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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