Senior Software Engineer, Applied AI

Gravie

4d•$140,000 - $180,000

About The Position

Gravie is seeking a Senior Software Engineer, Applied AI to join their team. Engineers at Gravie work closely with Product, owning outcomes end-to-end. This involves deeply understanding the business, shaping problems and solutions, and ensuring the developed solutions effectively address the intended problems. The role utilizes agentic development, where engineers use AI agents to assist in developing specifications, plans, and executing substantial engineering work. Engineers are responsible for reviewing and refining specifications, setting guardrails and acceptance criteria, validating results, and ensuring the quality of all shipped products. As AI agents handle more execution, the role requires strong problem framing, business understanding, architectural judgment, system thinking, risk identification, and the ability to evaluate quality, maintainability, and tradeoffs.

Requirements

Five or more years of software engineering experience, including ownership of complex systems from design through production.
Hands-on experience building and operating production AI applications, not only prototypes.
Hands-on experience with agentic software development, using AI coding agents to help create specifications and plans, execute meaningful multi-step work across a codebase, run and fix tests, validate results, and iterate while maintaining ownership of architecture, quality, and what ultimately ships.
Deep expertise in at least one primary area, such as Python backend and distributed systems, or React and TypeScript product engineering, plus the ability to work across the full system.
Experience with retrieval, embeddings, context, memory, evaluation, monitoring, or AI agent architectures and workflows.
Strong judgment in testing, monitoring, failure handling, privacy, security, access control, and data governance.
Clear communication and effective collaboration across technical and non-technical teams.

Responsibilities

Design and build production-grade AI agent systems, including multi-agent workflows, orchestration layers, and supporting services.
Design retrieval, context, and memory systems that ground AI outputs and support reliable multi-step workflows.
Develop AI-powered decision-support systems that meet the accuracy, traceability, and explainability requirements of healthcare and other regulated environments.
Develop distributed backend services, event-driven workers, job pipelines, APIs, and relational data models.
Build intuitive, product-quality user experiences using React and TypeScript that make complex AI capabilities understandable and actionable.
Establish patterns for AI quality assurance, including automated evaluations, regression testing, groundedness checks, and compliance guardrails.
Evaluate models and frameworks using accuracy, latency, reliability, privacy, security, and cost evidence.
Mentor engineers and help raise engineering standards across the team.