The posting
New York City, NY | On-Site
$150,000–$230,000 Base Salary + Competitive Equity | Full-Time
Global Placement Firm is conducting a confidential search for a Senior Software Engineer specializing in AI Agent Infrastructure and Backend Systems to join a rapidly growing healthcare AI technology startup in New York City.
This is a high-impact engineering opportunity for an experienced software engineer with deep expertise in TypeScript backend development, production-grade infrastructure, distributed systems, and AI agent architecture.
The ideal candidate has 4+ years of professional software engineering experience and enjoys solving complex infrastructure challenges, building reliable and scalable systems, and developing the foundational technology that enables AI agents to automate real-world healthcare workflows.
Position Overview
As a Senior Software Engineer – AI Agent Infrastructure, you will play a critical role in designing, building, and scaling the backend systems that power autonomous AI agents operating across complex healthcare environments.
These agents interact with electronic medical records (EMRs), healthcare portals, browser applications, desktop systems, documents, and other fragmented operational tools.
You will build the infrastructure that allows AI agents to operate reliably, manage state, recover from failures, execute workflows, and perform complex tasks across multiple systems.
This position offers significant ownership over agent architecture, backend infrastructure, workflow orchestration, evaluation systems, and platform reliability.
You'll work closely with engineering leadership and forward-deployed engineers to transform real-world implementation challenges into reusable, scalable platform capabilities.
Key Responsibilities
AI Agent Infrastructure & Architecture
- Design, build, and maintain the core infrastructure powering autonomous AI agents across healthcare customer workflows.
- Develop reliable systems supporting browser automation, desktop automation, tool execution, state management, and retry logic.
- Improve agent architecture through experimentation with planning, execution, memory, validation, and recovery mechanisms.
- Build reusable components that enable AI agents to interact with complex healthcare software systems.
- Develop scalable infrastructure supporting production AI agent deployments.
- Implement fault-tolerant systems that maintain reliability across long-running, multi-step agent workflows.
Backend Engineering & Distributed Systems
- Own and develop backend services across a TypeScript and Node.js monorepo.
- Design and maintain APIs, domain services, background jobs, and event-driven systems.
- Build durable workflow orchestration systems using technologies such as Temporal.
- Develop scalable backend architectures capable of supporting complex asynchronous operations.
- Improve system reliability, fault tolerance, scalability, and performance.
- Design clean abstractions and reusable engineering primitives to accelerate platform development.
Agent Evaluation, Monitoring & Observability
- Design and implement evaluation frameworks to measure AI agent performance and reliability.
- Build observability tools to monitor agent execution, diagnose failures, and investigate agent decisions.
- Develop systems to identify performance regressions and measure improvements over time.
- Create debugging tools that help engineers understand agent behavior across complex workflows.
- Improve testing, validation, and monitoring processes for production AI systems.
Healthcare Workflow Automation
- Build infrastructure enabling AI agents to interact with fragmented healthcare technologies, including: Electronic Medical Record systems (EMRs) Healthcare portals Browser-based applications Desktop applications Fax-based workflows PDFs and document-processing systems
- Develop reliable automation capabilities for complex administrative and operational workflows.
- Implement safeguards, validation processes, and recovery mechanisms appropriate for sensitive healthcare environments.
- Partner with forward-deployed engineers to identify recurring deployment challenges and develop scalable platform solutions.
Engineering Collaboration & Ownership
- Work closely with engineering and product teams to define infrastructure priorities and technical architecture.
- Own technical projects from initial design through implementation, deployment, and ongoing improvement.
- Contribute to engineering standards, architecture decisions, and platform development practices.
- Participate in rapid experimentation and iterative development cycles.
- Help establish the technical foundations required to scale an emerging healthcare AI platform.
Required Qualifications
- 4+ years of professional software engineering experience, with a strong emphasis on backend engineering and infrastructure development.
- Deep proficiency in TypeScript and Node.js.
- Demonstrated experience designing, building, and maintaining production-grade backend systems.
- Strong understanding of distributed systems, asynchronous processing, and scalable infrastructure.
- Experience developing APIs, background jobs, domain services, and event-driven applications.
- Experience working with relational databases such as PostgreSQL.
- Strong knowledge of system reliability, fault tolerance, observability, and performance optimization.
- Experience designing clean software abstractions and reusable platform components.
- Familiarity with AI agents, LLM-based applications, or modern AI infrastructure.
- Experience working in fast-moving engineering environments with significant individual ownership.
- Strong debugging, problem-solving, and technical communication skills.
- Ability to work collaboratively with engineers across infrastructure, product, and customer-facing teams.
Preferred Qualifications
- Hands-on experience developing computer-use agents or autonomous AI systems.
- Experience with browser automation frameworks such as Playwright.
- Experience with workflow orchestration technologies such as Temporal.
