W
Writer
Software Engineer (Generative AI)
Skills
Google Cloud PlatformDockerReactTypescriptPythonMicroservicesPostgreSQLAIAWSGitHubKubernetesFastAPIAzure
14 days ago
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Important information
Contract type:
Permanent
Salary:
$146,000 – $240,000 / year
Location:
United States
Work mode:
Onsite
Published on:
9 October 2026
What they need
- Imagine stepping into a role where your code directly empowers the world’s largest enterprises to safely adopt superintelligence
- As a software engineer, generative ai at WRITER, you’ll be at the forefront of expanding human capacity by building the secure, scalable foundation that allows our generative AI solutions to thrive in complex corporate environments
- The impact of this work is massive – for example, in the consumer packaged goods industry alone, our AI adoption is driving 69% revenue increases and 72% cost reductions
- If you thrive on proactivity without red tape and love owning projects from proposal to deployment, you’ll shape the future of AI and contribute to a product that’s changing how the world works
- You’ll report to an engineering director or a senior engineering manager
- Design and develop robust, secure, and scalable generative AI services and applications using Python and modern frameworks to drive enterprise-wide transformation
- Build and optimize high-performance, low-latency APIs and microservices to integrate advanced AI models and sophisticated agentic workflows into our core platform
- Act as a whole-systems thinker by making meaningful system design decisions and owning the architecture of core platform components from initial proposal through production deployment
- Implement and maintain responsive user interfaces using technologies like React and TypeScript to deliver intuitive user experiences and bridge the gap between backend services and frontend enablement
- Drive proactivity without red tape by clearly communicating changes, plans, and proposals to cross-functional teams and collaborating closely with product managers, data scientists, and DevOps engineers
- Partner with DevOps teams to build continuous deployment, logging, and monitoring systems that ensure top-tier performance, security, and reliability across distributed workloads
Benefits
- Health: Selection of employer-covered medical plans, plus dental, vision, life insurance, and FSA.
- Family-friendly: Competitive parental leave policy, working parents can truly own their schedules.
- Hybrid culture: We’re built around a mix of in office collaboration and remote work when needed.
- Finance: Company stock options, plus a 401k plan with employer contributions.
- Growth: Learning and development stipend and generous PTO.
- SF/NY/London office space: Three beautiful sunny offices in three incredibly exciting cities.- This role is designed for a well-rounded engineering generalist who leans heavily into generative AI while bringing a whole-systems mindset to architectural design
- Exposure to enterprise architecture including practical experience implementing IAM, SSO, SAML, OAuth, OIDC, RBAC, robust security best practices, or building services for enterprise administration and billing systems
- Solid grasp of modern web technologies including FastAPI, Asyncio, database systems like PostgreSQL, and hands-on experience leveraging AI developer tooling like Claude, Cursor, or GitHub Copilot to accelerate your engineering workflows
- Proven expertise in building and deploying generative AI applications, leveraging LLMs, vector databases like Pinecone, Weaviate, or pgvector, and modern open-source agentic frameworks
- 3-5+ years of hands-on experience as a software engineer with a strong emphasis on Python development in production environments
- A Connect mindset that thrives in collaborative settings where you actively engage with cross-functional teams and mentor other engineers, a Challenge spirit that drives you to tackle complex technical hurdles and proactively suggest innovative improvements, and an Own attitude where you take full accountability for delivering high-quality, resilient, and scalable code from conception to production
- Practical experience with microservices architecture, RESTful APIs, cloud platforms such as AWS, GCP, or Azure, and containerization with Docker and Kubernetes
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