Histórico de Puestos
About the Role
We are looking for a Data & AI Solutions Engineer to design and deliver intelligent solutions driven by data and machine learning.
This role is focused on solving business problems through well-designed data pipelines, applied machine learning, and reliable engineering practices. You will work end to end, from raw data to AI-powered features used in production.
If you enjoy working close to data, care about correctness and impact, and like turning messy problems into clean solutions, this role is for you.
Responsibilities
- Design and implement data pipelines that feed AI and machine learning systems.
- Develop and integrate machine learning models into production applications.
- Work closely with stakeholders to understand requirements and translate them into technical solutions.
- Ensure data quality, consistency, and reliability across systems.
- Optimize AI and data workflows for performance and scalability.
- Monitor system behavior and continuously improve solutions.
- Document designs, decisions, and best practices.
Technical Stack
You will work with a pragmatic, production-oriented stack:
Data and Processing
- Python for data processing and AI integration
- SQL for data querying and analysis
- ETL / ELT pipelines and batch processing
AI and Machine Learning
- Applied machine learning and model integration
- Exposure to LLMs or predictive systems
- Feature engineering and model evaluation
Infrastructure and Systems
- Backend services and APIs
- Containerized deployments
- Cloud platforms (AWS, GCP, or similar)
- Logging and monitoring tools
Requirements
- Strong experience working with data-driven systems.
- Solid software engineering fundamentals.
- Experience delivering AI or ML solutions in production.
- Ability to reason about data quality and system behavior.
- Strong problem-solving and communication skills.
- Ownership mentality and attention to detail.
Nice to Have
- Experience with analytics or BI tools.
- Familiarity with MLOps or data observability.
- Exposure to vector databases or semantic search.
- Experience working in product-led teams.
What We Offer
- Work on meaningful data and AI problems with real impact.
- End-to-end ownership of solutions.
- A collaborative and engineering-focused culture.
- Competitive compensation and growth opportunities.
- Flexible, remote-friendly working environment.
- Continuous learning and professional development.
Apply
If you are passionate about building data-driven AI solutions that actually deliver value, we would love to hear from you.
Apply and help us turn data into intelligent products.
Características del Puesto
About the Role We are looking for a Data & AI Solutions Engineer to design and deliver intelligent solutions driven by data and machine learning. This role is focused on solving business problems ...View more
About the Role
We are looking for an AI Platform Engineer to design, build, and evolve the foundational platform that enables AI-powered products at scale.
In this role, you will focus on creating shared infrastructure, tooling, and services that make it easy and safe for teams to build, deploy, and operate AI systems in production. Your work will directly impact developer productivity, system reliability, and the long-term scalability of AI initiatives.
This is a highly technical role for engineers who enjoy platform thinking, strong abstractions, and enabling others.
Responsibilities
- Design and build platform-level services for AI and machine learning workloads.
- Create standardized pipelines for model deployment, inference, and monitoring.
- Develop internal tools and APIs that enable teams to ship AI features faster.
- Ensure reliability, scalability, and security of AI infrastructure.
- Define best practices and architectural patterns for AI systems.
- Collaborate with product, ML, and engineering teams across the organization.
- Continuously improve platform performance, cost efficiency, and usability.
Technical Stack
You will work with a modern platform-oriented stack:
AI and Machine Learning
- Integration of ML models and LLM-based systems
- Support for training, inference, and experimentation workflows
- Understanding of model lifecycle management
Platform and Infrastructure
- Python and backend services
- Docker and container orchestration
- Cloud infrastructure (AWS, GCP, or similar)
- CI/CD pipelines and infrastructure automation
Data and Observability
- SQL and NoSQL data stores
- Logging, metrics, and monitoring systems
- Model performance and drift monitoring
Requirements
- Strong experience in backend or platform engineering.
- Hands-on exposure to AI or machine learning systems.
- Solid understanding of distributed systems and scalability.
- Experience designing reusable infrastructure and tooling.
- Ownership mindset and attention to system quality.
- Clear communication and collaboration skills.
Nice to Have
- Experience with MLOps or AI platform tooling.
- Familiarity with vector databases and LLM workflows.
- Background in developer platforms or internal tooling.
- Experience in fast-growing or product-driven environments.
What We Offer
- Ownership of a critical AI platform used across products.
- High technical influence and long-term impact.
- A collaborative, engineering-driven culture.
- Competitive compensation and career growth.