- Familiarity with Prisma ORM and modern TypeScript backend architectures.
- Experience with Google Cloud Platform (GCP).
- Experience with Docker, Pulumi, and infrastructure-as-code technologies.
- Experience designing evaluation and observability systems for AI agents.
- Experience integrating LLMs into production applications.
- Familiarity with agent planning, memory, tool use, execution, and recovery systems.
- Experience building automation across multiple applications or external systems.
- Experience working at an early-stage or rapidly scaling technology startup.
- Healthcare technology or workflow automation experience.
- Familiarity with AI-assisted engineering tools such as Cursor and Claude Code.
Technology Stack
The engineering environment includes:
Category, Technologies, Backend Development, TypeScript, Node.js, Database & ORM PostgreSQL, Prisma Workflow Orchestration, Temporal, Browser Automation, Playwright Cloud Infrastructure, Google Cloud Platform (GCP)Containers & Infrastructure, Docker, PulumiAI Technologies, LLMs, AI Agents, Computer-Use Agents Developer, Tools Cursor, Claude Code, Architecture Distributed Systems, APIs, Event-Driven Systems
Ideal Candidate Profile
The ideal candidate is a backend-focused systems engineer who is excited about building the infrastructure behind the next generation of autonomous AI agents.
You should be comfortable working on technically complex problems where reliability, scalability, and thoughtful architecture are essential.
This opportunity is particularly well suited for an engineer who enjoys building foundational infrastructure rather than exclusively developing user-facing applications.
We're Looking For Someone Who:
- Has strong technical depth in TypeScript backend engineering.
- Understands how to design and operate reliable production systems.
- Enjoys working at the intersection of AI agents, infrastructure, and systems engineering.
- Can independently own complex technical projects.
- Has strong architectural judgment and attention to system reliability.
- Enjoys solving difficult problems involving state management, distributed execution, and fault recovery.
- Is comfortable experimenting with emerging AI technologies.
- Can turn complex engineering challenges into reusable platform capabilities.
- Works effectively in a fast-paced startup environment.
- Values clean architecture, maintainable code, and production reliability.
- Collaborates effectively with engineers and technical stakeholders.
- Wants meaningful influence over the development of an emerging AI platform.
Work Environment
This is an on-site engineering position in New York City within a fast-moving healthcare AI startup.
The company emphasizes close technical collaboration, rapid iteration, and strong individual ownership.
Engineers work directly on foundational platform capabilities and are expected to contribute meaningfully to architectural decisions and product development.
The successful candidate should be comfortable working in an environment where technical challenges evolve quickly and engineers are empowered to develop practical, scalable solutions.
Compensation & Position Details
Base Salary: $150,000–$230,000 annually
Equity: Competitive equity package
Employment Type: Full-Time
Location: New York City, NY
Work Arrangement: On-Site
Open Positions: 1–2
Visa Sponsorship: Open to eligible visa transfers, including OPT and H-1B transfers.
Why Join
This is an opportunity to work on foundational technology at the intersection of artificial intelligence, autonomous agents, healthcare automation, and distributed systems.
Rather than simply integrating existing AI APIs into conventional applications, you will help build the infrastructure that allows intelligent agents to execute complex workflows reliably in real-world environments.
Key advantages include:
- Competitive Compensation: $150,000–$230,000 base salary plus competitive equity.
- Foundational Engineering Ownership: Build and shape the infrastructure powering autonomous AI agents.
- Advanced AI Technology: Work directly with LLMs, computer-use agents, browser automation, and workflow orchestration.
- Complex Technical Challenges: Solve problems involving state management, reliability, fault recovery, and distributed execution.
- Healthcare Impact: Develop technology designed to improve complex administrative and operational healthcare workflows.
- Modern Technology Stack: Work with TypeScript, Temporal, Playwright, PostgreSQL, GCP, and modern AI development tools.
- High-Impact Collaboration: Work closely with engineers solving real-world deployment challenges.
- Professional Growth: Gain significant experience developing production AI infrastructure in an emerging technology category.
- Startup Ownership: Influence platform architecture, engineering practices, and long-term technical direction.
Candidate Considerations
This position requires a strong backend and infrastructure engineering foundation.
Candidates whose experience is primarily limited to frontend development, basic application integrations, or experimental AI prototypes without substantial production engineering experience may not be the best fit.
The company is particularly interested in engineers who have demonstrated the ability to build reliable, scalable, production-grade systems and who are genuinely interested in advancing the capabilities of autonomous AI agents.
Candidates must also be comfortable working on-site in New York City and collaborating closely with a rapidly evolving engineering team.
Confidential Search
This position is being presented by Global Placement Firm on behalf of a confidential healthcare AI technology client.
Additional information regarding the company, engineering team, and opportunity will be shared with qualified candidates during the recruitment process.
