Senior Software Engineer, Backend; AI

About Posh

We are all social creatures, but the dominant “social” companies today have evolved into digital loneliness machines, driving isolation, anxiety, and mental health challenges around the world.

Human connection is lost. Posh is a beacon guiding us back.

Posh enables anyone to build an IRL community based on shared interests, while connecting consumers with the communities of people just like them. Founded by event organizers who were frustrated with the growing loneliness epidemic and the tools available to build their own event brand, we’ve built the ultimate platform for launching, monetizing, and finding IRL communities of people just like you.

In just 5 years, Posh has grown to a team of 65, expanded to 7M+ users, secured $70m in venture funding, and facilitated over $300M in transactions.

We’re looking for a Senior Backend Engineer to join our newly formed AI R&D pod—a small, fast-moving team dedicated to building the future of AI-native product experiences at Posh.

This is a backend-focused role with a strong emphasis on systems architecture and AI implementation. You will be responsible for building the intelligent, scalable, and reliable systems that power our AI features. Your work will focus on designing and deploying sophisticated Multi-Agent Systems
, moving beyond simple RAG to create truly autonomous and helpful user experiences.

You’ll work closely with frontend engineers and product designers to bring cutting‑edge AI tools to our platform. Expect to build robust APIs, architect data flows for evaluations and fine‑tuning, and pioneer new ways to leverage AI within our existing infrastructure. This represents a unique opportunity to build the foundational backend of our AI products, with the chance to ship experimental features to a large, growing, and highly engaged user base.

This is a hybrid role at our NYC office in SoHo.

• Build and Scale AI Services: Design, build, and maintain scalable backend services and APIs for AI-powered features, writing primary production code in Python
  .

• Architect Multi-Agent Systems: Move beyond standard RAG to design and implement complex, hierarchical Multi-Agent Systems that can perform sophisticated, multi-step tasks.

• Implement Evaluation and Fine‑Tuning: Build robust frameworks to evaluate the quality of AI systems and manage fine‑tuning pipelines to continuously improve model performance.

• Own Cloud Infrastructure with IaC: Define, deploy, and manage our AI infrastructure using Terraform
  . You'll be responsible for scaling our container‑based serverless solutions while ensuring reliability and performance.

• Optimize for Efficiency: Deeply analyze the tradeoffs between model performance, latency, and cost to make pragmatic, business‑aware technical decisions when using managed AI services.

• Integrate Across the Stack: Collaborate with our core engineering teams by occasionally working in Type Script (Node.js) to integrate AI features into our main application.

• 3–6+ years of backend or full-stack engineering experience
  , with a proven track record of shipping high-quality, scalable systems in fast-paced environments.

• Deep expertise in Python and its ecosystem for web services and data processing.

• Strong experience with Infrastructure as Code (Terraform), a major cloud platform (e.g., GCP, AWS, Azure), and deploying containerized applications.

• A passion for shaping 0→1 products in a lean, fast-paced R&D environment where you'll help define new playbooks for AI-native experiences.

Bonus points for:

• Pragmatic AI/ML Exposure: Familiarity with managed AI services (e.g., Vertex AI, AWS Bedrock), working with LLMs, or building advanced AI systems is a plus. Experience with model evaluation frameworks (e.g., RAGAs, Lang Smith, Deep Eval) or fine‑tuning is helpful but not required. The ability to think about tradeoffs between cost, latency, and performance is valuable.

• Experience with open-source agentic frameworks (e.g., Lang Graph, CrewAI, Strands, etc) is a plus.

• Experience with MLOps, data engineering, or a background in consumer, marketplace, or event-driven platforms.

We believe…