Lead Applied AI Engineer

Qualifications

• 5+ years of software engineering experience, with strong backend expertise in Python (FastAPI/Flask) and experience with TypeScript/React for integration

• Demonstrated track record of shipping AI features into production (not just prototyping)

• Hands-on experience with LangChain, LlamaIndex, LangGraph, AutoGen, or similar orchestration tools

• Deep knowledge of RAG, vector databases (Pinecone, FAISS, Weaviate, Chroma), embeddings, and prompt orchestration

• Experience building guardrails, monitoring, and eval frameworks for production LLM features

• Cloud deployment experience (AWS/GCP/Azure), containerization, CI/CD, observability

• 3 more items(s)

Benefits

• Package: $180K–$250K base salary + meaningful equity + comprehensive benefits

Responsibilities

• The Senior Applied AI Engineer will play a key role in architecting and delivering AI-powered features that sit at the heart of the platform

• This role involves end-to-end ownership — from designing retrieval pipelines and agent workflows, to deploying production-ready, reliable, and cost-efficient features

• Collaboration with product, design, and data teams will be central to turning ambitious ideas into tools that deliver measurable customer value

• Architect and build retrieval-augmented generation (RAG) pipelines and semantic search systems for financial data

• Design agentic workflows to automate complex compliance and reporting tasks

• Implement guardrails, monitoring, and evaluation frameworks to ensure accuracy, safety, and auditability in a regulated environment

• Optimize latency, cost, and reliability of LLM-powered features in production

• Partner with cross-functional teams to deliver customer-facing copilots and assistants that drive adoption and engagement

• Evaluate emerging models, frameworks, and tools, and integrate them into production

• 6 more items(s)

More job highlights

Job description

Lead Applied AI Engineer

About the Company

A high-growth, venture-backed Series B fintech is building the next generation of AI-native financial products.

Their platform uses applied AI to transform how businesses make financial decisions through real-time insights, automation, and intelligent workflows.

They’re scaling quickly and seeking engineers who can take the latest advances in LLMs and a...pplied AI and ship them into production for thousands of users.

The Role

The Senior Applied AI Engineer will play a key role in architecting and delivering AI-powered features that sit at the heart of the platform.

This role involves end-to-end ownership — from designing retrieval pipelines and agent workflows, to deploying production-ready, reliable, and cost-efficient features.

Collaboration with product, design, and data teams will be central to turning ambitious ideas into tools that deliver measurable customer value.

Key Responsibilities

• Architect and build retrieval-augmented generation (RAG) pipelines and semantic search systems for financial data.

• Design agentic workflows to automate complex compliance and reporting tasks.

• Implement guardrails, monitoring, and evaluation frameworks to ensure accuracy, safety, and auditability in a regulated environment.

• Optimize latency, cost, and reliability of LLM-powered features in production.

• Partner with cross-functional teams to deliver customer-facing copilots and assistants that drive adoption and engagement.

• Evaluate emerging models, frameworks, and tools, and integrate them into production.

Candidate Profile

• 5+ years of software engineering experience, with strong backend expertise in Python (FastAPI/Flask) and experience with TypeScript/React for integration.

• Demonstrated track record of shipping AI features into production (not just prototyping).

• Hands-on experience with LangChain, LlamaIndex, LangGraph, AutoGen, or similar orchestration tools.

• Deep knowledge of RAG, vector databases (Pinecone, FAISS, Weaviate, Chroma), embeddings, and prompt orchestration.

• Experience building guardrails, monitoring, and eval frameworks for production LLM features.

• Cloud deployment experience (AWS/GCP/Azure), containerization, CI/CD, observability.

Why Apply?

• Impact: Shape the core AI features of a rapidly scaling fintech.

• Cutting-edge: Work with the latest foundation models (OpenAI, Anthropic, LLaMA, Gemini) and frameworks.

• Ownership: Opportunity to take features from concept → production in a fast-moving environment.

• Growth stage: Series B, backed by top investors, high customer demand.

• Package: $180K–$250K base salary + meaningful equity + comprehensive benefits.

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