AI/ML Engineer - Philadelphia, PA || New York City, NY || Washington, DC
About the Opportunity
We are partnering with a fast-growing AI infrastructure startup helping enterprises deploy AI systems that are reliable, secure, observable, scalable, and production-ready. As organizations accelerate Generative AI adoption, they face increasing challenges around governance, compliance, reliability, safety, latency, and operational control.
The platform provides enterprise-grade infrastructure, evaluation frameworks, observability tools, and real-time guardrails that enable organizations to operationalize AI at scale.
This is a high-impact role that sits at the intersection of engineering, customer deployment, and AI reliability. You will work directly with enterprise customers and internal product and engineering teams to solve complex deployment challenges and help organizations successfully deploy AI systems in production environments.
Position: Founding AI/ML Engineer (Remote)
Location: Remote - Full Time position
Candidates must be based in one of the following locations:
Philadelphia, PA
New York City, NY
Washington, DC
Must be comfortable working within East Coast U.S. time zones and available for occasional evening collaboration calls with offshore teams.
Key Responsibilities
Debug and troubleshoot complex deployment and integration challenges across customer environments.
Work directly with customer engineering and platform teams to deploy and operationalize AI systems.
Design and implement integrations across enterprise AI workflows, APIs, infrastructure, and governance platforms.
Deploy and support AI evaluation frameworks, observability solutions, and guardrail implementations.
Translate customer deployment challenges into actionable feedback for product and engineering teams.
Partner with engineering, infrastructure, security, risk, compliance, and operations stakeholders to navigate enterprise governance requirements.
Drive successful customer adoption of AI infrastructure solutions while balancing technical and business requirements.
Preferred Background
Experience deploying enterprise AI, ML, or Generative AI solutions.
Exposure to AI governance, observability, evaluation frameworks, or model monitoring.
Experience working within regulated industries such as financial services, healthcare, insurance, or government.
Startup experience or demonstrated ability to thrive in fast-paced environments.
Experience managing multiple customer deployments simultaneously.
Why Join?
High-visibility role with significant ownership and direct exposure to company leadership.
Opportunity to work on cutting-edge AI infrastructure, observability, governance, and deployment challenges.
Direct impact on enterprise AI adoption across regulated industries.
Work closely with customers deploying production-grade AI systems.
Influence deployment best practices, customer success strategies, and product direction.
Fully remote work environment with strong growth potential and long-term career advancement opportunities.
Required Qualifications
3–8 years of professional experience after completing an undergraduate degree.
Strong software engineering background with experience in:
Distributed Systems
Kubernetes
APIs
Platform Engineering
Enterprise Integrations
Infrastructure Engineering or DevOps experience within a startup, consulting firm, or technology-focused organization.
Customer-facing deployment or implementation experience.
Ability to communicate effectively with engineering, security, compliance, and infrastructure teams.
Strong scripting and coding skills with the ability to read, understand, and write clean code.
Ability to independently navigate complex technical and organizational environments.
Comfortable working in East Coast U.S. time zones.
Available for occasional evening meetings to support global collaboration.
We are partnering with a fast-growing AI infrastructure startup helping enterprises deploy AI systems that are reliable, secure, observable, scalable, and production-ready. As organizations accelerate Generative AI adoption, they face increasing challenges around governance, compliance, reliability, safety, latency, and operational control.
The platform provides enterprise-grade infrastructure, evaluation frameworks, observability tools, and real-time guardrails that enable organizations to operationalize AI at scale.
This is a high-impact role that sits at the intersection of engineering, customer deployment, and AI reliability. You will work directly with enterprise customers and internal product and engineering teams to solve complex deployment challenges and help organizations successfully deploy AI systems in production environments.
Position: Founding AI/ML Engineer (Remote)
Location: Remote - Full Time position
Candidates must be based in one of the following locations:
Philadelphia, PA
New York City, NY
Washington, DC
Must be comfortable working within East Coast U.S. time zones and available for occasional evening collaboration calls with offshore teams.
Key Responsibilities
Debug and troubleshoot complex deployment and integration challenges across customer environments.
Work directly with customer engineering and platform teams to deploy and operationalize AI systems.
Design and implement integrations across enterprise AI workflows, APIs, infrastructure, and governance platforms.
Deploy and support AI evaluation frameworks, observability solutions, and guardrail implementations.
Translate customer deployment challenges into actionable feedback for product and engineering teams.
Partner with engineering, infrastructure, security, risk, compliance, and operations stakeholders to navigate enterprise governance requirements.
Drive successful customer adoption of AI infrastructure solutions while balancing technical and business requirements.
Preferred Background
Experience deploying enterprise AI, ML, or Generative AI solutions.
Exposure to AI governance, observability, evaluation frameworks, or model monitoring.
Experience working within regulated industries such as financial services, healthcare, insurance, or government.
Startup experience or demonstrated ability to thrive in fast-paced environments.
Experience managing multiple customer deployments simultaneously.
Why Join?
High-visibility role with significant ownership and direct exposure to company leadership.
Opportunity to work on cutting-edge AI infrastructure, observability, governance, and deployment challenges.
Direct impact on enterprise AI adoption across regulated industries.
Work closely with customers deploying production-grade AI systems.
Influence deployment best practices, customer success strategies, and product direction.
Fully remote work environment with strong growth potential and long-term career advancement opportunities.
Required Qualifications
3–8 years of professional experience after completing an undergraduate degree.
Strong software engineering background with experience in:
Distributed Systems
Kubernetes
APIs
Platform Engineering
Enterprise Integrations
Infrastructure Engineering or DevOps experience within a startup, consulting firm, or technology-focused organization.
Customer-facing deployment or implementation experience.
Ability to communicate effectively with engineering, security, compliance, and infrastructure teams.
Strong scripting and coding skills with the ability to read, understand, and write clean code.
Ability to independently navigate complex technical and organizational environments.
Comfortable working in East Coast U.S. time zones.
Available for occasional evening meetings to support global collaboration.