Presales Engineer, FlexAI
+ Equity & 15–20% performance-based bonus
More information about location
Delivering universal AI compute
Open for applications
Delivering universal AI compute
21-100 employees
Open for applications
+ Equity & 15–20% performance-based bonus
More information about location
21-100 employees
Company mission
To empower builders everywhere to develop groundbreaking AI solutions with effortless access to universal AI compute
Role
Who you are
- 5+ years in Presales, Solutions Engineering, or Technical Sales within AI, HPC, or Cloud Infrastructure
- Deep technical expertise in AI model training, fine-tuning, and inferencing, with hands-on experience in GPU acceleration, Kubernetes, Terraform, and CI/CD pipelines
- Proven experience deploying AI workloads on AWS, Azure, GCP, and hybrid on-prem environments
- Strong customer-facing communication skills, with the ability to explain technical concepts to both executives and engineers
Desirable
- Certifications in AWS Solutions Architect, Google Cloud ML Engineer, or Kubernetes (CKA) are a plus
- Experience working with AI frameworks (TensorFlow, PyTorch, JAX, Triton Inference Server)
- Familiarity with high-performance computing (HPC), distributed AI training (Horovod, DeepSpeed, FSDP)
What the job involves
- We are seeking a skilled Presales Engineer to be the technical bridge between our cutting-edge AI infrastructure solutions and our customers
- This role plays a crucial part in ensuring successful AI workload deployments, supporting both RTM1 (Partners - OEMs and Hyperscalers) and RTM2 (CSPs and Direct Enterprise Customers) by leading technical engagements, optimizing AI models, and driving Proof of Concept (PoC) success
- As a Presales Engineer, you will play a critical role in guiding customers through AI workload deployment, fine-tuning, training, and inferencing across cloud and on-prem infrastructures
- This role demands a strong blend of technical expertise, customer engagement skills, and hands-on AI deployment experience to ensure successful AI implementations at scale
- Lead technical discussions with customers to design AI, ML, and HPC workloads for cloud and on-prem deployment
- Guide clients on best practices for AI workload scaling, fine-tuning, and inferencing
- Collaborate with Sales, Product, and Engineering teams to ensure seamless customer onboarding
- Conduct live product demos, technical deep dives, and workshops to showcase FlexAI’s capabilities
- Work closely with account teams to develop customized AI infrastructure solutions
- Act as a trusted advisor to customers, helping them optimize AI workloads for performance and cost-efficiency
- Own the end-to-end PoC process, ensuring successful trials that demonstrate measurable value
- Optimize GPU utilization, AI training pipelines, and inferencing performance based on customer needs
- Document best practices and lessons learned from PoCs to enhance future implementations
- Provide real-time feedback to Product and Engineering teams on customer pain points and feature requests
- Stay ahead of AI infrastructure trends, recommending innovations for scalability, efficiency, and cost reduction
- Support cross-functional training for Sales, Customer Success, and Solution Architects
- Key Deliverables in the First 90 Days:
- Conduct Initial PoCs – Successfully execute technical demonstrations and AI workload optimization trials
- Develop Customer Playbooks – Build presales technical documentation for guiding customers through AI deployment
- Optimize AI Performance – Implement improvements in AI model inferencing and training efficiency
- Align with Sales & Product Teams – Establish a strong feedback loop to enhance AI infrastructure solutions
Application process
- We usually respond within a day
Our take
With a vision to contribute to the AI revolution, FlexAI delivers a layer of software intelligence, abstraction and orchestration into the AI compute stack. By rearchitecting existing architecture, it is creating accessible, universal AI compute to support the future of machine intelligence.
The idea is to combat the existing challenges with running AI workloads across diverse hardware. By doing this, FlexAI will enable AI developers to leverage a broader range of computing power without needing to modify their code.
FlexAI only came out of stealth in 2024, so we've yet to see much of what it has to offer, but its proposition has attracted a hefty seed investment. This will support the company as it moves forwards with the launch of its first product and towards its ultimate goal to empower AI acceleration.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (1 round)
Apr 2024
$30m
SEED
Total funding: $30m
Company benefits
- A chance to work alongside pioneers in AI and cloud computing, learning from the best and brightest
- An environment that values innovation, collaboration, and respect in every interaction
- Opportunities for personal and professional growth, encouraging you to stretch your abilities and make a lasting impact
- A platform to contribute significantly to the AI revolution, shaping the cloud services that power tomorrow's innovations
Company HQ
Vivienne, Paris, France
Leadership
Brijesh Tripathi
(CEO)Spent 4 years at Intel Corporation; first as VP and CTO of the Client Computing Group, then VP of AXG. Was VP pf Hardware Engineering at Zoox, co-founded SmartLivez and worked in Engineering at Tesla, Apple and NVIDIA.
Dali Kilani
(CTO)Angel Investor, who is also a Board Member at Epigene Labs and Go My Code. Previously they were an Advisor for ProsperUs, CTO at Lifen and Cloud/Devops Architect for The Boston Consulting Group.
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