Enterprise AI & Cloud Solutions Engineer, FlexAI
Delivering universal AI compute
Be an early applicant
Delivering universal AI compute
21-100 employees
Be an early applicant
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
- AI Workload Optimization - Strong understanding of fine-tuning, training, inferencing for LLMs, vision models, and HPC workloads
- Cloud & On-Prem Deployment - Deep expertise in deploying AI workloads on AWS, Azure, GCP, and hybrid on-prem clusters
- DevOps & Infrastructure as Code - Experience with Kubernetes, Docker, Terraform, Ansible, Helm for AI model deployment
- GPU & Accelerator Optimization - Familiarity with NVIDIA A100, H100, MI300X, TPU, Habana, Tenstorrent optimizations
- MLOps & AI Lifecycle - Experience with MLflow, Weights & Biases, Kubeflow, Airflow, Hugging Face for AI pipeline management
- Networking & Storage for AI - Proficiency in InfiniBand, NVMe, distributed training techniques (Horovod, DeepSpeed, FSDP)
- Ability to translate complex AI infrastructure topics into clear explanations for enterprise clients
- Experience in managing customer expectations, debugging real-time AI performance issues, and guiding technical roadmaps
- Strong communication and collaboration skills, especially in cross-functional teams involving AI engineers, DevOps, and customer success teams
Desirable
- Certifications - AWS Certified DevOps Engineer, Google Cloud ML Engineer, Kubernetes Administrator (CKA)
- Experience with AI Training Frameworks - TensorFlow, PyTorch, JAX, Triton Inference Server
- Previous Experience in CSP or AI-focused Cloud Services
What the job involves
- The Enterprise AI & Cloud Solutions Engineer will serve as a technical expert in AI workload deployment, DevOps, and infrastructure management across on-prem and multi-cloud environments
- The role focuses on fine-tuning, inferencing, and training AI models efficiently across hybrid infrastructures
- This person will work closely with customers, ensuring seamless deployment, troubleshooting, and optimization of high-performance AI workloads
- Lead the deployment, integration, and optimization of AI workloads (training, fine-tuning, inferencing) across cloud and on-prem environments
- Work directly with customers to set up high-performance computing (HPC) clusters, configure GPUs/TPUs, and optimize AI workloads
- Automate deployment pipelines for AI models using Kubernetes, Terraform, and CI/CD workflows across AWS, GCP, Azure, and on-prem clusters
- Implement best practices for scaling AI workloads dynamically across hybrid and multi-cloud environments
- Optimize GPU and accelerator utilization to maximize AI training efficiency
- Troubleshoot model performance by profiling workloads, identifying bottlenecks, and optimizing resource allocationWork with the engineering team to build self-healing, auto-scaling AI infrastructure
- Act as the primary technical liaison for enterprise customers, ensuring smooth onboarding and ongoing success
- Conduct technical deep dives with customer DevOps and engineering teams to optimize cloud/on-prem AI workloads
- Train customers onfine-tuning best practices, distributed training methodologies, and inference deployment strategies
- Guide customers in choosing the best deployment model (on-prem, hybrid, multi-cloud) based on workload and cost-efficiency
- Deploy, maintain, and monitor AI model lifecycle management solutions to improve operational efficiency
- Work with cloud providers (AWS, Azure, GCP) to optimize cost-performance trade-offs for AI workloads
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 values
- Ownership
- Optimism
- Velocity
Company HQ
Vivienne, Paris, France
Articles
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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