AI Engineer

Job Description

Job Description

This job is posted on behalf of Twenty80 LLC by Top Echelon.

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.

• 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.

• 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.

• 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.

• 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

• 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
• Experience supporting large-scale customer deployments

Successful candidates typically have:

• Experience building and deploying production AI solutions rather than purely research or advisory work
• Strong knowledge of open-source LLM frameworks and inference platforms
• Experience working directly with enterprise customers throughout implementation and deployment
• The ability to translate complex technical concepts for both engineering teams and executive leadership
• A collaborative mindset with a passion for solving complex customer challenges
• Experience working in fast-paced, high-growth environments

• Full-time position
• Remote-friendly within the United States
• Preference for candidates located near major East or West Coast metropolitan areas, though exceptional remote candidates will be considered
• Regular domestic travel to customer sites for technical discovery, proof-of-concept implementations, and production deployments

• Competitive base salary
• Performance-based bonus or on-target earnings (OTE)
• Equity package
• Compensation commensurate with experience and qualifications

• Comprehensive medical, dental, and vision insurance
• Equity participation
• Performance-based bonus opportunities
• Flexible remote work environment
• Professional development and career growth opportunities
• Opportunity to work with cutting-edge generative AI technologies on enterprise-scale deployments
• Collaborative, fast-paced engineering culture