Applied AI Engineer
Indexed description
Your Role in Our Mission
As an Applied AI Engineer, you will operate as a vision-driven Forward Deployed Engineer (FDE), embedding directly with teams across the organization to identify high-impact opportunities, build AI-powered products, and deliver measurable business outcomes. This is not a traditional engineering role. You'll work at the intersection of engineering, product, and business operations—owning projects end-to-end, from stakeholder discovery and process mapping to solution design, implementation, deployment, and optimization.
How You’ll Make An Impact
AI Discovery & Business Transformation
- Embed with Operations, Support, Risk, Finance, Trading, and Partner teams to understand workflows and identify high-impact automation opportunities
- Conduct stakeholder interviews, process mapping, and workflow analysis to quantify inefficiencies and establish improvement targets
- Build business cases and ROI models that prioritize AI initiatives with measurable operational impact
- Design, prototype, and deliver internal AI-driven tools and automation solutions that reduce manual effort across departments
- Build intelligent workflows, investigation assistants, operational copilots, and knowledge systems that improve efficiency and decision-making
- Create scalable solutions that generate measurable operational savings and process improvements
- Lead the development of customer-facing AI products across the FundedNext ecosystem, including AI-powered support assistants and intelligent analytics experiences
- Build and iterate on AI prototypes, rapidly validating ideas before transforming them into production-ready solutions
- Improve customer experience through AI-powered insights, automation, and self-service capabilities
- Build solutions using prompt engineering, Retrieval-Augmented Generation (RAG), vector databases, MCP integrations, agentic workflows, and modern AI frameworks
- Evaluate emerging AI technologies and integrate practical innovations into products and internal systems
- Develop and maintain AI-ready knowledge repositories that improve information accessibility across the organization
- Drive the adoption of AI-assisted coding tools and AI-native engineering practices across teams
- Leverage AI coding agents such as Claude Code, Cursor, Windsurf, and similar tools to accelerate development, debugging, testing, and code review
- Promote practical AI adoption through experimentation, enablement, and knowledge sharing
- Own end-to-end delivery of AI initiatives—from discovery and prototyping through production deployment and post-launch optimization
- Present findings, recommendations, and implementation plans to leadership and key stakeholders
- Translate technical concepts into measurable business outcomes and ROI
- Monitor adoption, performance, and impact to ensure delivered solutions achieve their intended objectives
- 4+ years of software engineering experience, including at least 2 years building AI/ML, LLM-powered, or AI-driven products in production environments
- Strong full-stack engineering expertise, with hands-on experience designing, building, and deploying scalable backend services, APIs, and modern frontend applications, backed by a solid understanding of software architecture and production systems
- Strong proficiency in Python and modern AI frameworks such as LangChain, LangGraph, Agno, LlamaIndex, Hugging Face, vLLM, or similar, with deep expertise in LLM architectures, agents, Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, fine-tuning, and AI application development
- Hands-on experience building and deploying production-grade AI solutions, including intelligent assistants, conversational AI, automation systems, and customer-facing AI products
- Experience with the Anthropic ecosystem, including Claude API, Claude Code, MCP workflows, and advanced AI-native engineering practices leveraging modern coding agents
- Strong understanding of APIs, Docker, microservices, cloud platforms (AWS, GCP, or Azure), and scalable software architecture
- Proven ability to conduct stakeholder discovery, analyze business processes, translate business challenges into technical solutions, and communicate effectively with both technical and non-technical audiences
- Experience in fintech, trading, brokerage, or financial services is a strong advantage
- You thrive in ambiguity and consistently turn unclear business problems into shipped products
- You combine deep technical expertise with strong product thinking and business judgment
- You are equally comfortable discussing ROI with leadership and writing production code
- You take ownership of outcomes, not just implementation
- Take-home assessment
- 30 minute HR interview with the Talent Acquisition team member
- 45 minute Problem Solving Interview (with talent acquisition team & department front line manager)
- 60-minute Bar Raiser Interview (with head of department & talent acquisition lead)
Apply now and be part of our journey — the future is calling, and it starts with you.
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