Backend Engineer

Jobgether; United States; Remote; USD 140,000 - 180,000; Full time

Benefits offered by this job

Remote-first culture

Competitive compensation

Development budget and conference机会

Job summary

Jobgether is building an AI-powered backend platform for behavioral health organizations. You will be one of the first engineering hires shaping architecture, scalability, and reliability using Java, Spring Boot, Kafka, and AWS.

You will own production-grade backend services, real-time data pipelines, and AI-driven clinical tools while collaborating with founders and clinical teams to translate complex workflows into secure, maintainable solutions.

Qualifications

• 5+ years of software engineering experience delivering production systems.
• Deep expertise in Java and the Spring Boot framework.
• Proficiency with Prometheus and Grafana for monitoring and observability.
• Strong hands-on experience with AWS services (EC2, ECS, EKS).
• Experience designing scalable distributed systems using messaging/streaming (SQS, Kafka, Kinesis).
• Experience with data reliability patterns and resilience techniques.
• Practical experience with LLM technologies and AI/ML pipelines in production.
• Security engineering focus, Spring Security, and healthcare compliance knowledge.
• Ability to model complex workflows and translate into backend logic.
• Experience building asynchronous, event-driven microservices at scale.
• Systems thinking mindset and proactive reliability focus.
• Strong communication with both technical and non-technical stakeholders.

Responsibilities

• Architect, develop, and maintain core backend services to support AI features.
• Implement monitoring, alerts, and observability with Prometheus and Grafana.
• Tune and optimize AWS infrastructure, including auto-scaling and services like EC2, ECS, EKS.
• Build distributed, event-driven systems using SQS, Kafka, and Kinesis for high-volume workloads.
• Apply data reliability strategies with retries, circuit breakers, and disaster recovery.
• Design and improve LLM integration pipelines including prompt engineering and monitoring.
• Enforce security with Spring Security and RBAC, ensuring HIPAA compliance.
• Model clinical workflows and translate requirements into scalable backend logic.
• Lead architecture decisions to support long-term scalability and product evolution.
• Collaborate with founders and clinical teams to deliver end-to-end features.
• Own major features from design through deployment and operation.

Skills

Java

Spring Boot

Distributed systems

Security engineering

Problem solving

Tools

Prometheus

Grafana

AWS

EC2

ECS

EKS

Kafka

Kinesis

SQS

Spring Security

RBAC

Terraform

Job description

Join an ambitious engineering team building AI-powered technology that helps behavioral health organizations operate more efficiently and focus more resources on patient care. As an early engineering hire, you will play a pivotal role in shaping the architecture, scalability, and reliability of a platform designed to transform mental healthcare. You will develop production-grade backend services, distributed systems, and real-time data pipelines using Java, Spring Boot, Kafka, and AWS. Working closely with founders and clinical teams, you will turn complex healthcare workflows into secure, maintainable technical solutions. You will also contribute to AI-driven clinical tools, optimize large-scale asynchronous processing, and establish robust monitoring and security practices. This is an opportunity to take end-to-end ownership of impactful features while influencing technical strategy and product direction in a fast-growing startup.

Accountabilities

• Architect, develop, and maintain core backend services using Java and Spring Boot to support the platform's AI-powered capabilities.
• Design and implement monitoring, alerting, and observability infrastructure using Prometheus and Grafana to maintain visibility into system health and performance.
• Configure and optimize AWS infrastructure, including auto-scaling policies and services such as EC2, ECS, and EKS, balancing reliability, performance, and cost.
• Build distributed, event-driven systems using message queues and streaming platforms such as Amazon SQS, Apache Kafka, and Amazon Kinesis to support high-volume asynchronous workloads.
• Implement data reliability strategies, including redundancy, circuit breakers, retries, graceful failure handling, and disaster recovery procedures.
• Design and improve large language model (LLM) integration pipelines, covering prompt engineering, usage monitoring, and output quality assurance.
• Establish robust security practices using Spring Security and role-based access control (RBAC), ensuring compliance with HIPAA and applicable healthcare data protection requirements.
• Model complex clinical and operational workflows and translate business and domain requirements into well-structured, maintainable backend processes.
• Make foundational architecture and technology decisions that support long-term scalability and evolving product needs.
• Collaborate with founders and clinical stakeholders to translate healthcare challenges into practical, scalable technical solutions.
• Take ownership of major product features throughout the entire lifecycle, from system design and implementation to deployment and ongoing operation.

Requirements

• At least 5 years of software engineering experience, with a strong track record of delivering production systems.
• Deep expertise in Java and the Spring Boot framework, including building and maintaining production-grade backend applications.
• Proficiency in Prometheus and Grafana for monitoring, dashboard development, alerting, and observability.
• Strong hands-on experience with AWS services, including infrastructure provisioning, auto-scaling, EC2, ECS, and/or EKS.
• Proven expertise in designing and operating scalable distributed systems using message queues and streaming platforms such as SQS, Kafka, and Kinesis.
• Experience implementing data reliability patterns, including redundancy, circuit breakers, retry mechanisms, graceful degradation, and failure recovery.
• Practical experience with LLM technologies, including prompt engineering, usage tracking, and quality measurement in production environments.
• Strong security engineering skills, particularly with Spring Security, RBAC, and healthcare compliance standards.
• Experience modeling complex business or domain workflows and translating them into effective backend logic.
• Demonstrated ability to build and operate asynchronous, event-driven systems and microservices at scale.
• A systems-oriented mindset, with the ability to anticipate failure modes, reason about data consistency, and design for resilience.
• Strong problem-solving skills, attention to operational details, and a proactive approach to reliability and performance.
• Excellent communication and collaboration skills, with the ability to work directly with technical and non-technical stakeholders.
• Ability to thrive in a fast-moving startup environment, balancing architectural planning with hands-on implementation and operational ownership.

Additional Experience That Would Be Advantageous Includes

• Audio or signal processing, real-time systems, or media-processing technologies.
• Domain-Driven Design (DDD) principles and practices.
• Advanced expertise with the Confluent Kafka platform.
• Infrastructure as Code (IaC), particularly Terraform.
• Experience with additional cloud platforms such as Google Cloud Platform (GCP) or Microsoft Azure.
• Healthcare technology experience or familiarity with HIPAA compliance requirements.
• AI/ML model deployment, monitoring, and production operations.
• Contributions to open-source projects.

Benefits

• Competitive compensation: Salary aligned with senior engineering roles and relevant experience.
• Healthcare coverage: Comprehensive medical, dental, and vision insurance.
• Remote flexibility: A remote-first culture with flexible working arrangements.
• Influence and ownership: Direct collaboration with founders and meaningful input into company strategy, architecture, and product direction.
• Professional development: A dedicated development budget and opportunities to attend conferences.
• Modern technology stack: The opportunity to work with contemporary backend, cloud, distributed-systems, and AI technologies.
• Technical autonomy: Significant ownership of engineering decisions and the freedom to shape scalable systems.
• Meaningful impact: The opportunity to build technology that helps improve operational efficiency and expand the impact of behavioral healthcare.