Senior Software Engineer, AI Platform & Agents
About The Position
We are hiring a Senior Software Engineer to lead the development of our internal AI platform and orchestration components, helping us accelerate the deployment of intelligent Agents and RAG pipelines across the organization. You will own the core infrastructure and SDKs that bridge the gap between raw LLM capabilities and production-grade applications, turning complex AI research and data into seamless, scalable tools for our engineering teams. Your work will directly enable us to automate sophisticated workflows and deliver smarter, AI-driven products to our users. You’ll be a key architect and builder of our internal AI platform, designing components that power various AI Agents and Retrieval-Augmented Generation (RAG) pipelines. You prioritize ensuring that complex logic branches and AI workflows are well-understood, tested, and focused on engineering excellence. You will build APIs and services that are highly intuitive to consume, ensuring our internal teams can seamlessly integrate AI capabilities into their workflows.
Requirements
- Core Development: Expert-level API and service development in Python (required) and/or Go. Experience with SQL, database management
- AI Architecture: Hands-on experience building RAG pipelines, managing vector databases, and orchestrating multi-agent systems.
- Cross-Functional Fluency: Proven ability to communicate technical requirements effectively across Data Science, Data Engineering, and Product domains.
- Cloud Native Principles: Deep understanding of production-tested principles including horizontal scaling, 12-factor application design, and security principles like OWASP.
- Observability: Experience monitoring AI performance and analyzing model/software errors using tools like Sentry, DataDog, or Jaeger.
- DevOps Tools: Proficiency in container-based development with Docker and source control via Git.
- Experience: At least 5+ years of hands-on software development experience—"It’s not the years, it’s the miles."
Nice To Haves
- Experience with AI orchestration frameworks (e.g., LangChain, LangGraph, LlamaIndex, LiteLLM, or CrewAI).
- Production experience with distributed, event-driven, and message-driven architectures.
- Experience building self-service "Platform-as-a-Product" for internal developers.
Responsibilities
- AI Platform Engineering: Build and maintain the core infrastructure, services, and SDKs that empower the rest of the company to leverage LLMs and Agentic workflows.
- Scientific Collaboration: Partner closely with Applied Scientists and Data Scientists to translate experimental models and research into scalable, production-grade AI services.
- Data Strategy: Work with Data Engineers to design robust data pipelines that feed into RAG systems, ensuring high-quality, real-time data retrieval for AI context.
- Internal Onboarding: Act as a technical consultant and facilitator for other engineering teams, helping them successfully onboard their specific AI use cases onto the platform.
- Design & Document: Design, document, and deploy public AI interfaces that provide an exceptional developer experience for internal users.
- Operational Excellence: Collaborate with Site Reliability Engineers (SRE) to deliver AI applications in a repeatable, stable, and highly efficient software development lifecycle.
- Quality Engineering: Develop comprehensive test cases for AI models and workflows, working with QE to ensure deterministic and reliable outcomes in a non-deterministic AI landscape.
Benefits
- 100% medical, dental and vision coverage
- Flexible PTO policy
- Annual home office stipend and WeWork access
- Mental & physical health wellness programs (One Medical, Headspace, Wellhub, and more)!
- Competitive compensation and opportunity for advancement
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
