Machine Learning/AI Engineer

Job not on LinkedIn

🔥 1 minute ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Ambush

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2015

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Ambush is a People Company that specializes in identifying, retaining, and integrating highly-talented remote designers and engineers into teams across various sectors. With almost a decade of experience, Ambush focuses on building long-term, dedicated partnerships, providing clients with exceptional software development and design services. The company prides itself on its human-centered approach, remote team integration, and commitment to quality, making it a trusted partner for organizations in the financial, medical, and privacy sectors.

📋 Description

• Design, build, and deploy enterprise-grade GenAI and Agentic AI solutions for complex financial services workflows • Build workflows for exception classification, triage, root-cause analysis, impact assessment, and remediation recommendations • Develop agentic workflows with orchestration, tool/function calling, state management, and human-in-the-loop validation • Correlate new exceptions with historical issues, root causes, business rules, and transaction/data attributes • Build Python and SQL services to query, transform, and analyze large structured enterprise datasets • Develop reusable tools and services for AI-agent retrieval, investigation, analysis, and workflow execution • Integrate AI applications with enterprise APIs, databases, workflow/ticketing platforms, and internal data sources • Apply RAG and context retrieval over regulatory documents, historical knowledge, and issue repositories • Implement confidence scoring, validation, guardrails, and traceability for AI-generated outcomes • Build backend services and APIs using Python/FastAPI and deploy them on a major cloud platform • Implement testing, logging, evaluation, observability, and production engineering practices • Collaborate with onshore and offshore engineers, architects, business analysts, data engineers, and application teams

🎯 Requirements

• Strong hands-on proficiency in Python backend development and production-grade services with frameworks such as FastAPI • Strong SQL and data analysis skills with large structured datasets • Proven experience building LLM/GenAI applications beyond proof-of-concept chatbots • Hands-on experience with an agent or workflow orchestration framework such as LangGraph, Google ADK, CrewAI, AutoGen, Semantic Kernel, or equivalent • Understanding of tool/function calling and reusable agent tools • Experience with RAG and retrieval techniques • Experience implementing LLM evaluation, guardrails, and validation • Software engineering fundamentals including Git, testing, code review, and CI • Experience deploying backend services on a major cloud platform; AWS preferred, GCP or Azure considered • Strong analytical, debugging, and root-cause analysis skills • Very good English and ability to collaborate across distributed engineering and business teams • Pragmatic understanding of deterministic logic versus LLM use • Experience level: Senior-level • Nice to have: financial services experience, including regulatory reporting, capital markets, trade lifecycle, post-trade processing, transaction reporting, reconciliations, exception management, or risk and controls • Nice to have: familiarity with EMIR, MiFID II, or SFTR • Nice to have: Model Context Protocol (MCP) and reusable agent tool interfaces • Nice to have: Knowledge Graphs, Graph RAG, or data lineage • Nice to have: vector databases, hybrid search, or re-ranking • Nice to have: AI observability and evaluation frameworks • Nice to have: AWS AI services such as Bedrock and SageMaker; Docker, Kubernetes, and Terraform • Nice to have: translating requirements into specifications, tasks, and acceptance criteria • Nice to have: Claude Code or similar AI coding assistants • Nice to have: basic React or frontend integration experience • Must answer whether based in Brazil

🏖️ Benefits

• People-first company culture • Supportive, trusted, and empowering work environment • Team collaboration and long-term partnership focus • Opportunity to work on meaningful products and AI solutions • Opportunity to collaborate with global/onshore and offshore teams