Senior/Staff Full Stack Engineer, Applied AI

Fora•New York City, NY

15h•$155,000 - $225,000•Hybrid

About The Position

Fora is seeking a seasoned Senior / Staff Full Stack Engineer to contribute to the development of Fora’s rapidly expanding suite of AI-driven products and infrastructure. The ideal candidate will have a strong understanding of AI, experience with LLMs in production, and the ability to thrive in an ambiguous environment with evolving APIs and SDKs. This role is crucial in building Via, an AI co-pilot designed to assist travel advisors by automating time-consuming tasks, enabling them to operate larger businesses and focus on client relationships and trip curation. The position involves working across the AI stack, including building MCP tools, optimizing agent orchestration for quality, cost, and speed, and developing evaluation and observability systems for non-deterministic AI. Key responsibilities include partnering with Product Managers and Designers to define the AI roadmap, designing and building MCP tooling to expose data and service layers, and hardening the agent orchestration layer for reliability and efficiency. The role also involves improving system reliability through evaluations, regression suites, tracing, and logging, with a focus on performance, latency, architecture, and clean code. Collaboration with other engineering teams to define end-to-end solutions and owning features from conception to delivery are also key aspects of this position. The engineer will play a vital role in establishing best practices for Applied AI at Fora.

Requirements

Bachelor's Degree in Computer Science, or equivalent practical experience
5+ years of experience in backend and frontend development
3+ years experience using React / Vue.js / Angular.io
3+ years experience with Python, using Django / Flask / Alternative
Experience building stateful and event-driven web applications
Experience testing web applications
High API and distributed-systems design skills, with strong fundamentals in relational databases and ORMs
Genuine curiosity and drive to go deep on applied AI – you're excited to spend your days making agents impactful, but reliable; you learn fast in a field that changes month-to-month or even day-to-day
Ability to be a team player, with strong communication and collaboration skills
An entrepreneurial mindset and comfort with ambiguity and fast iteration

Nice To Haves

Hands-on experience shipping LLM-powered features in production – MCP tools, agentic loops, structured outputs, streaming (SSE), prompt design, retrieval, evals
Familiarity with the modern agent stack: the Model Context Protocol (MCP), LLM provider SDKs (e.g., Anthropic, OpenAI), and agent / eval frameworks
Experience designing evaluation and observability for non-deterministic AI systems (offline evals, LLM-as-judge, tracing, prompt / version tracking)
Daily use of AI coding tools as part of how you build
Experience with async task and streaming infrastructure (Celery, Redis, RabbitMQ, or similar)
AWS experience
Kubernetes experience

Responsibilities

Partner with the team’s Product Manager and Designer to define and prioritize Fora’s Applied AI roadmap, turning ambiguous goals into shippable agent capabilities
Help design and build our MCP tooling – exposing Fora’s data and service layers through permission-aware MCP tools that agents can call on an advisor's behalf, with the proper guardrails in place so that we only ever act on the right data at the right time
Build and harden our agent orchestration – tool-calling loops, streaming responses, multi-step workflows, retries and guardrails, and the contracts between Fora’s advisor portal and the AI service
Continue improving the reliability of a non-deterministic system by designing evals, regression suites, tracing, and logging event metrics so we can measure quality, catch tool-call drift, and ship prompt, model, and tool changes with less risk
Focus on performance, latency, architecture, and clean code – advisors feel every millisecond of a streamed response and every wrong tool call
Collaborate with engineers across the company to define end-to-end solutions that span the AI services, the core Django platform, and our portal frontend
Take features from 0 → 1, owning an entire solution from design to implementation to delivery and beyond
Help establish the patterns, primitives, and best practices for Applied AI at Fora as the teams surface area grows