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Open nowFirst seen 4 days ago

Generative AI Engineer

Nearshore Business Solutions63 open roles

Where
Remote
Work mode
Remote
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Your applicationOpen nowGenerative AI EngineerNearshore Business Solutions · Remote

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Nearshore Business Solutions's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. Nearshore Business Solutions postings stay open a median of 2 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: first seen 4 days ago

Nearshore Business Solutions median: 2 days open

The posting

Generative AI Engineer

Location: LATAM

Type of Contract: Full-Time

Salary Range: Market rates

Language Requirements: Professional English

Our client is seeking a skilled Generative AI Engineer with extensive experience building production-grade AI applications and scalable cloud-native solutions. You will play a key role in designing, developing, and deploying enterprise Generative AI platforms using modern LLM frameworks, AWS services, and event-driven architectures. Your work will directly impact the delivery of innovative AI-powered solutions that drive business efficiency and enhance customer outcomes.

Key Responsibilities

  • Design, build, and deploy production-grade Generative AI applications using Python and modern AI frameworks.
  • Develop and optimize Retrieval-Augmented Generation (RAG) pipelines utilizing LangChain, LangSmith, vector databases, prompt engineering, and LLM orchestration.
  • Architect and deploy scalable cloud-native solutions on AWS using services such as Lambda, Bedrock, S3, DynamoDB, EC2, and Fargate.
  • Build and maintain RESTful APIs using FastAPI, Django, Flask, or similar Python frameworks.
  • Design and implement event-driven microservices using Kafka and distributed system best practices.
  • Collaborate with cross-functional teams in Agile environments to deliver high-quality AI solutions while communicating effectively with technical and business stakeholders.
  • Optimize application performance, reliability, and scalability across cloud infrastructure and AI workflows.

Must-Have Qualifications

  • 7+ years of experience in Software Engineering, Data Engineering, AI Engineering, or a related technical field.
  • Expert-level proficiency in Python development.
  • Proven experience building and deploying production-grade Generative AI solutions.
  • Hands-on experience with LangChain, LangSmith, Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, and LLM orchestration.
  • Strong experience with AWS services including Lambda, Bedrock, S3, DynamoDB, EC2, and Fargate.
  • Experience developing APIs with FastAPI, Django, Flask, or similar frameworks.
  • Strong knowledge of Kafka, event-driven architectures, distributed systems, microservices, relational databases, and NoSQL databases.
  • Experience working in Agile development environments with excellent communication and stakeholder management skills.

Preferred Qualifications

  • Experience designing and deploying multi-agent AI systems.
  • Hands-on experience with Anthropic Claude, OpenAI, Gemini, Llama, or other enterprise LLMs.
  • Experience with graph databases such as Neptune or Neo4j.
  • Knowledge of AI security, red teaming, and LLM vulnerability assessment.
  • Experience implementing AI governance, compliance, and responsible AI frameworks.
  • Experience using Terraform or other Infrastructure as Code (IaC) tools.
  • Experience with Apache Spark and large-scale distributed data processing.
  • Industry experience supporting fraud detection, financial services, telecommunications, or public sector AI solutions.
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    The review screen in CV Rocket: how each CV was read, round by round.

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    An application in CV Rocket: every answer filled in on the employer's form.

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