Solutions Engineer
About the role
Agera is seeking an Agentic AI Solutions Engineer to bring deep technical insight to the discovery process, guide solution optimization, and craft a technical vision that wins over complex healthcare organizations. You won't just be demoing features; you'll be architecting agentic AI workflows to prove how Artera can solve the industry's most persistent communication gaps.
Responsibilities
Agentic Solutions Architecture: Architect and propose optimized solutions for healthcare workflows using Artera’s AI suite, explaining how AI can safely reason, call tools, and interact with patients via voice and text.
Technical Discovery & Requirements Analysis: Conduct technical discovery sessions with prospects to evaluate system architecture, workflow needs, and data integration requirements. RFP/RFI & Security Review Leadership: Author definitive, technical responses to RFPs, RFIs, and security questionnaires, demonstrating how Artera satisfies both functional and compliance requirements.
Strategic Product Demonstrations: Lead compelling, value-driven demonstrations of the Artera platform for prospective clients. Go beyond feature-clicking to tell a cohesive story of how our core software and AI capabilities seamlessly orchestrate patient communication, collapse operational overhead, and improve patient access metrics.
Technical Architecture & Deal Strategy: Serve as the technical authority during the pre-sales cycle, defining the ideal future-state architecture and ensuring seamless technical alignment between prospect ecosystems and Artera’s platform.
Technical Continuity & Deployment Handoff: Act as the technical guide during the transition from sales to service rollout. Provide consultative, high-level oversight to Artera’s post-sales delivery teams to guarantee the architectural integrity of the scoped AI workflows is preserved during implementation.
Requirements
Experience: 3+ years of relevant experience in solutions engineering or technical consulting.
Patient Access Domain Knowledge: Strong familiarity with healthcare operations. You understand the operational friction points surrounding centralized scheduling, patient intake/registration, and referral management, allowing you to speak the same language as healthcare operations leaders.
Technical Concept Comprehension: Translate complex AI/ML concepts (e.g., context windows, Retrieval-Augmented Generation, Model Context Protocol) into highly clear, value-driven information for clinical, operational, and executive C-suite stakeholders.
AI & LLM Literacy: Firm grasp of Agentic AI paradigms, including token limits, prompt engineering, Claude CLI, Claude, Retrieval-Augmented Generation (RAG) data pipelines, and the Model Context Protocol (MCP) framework.
System Interoperability Acumen: Deep understanding of how health systems integrate with each other. Comfortable reading API documentation, map complex data fields, evaluate payloads/webhooks, and can pinpoint data dependencies during early-stage discovery.
Pay
$100,000 - $117,000 a year
Schedule
The compensation for this role will be based on level of experience and the geographic tier in which you are located. Compensation for this role is made up of a base salary with the possibility to earn an additional $30,000/yr through our bonus structure. This position also will be eligible for equity in the form of stock options.