Forward Deployed Engineers

Primary Responsibilities

• Solution Implementation & Delivery
• Build and deploy AI-powered solutions, including LLM-based workflows, copilots, and automation tools in client environments
• Implement integrations between AI models, APIs, and enterprise healthcare systems
• Translate defined solution designs into high-quality, production-ready code
• Contribute to end-to-end delivery by supporting development, testing, and deployment activities
• Hands-on Engineering
• Develop solution components using modern programming languages (e.g., Python, Java, SQL) and engineering frameworks
• Work with distributed systems and cloud platforms to support scalable, reliable deployments
• Assist with data preparation, prompt configuration, and model integration for AI-driven solutions
• Troubleshoot and resolve technical issues during development and deployment
• Client Delivery Support
• Work alongside senior engineers and consulting leads in client engagements across healthcare payer and provider organizations
• Support technical discussions and working sessions with client stakeholders
• Help execute on defined project plans, timelines, and deliverables
• Contribute to iterative development cycles, incorporating client and team feedback
• Collaboration & Translation
• Partner with cross-functional teams, including engineering, platform, and product teams, to deliver integrated solutions
• Translate technical requirements into actionable development tasks
• Communicate progress, risks, and technical considerations clearly within the team
• Support alignment between technical implementation and client expectations
• Documentation & Knowledge Transfer
• Document solution components, integration points, and deployment processes
• Support knowledge transfer to client technical teams to enable adoption and sustainability
• Contribute to reusable implementation patterns, assets, and playbooks
• Success Measures
• Delivers high-quality solution components that meet performance, reliability, and security expectations
• Contributes effectively to end-to-end client delivery efforts
• Demonstrates strong execution in translating requirements into working systems
• Communicates clearly within teams and supports client delivery activities
• Builds capability in both technical implementation and client engagement over time
• Demonstrates the ability to design and develop prototypes with a clear path to production, ensuring solutions are scalable, supportable, and can be transitioned effectively to production engineering teams.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or related field
• 3+ years of proficient experience in at least one programming language (e.g., Python, Java, SQL)
• 2+ years of experience operating in a consulting or advisory capacity, including structuring ambiguous problems, developing solution recommendations, and delivering against client or business objectives
• Demonstrated experience working in client-facing engagements, including partnering directly with stakeholders to understand needs, communicate solutions, and support delivery in real-world environments
• Experience working with APIs, data pipelines, or distributed systems
• Familiarity with cloud platforms (e.g., AWS, Azure, or Google Cloud Platform)
• Exposure to AI/ML concepts, including LLMs and prompt engineering
• Demonstrate advanced user capability on CodeX, Claude, etc. and other AI productivity tools
• Demonstrated ability to work effectively in client-facing delivery environments
• Demonstrated solid collaboration skills and ability to operate within structured project teams
• Demonstrated clear communication skills for working with both technical and non-technical stakeholders
• Demonstrated ability to execute against defined requirements and evolving priorities

Preferred Qualifications

• Master's degree in a technical discipline (AI/ML, Data Science, Software Engineering)
• Healthcare Domain Expertise; Understanding of healthcare payer and/or provider operations (e.g., claims, utilization management, care delivery, revenue cycle)
• Familiarity with healthcare data considerations (e.g., privacy, compliance)
• Demonstrated solid execution focus with attention to detail and code quality
• Demonstrated ability to work in fast-paced environments with multiple priorities
• Willingness to take ownership of assigned components and deliver reliably
• Continuous learning mindset, particularly in AI and emerging technologies