Staff Engineer, AI-Assisted Engineering Practices
Hims & Hers3 days ago
Location
US Remote
Workplace
Remote
Type
Full Time
Salary
USD 190,000 – 240,000
Level
Staff
Role
Staff Engineer
Posted
Jun 30, 2026
Full TimeRemoteStaff
The role
Summary
Staff Engineer at Hims & Hers leading the AI for Engineering Productivity initiative, designing and deploying AI-assisted development techniques including code generation, test automation, and refactoring tools across the organization. This role combines hands-on engineering expertise with technical leadership, requiring 8+ years of experience in software engineering with demonstrated success applying AI tools to improve developer productivity, strong backend or fullstack capabilities, and proven mentoring abilities in a fast-paced healthtech environment.
What you'll do
Lead AI-Assisted Development Implementation: Apply AI-assisted development techniques to real-world product and platform challenges, including code generation, test creation, static analysis, and dependency refactoring. Demonstrate practical impact by using AI tools like GitHub Copilot, CodeCombat, or similar solutions to accelerate development cycles and improve code quality across multiple product squads.
Cross-Team Collaboration and Integration: Partner with product engineers, DevOps teams, and the Developer Platform team to seamlessly integrate AI-driven workflows into existing systems, CI/CD pipelines, and development processes. Facilitate adoption by identifying integration points and removing technical barriers to widespread usage.
Scale Platform Services and Frameworks: Translate proven AI techniques into reusable platform services, SDKs, and developer-facing frameworks that enable adoption across the entire engineering organization. Build abstractions and tooling that make AI productivity gains accessible to engineers at all skill levels.
Drive High-Impact Engineering Initiatives: Lead special projects in collaboration with product engineering teams, such as codebase modernization, performance refactors, and CI/CD workflow automation. Demonstrate measurable improvements in velocity, reliability, and code maintainability using AI-augmented engineering practices.
Mentor and Coach Engineering Teams: Guide engineers on the effective and responsible use of AI in day-to-day development work. Foster a culture of continuous learning and experimentation, helping teams understand when and how to leverage AI tools for maximum impact on code quality and developer experience.
Shape AI Engineering Strategy: Contribute to long-term technical strategy for AI integration into the developer platform, engineering practices, and product delivery roadmap. Evaluate emerging AI tools and frameworks, recommend adoption strategies, and establish best practices for AI-assisted engineering at scale.
What we look for
Technical
Backend Development LanguagesProficiency in one or more backend technologies including Node.js, Kotlin, Java, Python, or Go. Strong fundamentals in systems design, concurrency patterns, and backend service architecture.
Frontend and Full-Stack CapabilitiesExperience with modern frontend frameworks such as React, TypeScript, and Next.js. Full-stack proficiency enables better collaboration across product engineering teams and holistic system thinking.
Mobile DevelopmentExperience with mobile platforms including React Native, Swift, or Kotlin/Android. Understanding of mobile-specific challenges, performance constraints, and user experience considerations.
Developer Tooling and Platform EngineeringHands-on experience building or maintaining developer tools, build systems, testing frameworks, or internal platforms. Understanding of developer experience (DevEx) principles and how to design tools that improve engineering velocity.
AI and Machine Learning IntegrationTechnical understanding of AI/ML concepts as they apply to software engineering, including large language models (LLMs), prompt engineering, workflow orchestration frameworks like LangChain and MCP, and responsible AI practices.
Education
Computer Science or Related DisciplineBachelor's degree in Computer Science, Software Engineering, or equivalent practical experience demonstrating foundational computer science knowledge in algorithms, data structures, and system design.
Experience
8+ Years Professional Software EngineeringMinimum 8 years of production software engineering experience with demonstrated progression in technical complexity and scope. Strong background delivering systems at scale with deep understanding of architecture, performance optimization, and system reliability.
Technical Leadership ExperienceProven track record leading engineering teams or squads with responsibility for technical direction, code quality standards, and team development. Experience mentoring mid-level and senior engineers, influencing architectural decisions, and setting technical standards.
AI-Enhanced Development PracticeDemonstrated hands-on experience using AI tools to improve engineering productivity, including AI-assisted code generation and review, automated test authoring and analysis, intelligent refactoring tools, or workflow orchestration with frameworks like LangChain and Model Context Protocol (MCP).
