Technical Solution Engineer

EntelechyAI is a company that unifies enterprise systems with comprehensive managed services. The Technical Solution Engineer will act as a technical and consultative bridge between the company's technology and clients' enterprise environments, focusing on collaboration and education to enhance client delivery.

Responsibilities:

• Collaborative Discovery: Partner with client stakeholders across finance and operations to lead deep technical discovery sessions
• Solution Co-creation: Design and implement the solution of Entelechy intelligence layer with clients, integrate across a wide array of enterprise finance systems, sub-ledgers, and operational data sources without forcing clients into disruptive system overhauls
• Technical Education & Trust: Serve as a trusted advisor to client finance and operations teams. Confidently address complex system objections and technical questions by educating users on data lineage, logic rules, and correctness, turning skepticism into collaborative alignment
• Cross-Functional Feedback Loop: Function as the vital link between field deployments and internal development. Synthesize complex client environments and workflows, collaborating directly with the CTO and core engineering to continuously evolve our core technology

Requirements:

• 5–7 years of proven success as a Solutions Engineer, Technical Consultant, or equivalent client-facing engineering role delivering software solutions to mid- or large-sized enterprise clients
• Strong hands-on foundations in modern software development utilizing advanced LLMs and AI coding tools (such as Claude and similar developer environments)
• Exceptional interpersonal skills with a natural ability to educate, guide, and resolve complex systemic concerns for business users while maintaining deep technical credibility
• Experience leveraging AI to rapidly build, test, and deploy agentic workflows or logic-driven automation is highly desired
• A practical, working knowledge of data engineering principles (such as data modeling, pipeline concepts, and navigating enterprise data silos) is a strong plus
• Being comfortable navigating and speaking the language of corporate finance and operations professionals is desirable