- Flexible working hours and remote-friendly setup.
- Continuous learning in a rapidly evolving field.
Apply
If you enjoy building platforms that empower teams to ship AI at scale, we would love to hear from you.
Apply and help us build the foundation for the next generation of AI products.
Características del Puesto
About the Role We are looking for an AI Platform Engineer to design, build, and evolve the foundational platform that enables AI-powered products at scale. In this role, you will focus on creating sha...View more
About the Role
We are looking for an Applied AI Systems Engineer to design and build intelligent systems where machine learning and software engineering come together.
This role focuses on creating end-to-end AI systems, not just models. You will work on data ingestion, model integration, orchestration, and production deployment, ensuring that AI solutions are reliable, scalable, and aligned with real product needs.
If you enjoy thinking in systems, care about clean architecture, and want to apply AI in practical, high-impact ways, this role is for you.
Responsibilities
- Design and implement end-to-end AI systems used in production.
- Integrate machine learning and LLM-based components into existing platforms.
- Build orchestration layers for AI workflows and pipelines.
- Develop APIs and services that expose AI capabilities.
- Ensure system reliability, scalability, and observability.
- Collaborate with product and engineering teams to translate requirements into AI solutions.
- Continuously improve system architecture and performance.
Technical Stack
You will work with technologies such as:
AI and Machine Learning
- Python as the primary development language
- Integration of LLMs and generative AI systems
- Prompt engineering and structured outputs
- Embeddings and semantic search
Systems and Backend
- Service-oriented and microservice architectures
- RESTful APIs
- Async processing and job orchestration
Infrastructure and Data
- Containerized deployments with Docker
- Cloud platforms (AWS, GCP, or similar)
- SQL and NoSQL databases
- Monitoring, logging, and system observability
Requirements
- Strong software engineering background.
- Hands-on experience building AI-enabled systems.
- Understanding of machine learning concepts and trade-offs.
- Experience deploying and maintaining production systems.
- Ability to work in ambiguous problem spaces.
- Strong ownership and communication skills.
Nice to Have
- Experience with RAG architectures or AI agents.
- Familiarity with vector databases and search systems.
- Exposure to MLOps or AI system monitoring.
- Experience working in product-led or startup environments.
What We Offer
- Work on real-world AI systems with measurable impact.
- High autonomy and technical ownership.
- A strong engineering culture focused on quality and clarity.
- Competitive compensation and growth opportunities.
- Flexible, remote-friendly working environment.
- Continuous learning in a fast-evolving field.
Apply
If you are excited about building AI systems that actually run in production, we would love to hear from you.
Apply and help us build intelligent systems that scale.
Características del Puesto
About the Role We are looking for an Applied AI Systems Engineer to design and build intelligent systems where machine learning and software engineering come together. This role focuses on creating en...View more
About the Role
We are looking for an AI Backend Engineer to build the core systems that power intelligent, data-driven products.
In this role, you will focus on designing and scaling backend architectures that integrate machine learning and AI capabilities as first-class components. Your work will ensure that AI features are reliable, secure, and performant in real production environments.
This position is ideal for engineers who enjoy backend development but want to work deeply with AI-driven systems rather than pure data science.
What You Will Do
- Design and develop backend services that integrate AI and machine learning models.
- Build APIs that expose AI capabilities to web and mobile clients.
- Implement data pipelines for training, inference, and evaluation.
- Ensure scalability, reliability, and security of AI-enabled systems.
- Optimize latency and cost for AI workloads.
- Collaborate with ML engineers, product teams, and frontend developers.
- Participate in architecture decisions and system design.
Technical Environment
You will work with a modern, production-focused stack:
Backend and APIs
- Python or similar backend-focused languages
- RESTful APIs and service-oriented architectures
- Asynchronous processing and background jobs
AI and Machine Learning
- Integration of ML models and inference services
- Experience working with LLMs or predictive models
- Understanding of model lifecycle and deployment
Infrastructure and Data
- Docker and container-based deployments
- Cloud platforms (AWS, GCP, or equivalent)
- SQL and NoSQL databases
- Monitoring, logging, and observability tools
What We’re Looking For
- Strong backend engineering experience.
- Hands-on exposure to AI or machine learning systems in production.
- Solid understanding of system design and scalability.
- Ability to translate product requirements into technical solutions.
- Ownership mindset and attention to detail.
- Strong communication and collaboration skills.
