Applied AI Engineer, Enterprise

Applied AI Engineer

About Carrot:

Carrot is the leading global fertility and family care platform, powered by intelligent care orchestration that delivers the right clinical guidance at the right moment. Trusted by over a thousand multinational employers, health plans, and health systems, Carrot supports millions of members in 195 countries through comprehensive clinical programs that drive industry-leading cost savings and award-winning member experiences.

Recognized by Fast Company and CNBC as a healthcare innovator, Carrot is frequently cited by leading global outlets for its work in digital health, the future of work, and family health. Learn more at get-carrot.com.

The Opportunity 🚀:

Carrot Fertility is hiring an Applied AI Engineer to join our Enterprise Technology team. You will design, build, and ship production-grade AI and integration solutions, providing internal teams with reliable, structured access to Carrot’s core product and operational data. This is a hands-on engineering role with end-to-end ownership, from scoping and architecture through deployment, iteration, and measurable business impact.

Your initial project will involve building the data access layer for Carrot’s enterprise AI agent ecosystem. You will design and deploy an MCP (Model Context Protocol) architecture that exposes structured, governed access to core operational data, including member eligibility, benefit balances, expense records, provider information, and employer-specific rules. This foundational infrastructure work is crucial for scaling Carrot’s AI capabilities.

You will collaborate closely with internal teams across Operations, Business Systems, and Product to translate data access needs and workflow gaps into AI-powered solutions. You will operate with the urgency of a startup engineer and the judgment of a senior architect, adhering to a principle of least complexity.

What You’ll Do:

• Embed with internal business teams to identify data access gaps and workflow pain points, prototype solutions, and own the full delivery lifecycle.
• Architect and build agentic AI systems for complex, multi-step business processes, ensuring reliable, deterministic, and auditable outcomes.
• Design systems with built-in compliance and data governance: HIPAA-compliant data handling, role-based access control, prompt hygiene, evaluation frameworks, and observability.
• Write high-quality, production-grade code, utilizing low-code solutions where they reduce delivery time and maintenance, and custom code where greater control or capabilities are needed.
• Use Claude Code as your primary AI-assisted development environment.
• Translate ambiguous business requirements into clear technical designs and communicate effectively with technical and non-technical stakeholders.
• Define and instrument success metrics (e.g., time saved, error rates, SLA improvements, cost reduction).
• Feed patterns, failure modes, and reusable frameworks back into a shared internal playbook.
• Lead enablement sessions and create documentation for business teams.
• Build and maintain MCP servers exposing Carrot’s core product and operational data to AI tools and agents.
• Develop deep familiarity with Carrot’s application database schema to independently navigate the data model and build clean access patterns.
• Build Claude skills and plugins for business teams and AI agents.
• Apply a principle of least complexity to all builds, prioritizing simple, maintainable, and documented solutions.

Example Projects You Might Tackle:

• Application Data Access Layer & AI Agent Enablement: Design and deploy MCP servers exposing structured, governed access to core product and operational data (e.g., expense records, member eligibility, benefit balances, employer rules). Tune agents to improve AI-assisted internal operations.
• AI-Assisted Intake and Routing: Build an intelligent triage system to classify inbound requests, summarize context, and route or draft responses.
• Revenue and Finance Automation: Partner with RevOps and Finance to automate data work, improve forecast accuracy, and surface insights.
• RAG-Powered Knowledge Assistant: Deploy a retrieval-augmented system to surface source-of-truth documentation and SOPs.
• Automated KPI Dashboards: Instrument and visualize business impact across all AI solutions.

About You:

• 6-10 years of software engineering experience with strong fundamentals in data structures, system design, SQL, and application integration. Experience in Business Systems, Enterprise Engineering, or internal-facing engineering is a plus.
• Proven track record of shipping production software, owning reliability, observability, and operational health.
• Highly proficient with Claude Code, using AI-assisted development as a core work practice.
• Hands-on experience building and deploying agentic AI systems (LLM orchestration, tool/function calling, RAG pipelines, MCP server development).
• Programming fluency in Python and TypeScript/JavaScript; Ruby experience is a plus.
• Experience with Workato or similar iPaas platforms.
• Background in enterprise applications like Salesforce or NetSuite and their integration patterns.
• Strong command of SQL and data modeling; ability to navigate production database schemas independently.
• Fluency with REST APIs, OAuth2, webhooks, and error handling.
• Strong instincts for security, data privacy, and compliance.
• Exceptional communication skills, able to engage both technical and non-technical audiences.
• Comfort with ambiguity and a bias toward action.
• Ability to develop working familiarity with existing application codebases and database schemas.
• Commitment to designing for maintainability and least complexity.

Nice to Have:

• Experience in healthcare, health tech, or other regulated environments (HIPAA).
• Experience with event-driven architecture, message queues, or stream processing.
• Knowledge of AI observability and evaluation frameworks.
• Experience with vector databases, semantic search, or embedding pipelines.
• Prior experience in a Business Systems, IT engineering, or embedded engineering context.
• Experience building Claude skills, plugins, or custom prompt libraries.
• Familiarity with enterprise AI assistant or knowledge management platforms like Glean.

Compensation:

• Base Salary Range: $165,000.00 - $200,000.00 annually. Actual compensation may vary based on confirmed job-related skills and experience.
• Carrot offers a holistic Total Rewards package including health and wellness benefits, retirement savings plans, short- and long-term incentives, parental leave, family-forming assistance, and competitive compensation.