3, POSIX, NFS, SMB

Familiarity with network protocols: TCP/IP, InfiniBand, RDMA

Curiosity about massively parallel technologies (Lustre, GPFS, Exascaler)

Aptitude for AI workloads and how storage enables AI innovation

Ability to communicate technical concepts to both engineers and executives

### Entry Level (0-3 years)

Bachelor's in Computer Science, Engineering, or related field (or equivalent experience)

Exposure to storage/systems through coursework, internships, or projects

Strong analytical and problem-solving skills

Customer-facing communication skills

### Experienced (3+ years)

3-8+ years in pre-sales, solutions architecture, or technical consulting

Proven track record designing storage/infrastructure solutions

Hands-on experience with enterprise storage systems

Experience with AI/ML infrastructure, HPC, or high-performance workloads (preferred)

Success managing complex technical sales cycles

### What Sets You Apart

Genuine curiosity about AI and its impact across industries

Ownership mindset—you solve problems until they're solved

Ability to translate technical complexity into business value

Thrive in fast-evolving technology environments

Collaborative team player with integrity and empathy

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Addn%3Abc40c079-340b-40e9-b013-030fc150bcf9 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.