Nice to Have
- Experience with microservices and event-driven architectures.
- Familiarity with MLOps or AI monitoring practices.
- Experience building AI-powered APIs for end-user products.
- Startup or fast-paced product environment experience.
What We Offer
- Ownership of core backend and AI systems.
- Work on products where AI is a fundamental capability.
- A technically strong and collaborative team.
- Competitive compensation and growth opportunities.
- Flexible working hours and remote-friendly culture.
- A product-driven environment with real impact.
Apply
If you want to build backend systems where AI is part of the foundation, not an afterthought, we’d love to hear from you.
Apply and help us scale intelligent platforms.
Características del Puesto
About the Role We are looking for an AI Backend Engineer to build the core systems that power intelligent, data-driven products. In this role, you will focus on designing and scaling backend architect...View more
About the Role
We are looking for a Machine Learning Engineer to build, deploy, and maintain production-grade AI systems that power real products and workflows.
This role focuses on reliability, scalability, and performance. You will work on models that run in real environments, handle real data, and must meet high standards for quality, cost, and latency.
If you care about clean engineering, measurable impact, and turning machine learning into dependable software, this role is for you.
Responsibilities
- Develop and deploy machine learning models into production environments.
- Design scalable inference pipelines and data flows.
- Collaborate with software engineers to integrate ML systems into larger platforms.
- Monitor model performance, drift, and data quality over time.
- Optimize models and systems for speed, cost, and reliability.
- Contribute to ML engineering standards, tooling, and best practices.
- Participate in technical decisions and architecture discussions.
Technical Stack
You will work with technologies such as:
Machine Learning and AI
- Python as the primary language
- Scikit-learn, TensorFlow, or PyTorch
- Feature engineering and model evaluation
- Experiment tracking and reproducibility
Backend and Infrastructure
- REST APIs and microservices
- Docker and container-based deployments
- Cloud infrastructure (AWS, GCP, or similar)
- CI/CD pipelines
Data and Monitoring
- SQL and NoSQL databases
- Data pipelines and batch/stream processing
- Model monitoring and logging
- Basic MLOps tooling and workflows
Requirements
- Strong experience in machine learning engineering or applied data science.
- Solid software engineering fundamentals.
- Experience deploying ML models to production.
- Understanding of system design and scalability.
- Ability to work independently and take ownership.
- Clear communication and collaboration skills.
Nice to Have
- Experience with MLOps platforms or tooling.
- Familiarity with streaming systems or real-time inference.
- Exposure to LLMs or generative AI systems.
- Background in startups or high-growth environments.
What We Offer
- Work on real AI systems used by real users.
- High technical ownership and influence.
- A collaborative, engineering-driven culture.
- Competitive compensation based on experience.
- Flexible working hours and remote-friendly setup.
- Continuous learning and professional growth.
Apply
If you are interested in building robust, production-ready AI systems and want your work to make a tangible impact, we would love to hear from you.
Apply and join us in building AI that actually works.
Características del Puesto
About the Role We are looking for a Machine Learning Engineer to build, deploy, and maintain production-grade AI systems that power real products and workflows. This role focuses on reliability, scala...View more
About the Role
We are looking for a Senior AI Product Engineer to help us build intelligent, AI-first products where machine learning and generative AI are core features, not add-ons.
This role sits at the intersection of AI, product, and engineering. You will work closely with product managers and engineers to design AI-driven user experiences, experiment fast, and turn validated ideas into scalable production systems.
If you enjoy shipping real AI features, iterating with users, and shaping product decisions with technology, this role is for you.
What You Will Be Working On
- Designing and implementing LLM-powered features used directly by end users.
- Building RAG pipelines (retrieval-augmented generation) using vector databases and custom data sources.
- Creating AI workflows, agents, and tools that automate complex tasks.
- Experimenting rapidly with prompts, models, and architectures, then productionizing what works.
- Integrating AI services into web or mobile products with strong UX considerations.
- Measuring and improving quality, latency, and cost of AI systems.
- Helping define best practices for AI-powered product development.
Tech & Tools
You will work with a modern, pragmatic stack including:
Generative AI & LLMs
- OpenAI / Anthropic / open-source LLMs
- Prompt engineering and structured outputs
- RAG architectures and embeddings
- LangChain or similar orchestration frameworks
Engineering
- Python (primary language)
- RESTful APIs and microservices
- Docker and cloud deployments
- Async processing and background jobs
Data & Infrastructure
- Vector databases (Pinecone, Weaviate, FAISS)
- SQL / NoSQL databases
- Cloud platforms (AWS, GCP, or equivalent)
- Monitoring, logging, and basic MLOps practices
What We’re Looking For
- Proven experience building AI-powered products in production.
