Senior Software Engineer

Benefits

Pulled from the full job description

Full job description

The Role

Medasync is looking for a hands-on Senior Software Engineer to turn product priorities into secure, reliable, production-ready software.

This is a senior individual-contributor role focused on end-to-end delivery. You will work with the CTO, engineering team, product stakeholders, and subject-matter experts to clarify requirements, shape technical solutions, implement features, validate their behavior, and carry them through deployment and production support.

We are looking for an engineer who takes ownership beyond writing code: someone who can reason through ambiguity, make sound technical tradeoffs, and move work steadily from definition to production.

Modern coding agents are part of how we build software, and LLM inference is part of our product. You should be comfortable using agents to accelerate development without delegating engineering judgment, and understand how to build reliable application workflows around probabilistic models.

Our software supports Skilled Nursing Facilities and other post-acute care organizations by analyzing complex clinical and operational data to improve reimbursement accuracy, care-quality analysis, and audit defensibility. Reliability, security, and explainable behavior matter because our customers depend on these systems in operational and regulated workflows.

What You'll Do

• Own customer-facing features and services from clarified requirements through implementation, testing, deployment, and production support.
• Work with product stakeholders, client success, and subject-matter experts to understand intended behavior, identify gaps, and translate requirements into manageable technical work.
• Design and implement maintainable application architecture, APIs, data flows, background processes, and user-facing functionality.
• Use modern coding agents to accelerate analysis, implementation, testing, refactoring, and documentation while remaining accountable for architecture, correctness, security, and maintainability.
• Build and improve LLM-enabled workflows, including prompt and context design, structured outputs, tool use, model selection, validation, fallback behavior, and integration with deterministic application logic.
• Evaluate LLM behavior using representative examples and measurable criteria; investigate failures, reduce avoidable variability, and make inference workflows observable in production.
• Write automated tests, participate in code review, and ensure new work meets expectations for security, performance, reliability, and operational readiness.
• Break larger initiatives into smaller deliverables that can ship frequently, surface uncertainty early, and challenge unnecessary complexity.
• Diagnose production issues across application code, data, integrations, and infrastructure.
• Improve shared patterns, documentation, and development practices that make the engineering team faster and the platform easier to maintain.

Initial Priorities

In your first months, we expect you to:

• Take independent ownership of defined product initiatives and move them steadily into production.
• Help establish effective day-to-day use of coding agents while ensuring agent-assisted work remains reviewed, tested, secure, and maintainable.
• Improve the evaluation, observability, and reliability of LLM workflows that extract, interpret, summarize, or act on clinical and operational information.

What We're Looking For

We care more about demonstrated ownership, technical judgment, and the ability to ship dependable software than a particular number of years in the field.

You should bring:

• Senior-level software-engineering experience building, deploying, and supporting customer-facing production applications.
• Strong application-development skills across backend services, APIs, databases, integrations, background processing, and user-facing functionality.
• A track record of taking meaningful features or services from requirements through production rather than contributing only to isolated implementation tasks.
• Demonstrated ability to use modern coding agents to increase development velocity while retaining ownership of architecture, correctness, testing, security, and maintainability.
• Practical experience building software that uses LLM inference, including prompts, context management, structured outputs, model APIs, evaluation, error handling, and production monitoring.
• Sound judgment about where probabilistic model behavior is appropriate and where deterministic rules, validation, human review, or fallback paths are required.
• Strong debugging skills and the ability to reason across application code, data, external services, infrastructure, and production behavior.
• Experience with automated testing, code review, CI/CD, observability, and the operational responsibilities that accompany production ownership.
• The ability to clarify ambiguity, explain technical tradeoffs, and keep delivery moving without requiring constant direction.
• Comfort working with sensitive data and treating security, privacy, and data integrity as core engineering requirements.

Our Environment

Our platform is primarily built with Python, Django, PostgreSQL, and AWS. We use containerized and serverless workloads, integrate with healthcare and operational data sources, and use LLM inference in production workflows.

Our exact stack is not a prerequisite. We care more about strong engineering fundamentals and the ability to become productive in an existing system than prior experience with a particular framework or cloud service.

Helpful, but Not Required

• Experience developing AI-enabled products that extract, interpret, summarize, or act on unstructured data.
• Experience evaluating and monitoring LLM quality, cost, latency, and failure modes in production.
• Experience with document processing, retrieval, classification, or workflow automation.
• Experience in an early-stage or high-growth software company.
• Experience with healthcare data, clinical documentation, reimbursement, billing, audit, or another regulated-industry workflow.

How We Work

Medasync is outcome-focused and execution-oriented. We favor simple solutions, manageable scope, clear interfaces, automated tests, and frequent delivery of measurable value. Engineers are expected to challenge assumptions constructively, identify unnecessary complexity, and remain accountable for the services they build after release.

Agentic tools are part of how we increase development capacity, but they do not replace engineering ownership. You are responsible for understanding, reviewing, testing, securing, and supporting work delivered with the assistance of those tools.

Employment Details

• Fully remote position open to candidates based in the United States.
• Benefits include equity and health, dental, and vision insurance.
• Candidates must already be authorized to work in the United States. Medasync is unable to provide current or future visa sponsorship.

Pay: $140,000.00 - $165,000.00 per year

Benefits:

• Dental insurance
• Health insurance
• Vision insurance

Application Question(s):

• Tell us about an AI-enabled product or feature you helped develop that used LLM inference or generative output. What did you personally build, and how did you evaluate and manage the quality and reliability of the model’s output?

Work Location: Remote