Software Engineer - AI

Newfold Digital; Argentina; Presencial; ARS 181.094.000 - 271.641.000; Jornada completa

Descripción de la vacante

Newfold Digital is seeking an Applied AI Engineer for its AI Center of Excellence to build production AI experiences across networks and services. You will work with senior engineers to turn product problems into reliable, secure AI systems, focusing on practical AI probl em solving, tool calling, and scalable workflows.

The role requires hands-on Python, FastAPI, and experience with RAG, embeddings, and model integration, with a focus on reliable production deployments and observability.

Formación

• 3+ years of professional software engineering in backend or cloud systems.
• At least 1 year building Applied AI, LLM, or agent-based apps in production.
• Strong Python and API development with production-grade tooling.

Responsabilidades

• Translate product requirements into practical AI solutions using LLMs and tools.
• Build production AI services with Python, FastAPI, and databases.
• Develop robust tool calling agents and multi-step workflows with internal APIs.

Conocimientos

Python

FastAPI

Distributed systems

LLM integration

RabbitMQ/Kafka

Herramientas

PostgreSQL

Redis

SQLAlchemy

Descripción del empleo

Applied AI Engineer, AI Center of Excellence

Who We Are.

Newfold Digital is a leading web technology company serving millions of customers globally. Our customers know us through our robust portfolio of brands. We have some of the industry's most prominent and storied go-to-market brands, including Bluehost, HostGator, Domain.com, Network Solutions, Register.com and Web.com. We help customers of all sizes build a digital presence that delivers results. With our extensive product offerings and personalized support, we take pride in collaborating with our customers to serve their online presence needs. The strength of our company lives in the intersection of our people, our customers, and our brands.

Whatyou’lldo & howyou’llmake your mark.

We are looking for a hands on Applied AI Engineer who combines strong software engineering fundamentals with practical AI problem solving. You will help build production AI experiences across Network Solutions, including conversational agents, business and website creation, knowledge and FAQ agents, content experiences, domain discovery, and intelligent automation.

You will work with senior engineers, architects, and product partners to turn customer and product problems into reliable, secure, observable, and cost efficient AI systems. This is an applied engineering role focused on building, measuring, and continuously improving real AI products.

Who you are & whatyou’llneed to succeed

• Translate product requirements into practical AI solutions using LLMs, RAG, tool calling, agents, deterministic workflows, or traditional software where appropriate.
• Build production AI services using Python, FastAPI, asynchronous workers, PostgreSQL, Redis, queues, model APIs, and external tools.
• Implement reliable tool calling agents and multi step workflows that interact with internal APIs, MCP tools, business systems, and knowledge sources.
• Build event driven workflows using RabbitMQ, Kafka, Azure Service Bus, or equivalent platforms, including retries, dead letter handling, idempotency, and failure recovery.
• Build and improve RAG systems covering ingestion, chunking, embeddings, hybrid retrieval, reranking, metadata filtering, context construction, and citations.
• Integrate models from OpenAI, Anthropic, Google, xAI, and open weight ecosystems, and help select models based on quality, latency, reliability, and cost.
• Build and run AI evaluations using curated datasets, regression tests, retrieval metrics, LLM as judge techniques, groundedness checks, and tool execution evaluation.
• Debug hallucinations, retrieval failures, incorrect tool usage, agent loops, latency issues, provider failures, and unexpected inference costs.
• Operate as an AI powered engineer using Cursor, Claude Code, OpenAI Codex, or equivalent coding agents to accelerate implementation, testing, debugging, refactoring, and documentation.

What We’re Looking For

• 3 or more years of professional software engineering experience building production backend, distributed, or cloud based systems.
• At least 1 year of hands on experience building Applied AI, LLM, RAG, NLP, or agent based applications, with production experience strongly preferred.
• Strong Python skills including FastAPI, asynchronous programming, Pydantic, SQLAlchemy or SQLModel, and production API development.
• Good backend and distributed systems fundamentals including REST APIs, concurrency, background processing, caching, reliability, and production debugging.
• Hands on experience with RabbitMQ, Kafka, Azure Service Bus, or equivalent queue and messaging architectures is required.
• Hands on experience integrating LLM APIs and building structured output, function calling, tool calling, or agent execution workflows.
• Experience building or contributing to a RAG or knowledge grounded system, including retrieval, embeddings, indexing, context construction, and evaluation.
• Working knowledge of PostgreSQL and data modeling, with exposure to Redis, pgvector, vector databases, or hybrid search technologies.
• Demonstrated use of AI coding agents such as Cursor, Claude Code, Codex, or equivalent tools as a regular part of software engineering work.

Nice to have.

You should be comfortable going beyond a working demo and understand the core engineering patterns needed to make AI systems reliable in production.

What Will Make You Stand Out

• Understanding of prompting, structured outputs, tool schemas, context management, retries, fallbacks, rate limits, caching, and streaming responses.
• Ability to use experiments and evaluations to compare approaches using measurable outcomes rather than subjective testing alone.
• Understanding of retrieval quality, grounding, hallucination mitigation, prompt injection risks, tool authorization, and practical agent guardrails.
• Experience with Docker, CI/CD, automated testing, logging, observability, distributed tracing, OpenTelemetry, Langfuse, or similar tooling.

Curiosity, strong problem solving, solid software engineering fundamentals, and the ability to learn quickly and turn ideas into reliable production features are the foundation for this role.

Join us to build the agent-powered backbone of our AI platform—robust, model agnostic, and ready for millions of users.

This Job Description includes the essential job functions required to perform the job described above, as well as additional duties and responsibilities. This Job Description is not an exhaustive list of all functions that the employee performing this job may be required to perform. The Company reserves the right to revise the Job Description at any time, and to require the employee to perform functions in addition to those listed above.