Senior Software Engineer

Parakeet Health•San Francisco, CA

19d•$170,000 - $230,000•Onsite

About The Position

We are building a platform that handles all aspects of patient interaction in healthcare, from scheduling to billing, with the patient at the center of every touchpoint. Our tools leverage AI and LLMs to improve efficiency and patient experience. We are a fast-growing, well-funded startup working with over 400 medical practices. The engineering team thrives on innovation, treating LLMs as force multipliers to move quickly and solve complex problems in a domain with a low margin for error. This role involves harnessing LLMs to increase leverage across all engineering tasks, from uncovering product gaps to shipping features rapidly. Engineers work closely with customers, using an internal agent harness with custom skills to build and deploy solutions. The goal is to reach a point where engineers can ship meaningful work without manually writing code. The role requires a blend of technical expertise, strong judgment, and a commitment to quality and compliance, especially when dealing with sensitive health data.

Requirements

3-7 years of relevant engineering experience.
Expertise in Python, Django, and React.
Strong backend fundamentals: experience designing and implementing scalable, robust systems.
Genuine belief that agentic tools are the future of how software gets built.
Ability to make judgment calls regarding patient experience and agent behavior.
Experience working with LLMs as force multipliers.
Strong instincts and genuine curiosity.
Ability to question the status quo and identify better ways of working.
Commitment to shipping products that reach real people.
Honesty about what you don't know and willingness to admit when you are wrong.
Willingness to rotate through mundane tasks without complaint.
Ability to work in a fast-paced environment where problems are not always fully defined.

Nice To Haves

Previous experience at an early-stage startup is a plus.

Responsibilities

Launch new end-to-end agent use cases for live customers within the first two weeks.
Make judgment calls on gray-area decisions related to patient experience, agent behavior, and error recovery.
Harness LLMs to gain leverage across all engineering activities, including problem-solving, identifying edge cases, and accelerating development.
Use LLMs to uncover product gaps, pressure-test ideas, and reduce the time between conception and deployment.
Collaborate closely with customers to understand their needs and inform product decisions.
Plan and build using an internal agent harness with custom skills.
Contribute to building the infrastructure that enables autonomous agent capabilities, including evaluation systems, context graphs, and guardrails.
Expand and build upon existing platforms, such as the referral and prior authorization processing tool.
Design and implement voice and conversation strategies at scale for agents interacting with tens of thousands of patients daily.
Determine appropriate agent behavior and conversation stages, ensuring compliance and routing edge cases to humans.
Build and improve evaluation systems to distinguish between good and incorrect agent responses.
Develop rich context for agents to understand and interact with production codebases and patient data.
Implement guardrails that ensure safe failure modes for agents.
Handle prescription refill requests and other manual, error-prone practice workflows.
Verify and ship fixes identified by agents monitoring production systems.
Develop new features, such as a 'Mark as Reviewed' button for QA auditors, rapidly.
Collaborate with Customer Success Managers (CSMs) and leadership to understand customer feedback and identify new product opportunities.
Sketch and build prototypes for new product ideas.