Senior AI Engineer

Motum; Buenos Aires; A distancia; ARS 227.628.000 - 318.679.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote work

Ownership over AI systems

Direct collaboration with US teams

Growth in fintech AI

Descripción de la vacante

Motum is partnering with a fast-growing US fintech AI company to join a remote, full-time team. As a Senior AI Engineer, you will build production-grade LLM apps, connect AI models to financial data, and ship reliable AI features to production.

You will work closely with product managers and engineers, writing robust Python services, and ensuring security, observability, and cost management in a fintech context.

Formación

• 5+ years of software or AI engineering experience.
• 2+ years building with large language models.
• Experience shipping LLM-powered features to production.
• Advanced Python and backend service design.
• Strong knowledge of RAG, embeddings, vector search, and document processing.
• Production experience with OpenAI, Anthropic, or comparable APIs.
• Experience with agent workflows using LangGraph, LangChain, or LlamaIndex.
• Experience designing REST APIs with FastAPI.
• Strong PostgreSQL and data modeling knowledge.
• Experience with vector search tech like pgvector, Pinecone, Weaviate, or OpenSearch.
• Cloud deployment and monitoring (AWS/GCP/Azure).
• Clear English communication within a distributed US team.

Responsabilidades

• Build production LLM applications for financial research, document processing, decision support, and workflow automation.
• Design RAG pipelines using document ingestion, chunking, metadata filtering, embeddings, reranking, and hybrid search.
• Develop AI agents using APIs, databases, internal services, and external tools to complete multistep tasks.
• Implement structured outputs, tool calling, memory, state management, retries, and human approvals.
• Build evaluation suites for retrieval quality, factual accuracy, latency, and cost.
• Create safeguards for hallucinations, prompt injection, sensitive data, and unauthorized tool access.
• Design and maintain Python services using FastAPI and PostgreSQL.
• Deploy, monitor, and improve AI workloads in a cloud environment.
• Collaborate with product managers, engineers, and leadership.
• Review architecture decisions and help establish engineering standards.

Conocimientos

5+ years

2+ years LLM

Python

Backend services

RAG architecture

OpenAI APIs

LangGraph LangChain

REST APIs FastAPI

PostgreSQL

Vector search

Cloud (AWS/GCP/Azure)

English communication

Herramientas

LangGraph

LangChain

LlamaIndex

FastAPI

PostgreSQL

OpenAI API

Weaviate

Pinecone

Descripción del empleo

About Motum

Motum connects experienced developers, engineers, and technical professionals with US companies buildingcommitted, long-term tech teams. Our roles are fully remote and full-time, designed for people who want realownership, meaningful work, and the opportunity to grow inside US-based dynamic teams.

When you joinMotum, you work full-time with one company, integrate directly into their team, and build a career with long-term impact. Ready to join us?

About the Client

Our client is a fast-growing US fintech AI company building intelligent software for modern financial teams.

Its platform brings together financial, operational, and customer data to help companies automate complex workflows, identify risk, and make faster decisions. The team is now expanding its AI capabilities across document intelligence, financial research, data retrieval, and workflow automation.

You will join a small product-focused engineering team where AI is a core part of the product rather than an experimental feature. Your work will move directly into production and be used in high-trust financial workflows where accuracy, security, and reliability matter.

About the Role

We are looking for a Senior AI Engineer to design, build, and operate production-grade LLM applications and AI agents.

You will develop retrieval and knowledge systems, connect language models to financial data and external tools, and create agent workflows that can complete complex tasks reliably. You will also establish the evaluation, observability, and security practices needed to run these systems in a fintech environment.

This role is best suited to an engineer who has already shipped generative AI features into production and understands the difference between a successful prototype and a dependable product.

Responsibilities

• Build production LLM applications for financial research, document processing, decision support, and workflow automation
• Design RAG pipelines using document ingestion, chunking, metadata filtering, embeddings, reranking, and hybrid search
• Develop AI agents that use APIs, databases, internal services, and external tools to complete multistep tasks
• Implement structured outputs, tool calling, memory, state management, retries, and human approval flows
• Build evaluation suites for retrieval quality, factual accuracy, task completion, latency, and cost
• Create safeguards for hallucinations, prompt injection, sensitive financial information, and unauthorized tool access
• Design and maintain Python services using FastAPI and PostgreSQL
• Deploy, monitor, and improve AI workloads in a cloud environment
• Collaborate directly with product managers, engineers, and company leadership
• Review architecture decisions and help establish engineering standards for the company's AI platform

Qualifications

• 5+ years of professional software engineering, machine learning engineering, or applied AI experience
• 2+ years building applications with large language models
• Experience shipping at least one LLM-powered product or major feature to production
• Advanced Python skills and experience designing maintainable backend services
• Strong knowledge of RAG architecture, embeddings, vector search, reranking, and document processing
• Production experience with OpenAI, Anthropic, or comparable model APIs
• Experience building agent workflows with LangGraph, LangChain, LlamaIndex, or similar frameworks
• Experience designing and consuming REST APIs with FastAPI
• Strong working knowledge of PostgreSQL and data modeling
• Experience with at least one vector search technology, such as pgvector, Pinecone, Weaviate, or OpenSearch
• Experience deploying and monitoring applications on AWS, GCP, or Azure
• Understanding of testing, observability, security, and cost management for production AI systems
• Ability to explain technical tradeoffs clearly in English and collaborate with a distributed US team

Nice To Have

• Experience building AI products for fintech, banking, payments, lending, risk, fraud, accounting, or financial operations
• Experience working with financial documents, transaction data, or other sensitive information
• Experience with LangGraph, MCP, and agent orchestration
• Experience with hybrid search, knowledge graphs, or advanced retrieval techniques
• Experience building automated LLM evaluation and regression-testing systems
• Experience with multimodal models and document intelligence
• Familiarity with SOC 2, data privacy, audit logging, or regulated software environments
• Experience optimizing inference latency and model usage costs
• Familiarity with Docker, Kubernetes, Terraform, and CI/CD pipelines

We Offer

• Grow along a top US company and shape its future
• The chance to help shape an AI-first fintech product during an important stage of growth
• Meaningful ownership over production AI systems
• Direct collaboration with the client's product and engineering teams