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# Senior Software Engineer, Applied AI

- **Company:** Gravie
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Governance, Relational Databases, Distributed Systems, Regression Testing, Requirements Management, Software Engineering, TypeScript, ReactJS, AI Coding Agents, Backend, Agentic-AI, Build Management, Virtual Agents
- **Published:** October 31, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-software-engineer-applied-ai--97faa16e-4668-472b-aad9-bdca48ef2c9b

## About the Role

Software Engineering, Artificial Intelligence (AI), Problem Solving Skills, Artificial Intelligence (AI) Agents, Requirements Management, Risk Analysis, Business Architecture, Memory Hardware, Artificial Intelligence (AI), Traceability, * 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.

## Description

At Gravie, engineers work closely with Product and own outcomes end to end. That means understanding the business deeply, shaping the problem and solution, and staying accountable for whether what we build actually solves the problem-not simply implementing a set of requirements.

We practice agentic development to increase the scope and leverage of that ownership. Engineers start with a clear outcome or problem, use AI agents to help develop the specification and proposed plan, and then use those agents to execute substantial multi-step engineering work. Engineers review and refine the spec and plan, set guardrails and acceptance criteria, validate the results, and own the quality of everything that ships.

As agents take on more of the execution, the bar for engineers gets higher. Strong problem framing, business understanding, architectural judgment, system thinking, risk identification, and the ability to evaluate quality, maintainability, and tradeoffs become even more important.

You Will:

 * 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.