AI Engineer

Hire Hangar, Inc.; Argentina; Remote; ARS 181,906,000 - 272,860,000; Full time

Job summary

Hire Hangar, Inc. is seeking a hands-on AI Engineer to design, build, and deploy intelligent systems across client environments in a fully remote role. You will work end-to-end on the AI development lifecycle, from prototyping to production deployment and ongoing optimisation.

The ideal candidate thrives at the intersection of machine learning, software engineering, and product thinking, with fluency in modern AI tooling and systems thinking. Remote collaboration with US-based teams is essential.

Qualifications

• Strong programming skills in Python and software engineering fundamentals.
• Hands-on experience building with LLMs via API and SDK.
• Experience with RAG architectures and vector databases (Pinecone, Weaviate, Chroma).
• Familiarity with AI agent frameworks (LangChain, LlamaIndex, AutoGen, CrewAI).
• REST APIs and integrating third‑party services.
• Ability to work autonomously in a fast-paced remote environment.

Responsibilities

• Design and build AI-powered features, pipelines, and automation workflows.
• Integrate and fine-tune LLMs and embedding models into production apps.
• Develop and maintain RAG pipelines and vector search systems.
• Write clean code across backend and API layers for AI features.
• Evaluate and iterate model outputs for quality and reliability.
• Collaborate with cross-functional teams to scope AI solutions.
• Stay current with AI tooling and approaches.
• Document designs, system behavior, and deployment processes.

Skills

Python programming

LLM integration

RAG pipelines

Vector databases

REST APIs

LangChain

LLM tooling

Remote work experience

Cloud platforms

Docker

Tools

Pinecone

Weaviate

Chroma

LangChain

LlamaIndex

CrewAI

Job description

Join Hire Hangar and work with fast-growing global companies while building a long-term career.

Job Title: AI Engineer

Location: Remote

Time Zone: US Time Zones (EST–PST)

Role Overview

We are looking for a hands-on AI Engineer to design, build, and deploy intelligent systems across a range of client environments. This is a technically deep role suited to someone who thrives at the intersection of machine learning, software engineering, and product thinking. You will work across the full AI development lifecycle — from prototyping and model integration to production deployment and ongoing optimisation. The ideal candidate is fluent in modern AI tooling, thinks in systems, and can translate complex technical concepts into scalable, working solutions.

Key Responsibilities

• Design and build AI-powered features, pipelines, and automation workflows from scratch
• Integrate and fine-tune LLMs, embedding models, and other ML systems into production applications
• Develop and maintain RAG pipelines, vector search systems, and agent-based architectures
• Write clean, well-structured code across backend and API layers to support AI feature delivery
• Evaluate, benchmark, and iterate on model outputs to ensure quality and reliability
• Collaborate with cross-functional teams to scope requirements and architect AI solutions
• Stay current with the rapidly evolving AI landscape and proactively introduce relevant tooling and approaches
• Document technical designs, system behaviour, and deployment processes clearly and thoroughly

Required Qualifications

• Strong programming skills in Python; solid understanding of software engineering fundamentals
• Hands-on experience building with LLMs (OpenAI, Anthropic, Mistral, or similar) via API and SDK
• Practical experience with RAG architectures, vector databases (Pinecone, Weaviate, Chroma, etc.), and prompt engineering
• Familiarity with AI agent frameworks such as LangChain, LlamaIndex, AutoGen, or CrewAI
• Solid understanding of REST APIs and experience integrating third‑party services and data sources
• Ability to work autonomously in a fast‑paced remote environment with minimal hand‑holding
• Must have prior remote work experience, be fluent with remote collaboration tools and platforms (such as Slack, Zoom, Google Workspace, Asana, or similar), and have ideally worked with US or UK‑based companies. Applications without this experience will not be considered.

Preferred Qualifications

• Experience with model fine-tuning, RLHF, or custom training workflows
• Familiarity with MLOps tooling and model deployment pipelines (Docker, cloud functions, etc.)
• Exposure to multimodal systems (vision, audio, or document understanding)
• Background in data engineering or working with structured/unstructured data at scale
• Contributions to open-source AI projects or a strong public portfolio of AI work

Tools & Technology

• Python, REST APIs, and relevant AI/ML libraries
• LLM platforms: OpenAI, Anthropic, Mistral, Hugging Face
• Vector databases and embedding infrastructure
• Agent frameworks: LangChain, LlamaIndex, CrewAI, or similar
• Cloud infrastructure (AWS, GCP, or Azure)
• Google Workspace, Slack, Zoom, and remote collaboration tools