Cloud Infrastructure and DevOpsExperience with containerization, orchestration, and cloud platforms (AWS primary), including Docker, Kubernetes, and CI/CD pipeline design. Understanding of infrastructure-as-code, observability, and deployment automation.
Production System DeliveryDemonstrated success delivering and maintaining production systems across complex, multi-service codebases. Experience navigating technical debt management, code review at scale, and operational excellence in high-stakes environments.
Skills
Required skills
AI-Assisted Code GenerationHands-on experience leveraging AI tools for code generation, code completion, and AI-driven code review. Ability to evaluate generated code quality and integrate AI suggestions into production workflows.
Test Automation and AI TestingExpertise in designing automated test strategies and experience with AI-assisted test generation and test case optimization. Understanding of how AI can accelerate test coverage and reduce testing bottlenecks.
Refactoring and Code QualityStrong ability to lead large-scale refactoring efforts and establish code quality standards. Experience with static analysis tools, linting, and architectural improvements using both traditional and AI-assisted approaches.
CI/CD Pipeline DesignExpertise in designing and implementing continuous integration and continuous deployment pipelines. Experience optimizing build times, test execution, and deployment processes for developer productivity.
System Design and ArchitectureStrong systems thinking and experience designing scalable, maintainable architectures. Ability to evaluate trade-offs, design for reliability, and make technology choices that balance innovation with operational excellence.
Technical MentorshipProven ability to mentor engineers at various levels, elevate technical standards, and influence peers through example. Strong communication skills for explaining complex technical concepts clearly and building shared understanding.
Cross-Functional CollaborationExperience working effectively across engineering disciplines (backend, frontend, mobile, DevOps, platform). Ability to understand different technical perspectives and build consensus around engineering practices.
Nice to have
LLM and Prompt EngineeringExperience working with large language models, understanding model capabilities and limitations, and expertise in prompt engineering for software engineering tasks. Familiarity with GPT-4, Claude, or similar models.
Workflow Orchestration FrameworksPractical experience with workflow orchestration frameworks such as LangChain, Model Context Protocol (MCP), Airflow, or similar tools. Understanding of how to chain AI tools and services together for complex engineering tasks.
Platform EngineeringBackground in building internal developer platforms, golden paths, or engineering infrastructure that scales across large organizations. Experience designing APIs and abstractions for developer tooling.
Observability and Performance OptimizationDeep expertise in observability tools, distributed tracing, and profiling. Experience optimizing systems for performance and building data-driven approaches to engineering decisions.
Open Source ContributionActive participation in open source communities, particularly in developer tooling, testing frameworks, or AI/ML projects. Demonstrates thought leadership and ability to work in collaborative technical communities.
TypeScript and Modern Web TechnologiesAdvanced proficiency with TypeScript and modern JavaScript frameworks. Strong understanding of type safety benefits and ability to guide architectural decisions in full-stack environments.
Kubernetes and Container OrchestrationAdvanced expertise in Kubernetes cluster management, helm charts, service mesh technologies, and cloud-native architecture patterns for both applications and tooling.
Compensation & benefits
Salary
USD 190,000 – 240,000 (annual)
Stock options
Available
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Hims & Hers
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Hims & Hers is a digital health company that provides affordable and convenient healthcare services to patients through a direct-to-consumer online platform. The company offers prescription medications, treatments, and consultations with licensed healthcare providers for a wide range of common conditions including erectile dysfunction, hair loss, and skincare concerns. Hims & Hers operates in the telehealth and e-commerce pharmacy market, making healthcare more accessible by eliminating traditional barriers like lengthy doctor visits and expensive in-person consultations. The company is on a mission to make healthcare more affordable, accessible, and transparent for everyday people.
San Francisco, USAFounded 2017hims.com
Tech Stack
Languages
Node.jsPythonJavaKotlinGoTypeScriptReact and React NativeSwift
Frameworks
ReactNext.jsLangChainModel Context Protocol (MCP)
Databases
PostgreSQLRedisMongoDB
Tools
DockerKubernetesAWSGitHub ActionsGitGitHub Copilot and AI Code AssistantsMonitoring and Observability ToolsTesting Frameworks
Other
Microservices ArchitectureInfrastructure as CodeGraphQLAPI Design and REST PrinciplesDevOps and SRE PracticesLarge Language Models (LLMs)