Forward Deployment Engineer FDE

Keylent Inc; Washington, Baltimore (District of Columbia, MD); On-site; USD 150,000 - 190,000; Full time

Job summary

Keylent Inc is seeking a hands-on Forward Deployed Engineer to deploy AI/ML solutions for healthcare payer teams. You will work directly with business, operations, and technology stakeholders to understand claims workflows and deliver production-ready AI-powered automation.

The role emphasizes Python, APIs, SQL, LLMs/GenAI, and data pipelines, with on-site work in Maryland and collaboration with cross-functional teams to scale solutions and improve claims operations.

Qualifications

• 3+ years in Software Engineering, Data Engineering, ML Engineering, Applied AI, or related field.
• Proficient with Python, APIs, SQL and cloud platforms.
• Experience with AI/ML technologies and production-ready solutions.
• Experience with LLMs, Generative AI, RAG, or AI agents/agentic workflows.
• Healthcare payer/health insurance experience, especially claims processing or adjudication.

Responsibilities

• Understand claims workflows with healthcare payer teams.
• Configure, integrate, and deploy AI/ML solutions in customer environments.
• Develop solutions using Python, APIs, SQL, LLMs/GenAI, ML models, and data pipelines.
• Analyze claims data, business rules, SOPs, and workflows for automation opportunities.
• Build and enhance AI-powered workflows and applications.
• Integrate AI/ML solutions with enterprise applications and healthcare systems.
• Troubleshoot production issues and adapt solutions per customer needs.
• Collaborate with product and engineering to translate requirements into scalable capabilities.
• Support testing, deployment, monitoring, and continuous improvement of AI/ML solutions.

Skills

Python

APIs

SQL

LLMs/GenAI/RAG

AI/ML production

Healthcare payer experience

Customer collaboration

Cloud platforms

Job description

Job Summary

We are seeking a hands-on Forward Deployed Engineer (FDE) with strong AI/ML and software engineering experience to work directly with healthcare payer teams. The engineer will help deploy and integrate AI-driven solutions that improve and automate healthcare claims operations and claims workflows.

Responsibilities

• Work directly with healthcare payer business, operations, and technology teams to understand claims workflows and business requirements.
• Configure, integrate, and deploy AI/ML solutions within customer environments.
• Develop solutions using Python, APIs, SQL, LLMs/GenAI, ML models, and data pipelines.
• Analyze claims data, business rules, SOPs, and exception/pend workflows to identify opportunities for automation.
• Build and enhance AI-powered workflows and applications.
• Integrate AI/ML solutions with existing enterprise applications and healthcare systems.
• Troubleshoot production issues and quickly adapt solutions based on customer requirements.
• Work closely with product and engineering teams to convert customer requirements into scalable product capabilities.
• Support testing, deployment, monitoring, and continuous improvement of AI/ML solutions.

Required Qualifications

• 3+ years of experience in Software Engineering, Data Engineering, ML Engineering, Applied AI, or a related field.
• Strong hands-on experience with Python, APIs, SQL, and cloud platforms.
• Experience with AI/ML technologies and developing production-ready solutions.
• Experience with LLMs, Generative AI, RAG, or AI agents/agentic workflows.
• Healthcare payer or health insurance experience, particularly claims processing or claims adjudication.
• Understanding of healthcare claims, payment integrity, business rules, and payer workflows.
• Strong problem-solving and troubleshooting skills.
• Ability to work directly with customers and business stakeholders.
• Strong communication and collaboration skills.
• Willingness to work onsite in Maryland.

Preferred Qualifications

• Experience with healthcare AI/ML solutions.
• Experience with claims automation, payment integrity, claims adjudication, or claims analytics.
• Experience building RAG pipelines and agentic AI workflows.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with data pipelines and large healthcare datasets.
• Experience deploying AI/ML applications in enterprise or production environments.