AWSCloudDockerGraphQLJavaJavaScriptKubernetesNode.jsPostgresReactRuby on RailsSQLTypeScriptGoC#C++CGolangRubyAIMLGenAILLMOpenAIAnthropicRAGAgenticRailsFargateLambdaPostgreSQLCI/CD
About this role
Role Overview
Full-Stack Development: Focus on our back-end and front-end codebase to develop and maintain SmithRx product features using Golang, GraphQL, SQL, React, JavaScript/TypeScript, Node, and Java.
Bridge the Stochastic/Deterministic Gap: Architect and implement robust "safety rails" surrounding LLMs by developing deterministic software that manages, validates, and encapsulates the stochastic nature of AI models, ensuring the high-precision accuracy required for healthcare data.
Implement Context-aware systems: Help design and build retrieval-augmented generation (RAG) pipelines and stateful orchestration logic to integrate data sources with LLMs, enabling development of complex, multi-step agentic workflows.
Collaborate: Work with technical leads to understand functional and technical requirements to produce high-quality, scalable software.
Learn and Apply Best Practices: Study and apply software development best practices, design patterns, and modern tools across every project.
Extend the Platform: Leverage frameworks such as GraphQL, React, and GORM to expand the capabilities of our platform.
Cloud Infrastructure: Learn to effectively use AWS technologies at production scale, including Lambda and Fargate, to handle various job types and batch processing.
Quality Assurance: Ensure code is fully tested end-to-end, maintains high code coverage, and that all features are thoroughly documented.
Production Support: Quickly learn to troubleshoot production issues by performing triage, assessing impact, executing mitigation plans, and performing root cause analysis to prevent recurrence.
Culture of Learning: Contribute to a collaborative culture through code reviews and the exploration of new technologies.
AI Innovation: Actively seek out and share new AI tools and technologies to improve software delivery speed and quality.
Requirements
Education: BS in Computer Science and 1 year of experience or a MS in Computer Science.
Background: Besides education, participation in coding competitions or fully released independent projects, internship experience related to AI is a plus.
Technical Knowledge: Experience with a compiled language such as Go, Java, C#, or C++ (Go experience is a strong plus).
AI/ML: Solid ML/AI concepts, knowledge and relevant coursework, experience using GenAI tools to build AI-native high-quality, production-ready software is a plus; an understanding of the pitfalls and limitations of AI is a must.
Database Fundamentals: Ability to write effective and efficient queries with relational databases (specifically PostgreSQL), including basic schema design.
Familiarity or hands-on experience with Agentic Frameworks, MCP, LLM APIs (Anthropic/OpenAI) and basic Prompt Engineering Evals
API Design: A solid grasp of the fundamentals of designing and implementing scalable APIs, along with an understanding of design patterns and testing best practices.
Cloud & DevOps: A basic understanding of GraphQL APIs, CI/CD pipelines, AWS, Docker, and Kubernetes.
Soft Skills: A positive, non-dogmatic, team-first attitude with the flexibility to navigate ambiguity.
Tech Stack
AWS
Cloud
Docker
GraphQL
Java
JavaScript
Kubernetes
Node.js
Postgres
React
Ruby on Rails
SQL
TypeScript
Go
Benefits
Highly competitive wellness benefits including Medical, Pharmacy, Dental, Vision, and Life Insurance and AD&D Insurance
Flexible Spending Benefits
401(k) Retirement Savings Program
Short-term and long-term disability
Discretionary Paid Time Off
Paid Company Holidays
Wellness Benefits
Commuter Benefits
Paid Parental Leave benefits
Employee Assistance Program (EAP)
Well-stocked kitchen in office locations
Professional development and training opportunities