- Strong software engineering background with a product mindset.
- Hands-on experience with LLMs and generative AI systems.
- Ability to balance experimentation with engineering discipline.
- Comfort working in ambiguous, fast-moving environments.
- Strong communication skills and ownership mentality.
Nice to Have
- Experience designing AI-first UX or conversational interfaces.
- Background in startups or product-led companies.
- Familiarity with mobile or frontend integration.
- Knowledge of cost optimization strategies for LLM-based systems.
What We Offer
- The opportunity to build AI-native products from scratch.
- High ownership and real influence on product direction.
- A small, talented, and highly motivated team.
- Flexible working hours and remote-friendly setup.
- Competitive compensation aligned with impact and experience.
- A culture focused on learning, experimentation, and shipping.
Ready to Build the Future?
If you are excited about creating products where AI is the product, not just a feature, we’d love to meet you.
Apply and help us define what great AI-powered products look like.
Características del Puesto
About the Role We are looking for a Senior AI Product Engineer to help us build intelligent, AI-first products where machine learning and generative AI are core features, not add-ons. This role sits a...View more
About the Role
We are looking for a passionate and highly skilled AI Engineer to join our team and help us design, build, and scale intelligent systems that solve real-world problems.
This role is not about experiments that never reach production. You will work on applied AI, transforming ideas into robust, scalable solutions used by real users. You will have ownership, autonomy, and the opportunity to shape how AI is embedded into products from day one.
If you enjoy working at the intersection of machine learning, software engineering, and product, this role is for you.
What You Will Do
- Design, develop, and deploy AI-powered features end to end, from concept to production.
- Build and optimize machine learning models for tasks such as NLP, computer vision, recommendation systems, or predictive analytics.
- Work with LLMs and generative AI (prompt engineering, fine-tuning, RAG pipelines, agents).
- Integrate AI models into production systems using APIs and microservices.
- Collaborate closely with product, backend, and frontend teams to turn business needs into intelligent solutions.
- Continuously improve model performance, scalability, and reliability.
- Stay up to date with the latest advances in AI and proactively propose new ideas and improvements.
Tech Stack (What We Use & What You’ll Touch)
Depending on the project, you’ll work with technologies such as:
AI & Machine Learning
- Python (NumPy, Pandas, Scikit-learn)
- Deep Learning: TensorFlow / PyTorch
- NLP & LLMs: OpenAI APIs, Hugging Face, LangChain
- Vector databases: Pinecone, FAISS, Weaviate
- Model evaluation, fine-tuning, and experimentation
Backend & Infrastructure
- REST & GraphQL APIs
- Docker & containerized deployments
- Cloud platforms (AWS, GCP, or similar)
- CI/CD pipelines
- Basic MLOps practices (monitoring, versioning, model lifecycle)
Data
- SQL / NoSQL databases
- Data pipelines and preprocessing
- Feature engineering
What We’re Looking For
- Strong experience in AI / Machine Learning engineering or applied data science.
- Solid programming skills (Python required).
- Experience taking ML models from prototype to production.
- Understanding of trade-offs between accuracy, performance, cost, and scalability.
- Ability to work independently and take ownership of solutions.
- Clear communication skills and a product-oriented mindset.
Nice to Have
- Experience with Generative AI, LLM agents, or RAG architectures.
- Previous startup or fast-paced environment experience.
- Frontend or mobile integration experience.
- Contributions to open-source or AI research projects.
What We Offer
- High-impact work on meaningful, real-world AI products.
- Freedom to propose ideas and shape technical decisions.
- A collaborative, no-bureaucracy environment.
- Competitive compensation based on experience.
- Remote-friendly culture and flexible working hours.
- Continuous learning and growth in one of the fastest-moving fields in tech.
Join Us
If you are excited about building practical AI, not just demos, and want to work on products where your work truly matters, we’d love to hear from you.
Apply and help us shape the future with AI.
Características del Puesto
About the Role We are looking for a passionate and highly skilled AI Engineer to join our team and help us design, build, and scale intelligent systems that solve real-world problems. This role is not...View more