Role Summary
Our client, a rapidly growing AI infrastructure company, is seeking multiple
AI Engineers (Enterprise)
to help design, build, and deploy production-grade generative AI solutions for enterprise customers.
This is a customer-facing, hands-on engineering role that combines deep technical expertise with solution architecture and client engagement. You will partner closely with enterprise organizations to transform generative AI concepts into scalable production systems while collaborating with internal engineering and product teams to drive innovation.
Strong candidates will have experience deploying AI/ML solutions in production environments, working with large language models (LLMs), and supporting enterprise customers through complex technical implementations.
Key Responsibilities
Enterprise AI Solutions
Lead technical discovery sessions with enterprise customers to understand business requirements and define AI solution strategies.
Scope and execute proof-of-concept (POC) projects, performance testing, and solution evaluations.
Design, build, and deploy production-ready AI applications within customer environments.
Recommend appropriate model architectures, deployment strategies, and infrastructure based on customer requirements.
Advise customers on model fine-tuning and optimization techniques, including supervised fine-tuning and other modern training approaches.
Develop evaluation frameworks to measure model performance and production readiness.
Customer Engagement
Serve as the primary technical advisor for enterprise customers throughout implementation and deployment.
Build relationships with technical and executive stakeholders.
Guide customers through infrastructure, security, and compliance considerations.
Support successful production rollouts and ongoing technical adoption.
Cross-Functional Collaboration
Partner with Product and Engineering teams to communicate customer feedback and influence product improvements.
Identify recurring customer challenges and contribute to product roadmap discussions.
Collaborate internally to improve deployment processes and customer success.
Required Qualifications
3+ years of experience in customer-facing AI/ML, machine learning infrastructure, solutions engineering, or related technical roles
Proven experience deploying AI/ML applications into production environments
Hands-on experience with large language model (LLM) inference and/or model training using open-source model frameworks
Strong Python programming skills
Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP)
Experience with containerization and orchestration technologies, including Kubernetes
Excellent communication skills with the ability to engage both technical teams and executive stakeholders
Ability to manage multiple enterprise projects in a fast-paced environment
Preferred Qualifications
Experience with modern LLM fine-tuning methodologies such as supervised fine-tuning (SFT) and other advanced optimization techniques
Background in enterprise AI solution architecture or technical consulting
Experience working within high-growth startup environments
Strong understanding of enterprise infrastructure, security, and compliance requirements