AI Software Engineer
Build, Deploy & Evolve Intelligent Products with Nearshore AI Experts
AI Software Engineers turn cutting‑edge machine‑learning models into production‑grade software that delights users and drives revenue. From serverless inference APIs to multimodal chat interfaces, they translate AI breakthroughs into business outcomes—fast.
Chosen by Fast-Growing Teams
Key Focus Areas
Handling prototype‑to‑production gaps, scaling hurdles, and front‑end integration challenges can stall your AI roadmap. Our AI Software Engineers clear that fog by honing in on the high‑impact domains that close the gap between research and reliable user experiences. Explore the focus areas below to see where they’ll move the needle first.
Data Acquisition
& PipelinesData Acquisition & Pipelines
Design resilient batch/stream pipelines that ingest, transform and deliver trustworthy data/feature sets.Data Storage
& ManagementData Storage & Management
Select, model and administer relational & NoSQL stores for scalability, security and performance.Tooling
& Platform EnablementTooling & Platform Enablement
Provision version-controlled, self-service tooling to speed delivery.Real-time
InferenceReal-time Inference
Serve low-latency predictions via micro-services or streaming frameworks, with monitoring for drift & quality.Model
& Algorithm DevelopmentModeling & Algorithm Development
Frame problems, choose algorithms, train, validate, and optimize statistical/ML models.Model
& Deployment ServingModel Deployment & Serving
Package, containerize, and ship models into production.ML Ops & Lifecycle Automation
ML Ops & Lifecycle Automation
Automate CI/CD for ML: version data/models, orchestrate retrains, manage feature stores, monitor performance.Tools & Technologies
Our AI Software Engineers work within a modern AI application stack that ensures flexibility, scalability, and reliability across every stage of the product lifecycle. From ingestion to production, they use tools that enable rapid iteration, close collaboration, and robust observability.
Below, you’ll see some of the most-used tools & technologies across the AI & Data lifecycle stages a AI Software Engineer typically works on. If your stack runs on something else, let us know, our team adapts to any platform.
Lifecycle Stages
Ingest & Organize
Acquire, clean, and structure data with governed pipelines, scalable storage, and platform enablement so information is reliable, secure, and discoverable.
Explore & Understand
Model & Experiment
Design experiments and causal analyses; develop, validate, and tune models and features; add real-time inference where instant decisions matter.
Deploy & Operate
Ship models to production with CI/CD and serving, monitor performance and drift, automate retraining, and feed insights back into the next iteration.
Acquire, clean, and structure data with governed pipelines, scalable storage, and platform enablement so information is reliable, secure, and discoverable.
Turn raw tables into business context through storytelling, dashboards, KPI definitions, and analytics that surface opportunities and risks.
Design experiments and causal analyses; develop, validate, and tune models and features; add real-time inference where instant decisions matter.
Ship models to production with CI/CD and serving, monitor performance and drift, automate retraining, and feed insights back into the next iteration.
Meet Some of Our AI Software Engineers
8 years Mercado Libre Auth0
Juan
RAG systems, serverless inference, React chat UIs
Past Companies
7 years Nubank Gympass
Maria
Vector search, real-time personalization, TypeScript-centric micro-frontends
Past Companies
9 years Rappi Bancolombia
Diego
Financial forecasting agents, LangChain evaluators, CI/CD automation
Past Companies
6 years Globant PedidosYa
Luisa
Multimodal chatbots, speech-to-text integration, mobile AI SDKs
Past Companies
10 years LATAM Airlines Banco de Chile
Carlos
Governance, security, SOC 2 compliance for AI workloads
Past Companies
5 years Itaú Despegar
Fernanda
Ecommerce recommendation engines
Past Companies
U.S. Hiring vs Abstra Nearshore Savings
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Why Abstra Is Your Ideal Partner
Fast and Flexible
Fast and Flexible
Our adaptability and agile processes enable us to swiftly meet your project needs, delivering tech solutions aligned with your timelines and goals.
Partnership-Oriented
Partnership-Oriented
Through open communication and mutual trust, we create collaborative relationships that drive sustained success and growth.
US-Trained Leadership
US-Trained Leadership
Our US-trained founders bring a wealth of technical knowledge and a deep understanding of the US and LATAM markets.
15 Years of Experience
15 Years of Experience
Our expertise spans a variety of industries. We tailor our solutions to meet the needs of each company, regardless of its size or sectorWhat Are the Different Ways to Hire Our Team?
Staff Augmentation
Our professionals seamlessly integrate into your team, boosting your capabilities and driving your projects forward.
Dedicated Teams
We provide complete software teams that become integral to your organization, working collaboratively to achieve your business goals.
Software Outsourcing
Our experienced project managers and software teams handle your projects from start to finish, delivering tailored solutions that meet your requirements.
Managed IT Services
We offer comprehensive management of your IT services, ensuring smooth operations and optimal performance of your tech stack.
Ready to take the next step?
Frequently Asked Questions
Can Abstra supply a full team or just one role?
Both. We can provide a single specialist to fill a specific gap or build out an entire cross-functional team tailored to your project.