How AI Staff Augmentation Drove Breakthroughs in FinTech
AI Staff Augmentation
Supercharge Your AI Projects
with our Engineers & Consultants.
Ready to onboard in 48 Hours!
Our AI engineers, solution architects, and developers integrate seamlessly with your in-house team, boosting delivery speed without the hiring delays. Serving companies across the US and Europe, we provide access to Kaggle-ranked talent from Poland — recognized globally for AI excellence. From data strategy to AI DevOps, our experts hit the ground running. Scale your projects in record time and keep your competitive edge.
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AI & Data Science Professionals,
Ready in 48 Hours
Ready in 48 Hours
Experienced AI and Data Science experts,
seamlessly integrated to speed up your delivery and innovation.
Building a Data Science or Gen AI team with the right mix of roles can be challenging and time-consuming. To accelerate the process, we provide instant access to a diverse pool of proven AI talent — from engineers and solution architects to software developers and DevOps experts — with expertise across the latest AI technologies. Hire the right specialists in record time and scale your projects without the delays of traditional recruitment.
01
AI / LLM ENGINEERS
Role:
Builds and deploys AI systems with a focus on Large Language Models and Generative AI, applying Machine Learning and NLP to solve real-world challenges. Collaborates with teams to align solutions with business goals while ensuring scalability, efficiency, and continuous improvement.
Technology expertise:
Programming: Proficiency in Python with strong use of ML/DL frameworks (TensorFlow, PyTorch) and LLM-specific libraries (Hugging Face Transformers, LangChain, LlamaIndex).
LLM Application Development: Experience with building and deploying LLM-powered apps using Streamlit, Gradio, or FastAPI.
Data & Scaling: Skilled in Databricks and distributed computing frameworks like Spark for handling large-scale data used in model training and fine-tuning.
Azure AI Stack: Hands-on knowledge of Azure Machine Learning, Cognitive Services, Data Factory, and Azure OpenAI Service for enterprise-grade LLM solutions.
AWS AI Stack: Proficiency with AWS SageMaker, Bedrock, EC2, S3, and Lambda for deploying and managing AI/LLM workloads.
Ecosystem Tools: Familiarity with MLOps platforms (MLflow, Weights & Biases), vector databases (Pinecone, Weaviate, FAISS), and containerization/orchestration (Docker, Kubernetes) for LLM lifecycle management.
02
AI SOLUTION ARCHITECTS
Role:
Designs and oversees the architecture of end-to-end AI/LLM systems, translating business needs into scalable, secure technical solutions. Works across data pipelines, model deployment, infrastructure, and integration to ensure robust performance and maintainability. Guides implementation from proof-of-concept through production, aligning with organizational goals.
Technology expertise:
Architecture Design: Expertise in designing scalable, secure, and maintainable AI/LLM system architectures (cloud, hybrid, on-prem).
Cloud Platforms: Deep knowledge of Azure (ML, Cognitive Services, OpenAI), AWS (SageMaker, Bedrock, Lambda), and GCP (Vertex AI, BigQuery).
Data & Integration: Experience with enterprise data platforms (Databricks, Snowflake, Spark) and API/microservice integrations.
Deployment & Orchestration: Proficiency in MLOps tools (MLflow, Kubeflow), containerization (Docker, Kubernetes), and CI/CD pipelines.
AI/LLM Ecosystem: Familiarity with LLM frameworks (Hugging Face, LangChain, LlamaIndex) and vector databases (Pinecone, Weaviate, FAISS).
Security & Governance: Knowledge of data privacy, compliance, model monitoring, and responsible AI practices.
03
AI STRATEGY CONSULTANTS
Role:
Partners with senior leadership to define AI vision and roadmap, identifying high-impact opportunities and assessing feasibility, ROI, and risks. Advises clients on how to embed AI/LLM technologies into their business models, operations, and processes for measurable outcomes. Leads strategic planning, workshops, and governance around AI adoption, ethical use, and capability building.
Technology expertise:
AI/ML Landscape: Strong understanding of AI/LLM technologies (generative AI, NLP, computer vision, predictive analytics) and their business applications.
Cloud Ecosystems: Working knowledge of major AI cloud offerings (Azure AI, AWS AI/ML, GCP Vertex AI) to guide vendor selection and strategy.
Data & Analytics Platforms: Familiarity with data warehouses/lakes (Snowflake, Databricks, BigQuery) and BI tools (Power BI, Tableau).
Emerging LLM Tools: Awareness of generative AI toolkits (OpenAI APIs, Anthropic, Hugging Face, LangChain) and their enterprise use cases.
Governance & Ethics: Expertise in responsible AI, bias detection, explainability frameworks, and regulatory compliance (GDPR, AI Act).
Strategic Enablement: Experience with AI adoption frameworks, ROI analysis, and capability building to align technology with business transformation.
04
AI SOFTWARE DEVELOPERS
Role:
Develops and integrates AI/LLM capabilities into software applications, ensuring seamless interaction between models and business systems. Collaborates with data scientists and engineers to transform prototypes into production-ready, user-focused solutions. Focuses on performance, usability, and maintainability of AI-enabled applications.
Technology expertise:
Programming & Frameworks: Strong in Python and modern development languages (JavaScript/TypeScript, Java, C#) with experience in AI libraries (PyTorch, TensorFlow, Hugging Face).
LLM Integration: Skilled at embedding LLMs via APIs (OpenAI, Anthropic, Azure OpenAI) and frameworks like LangChain or LlamaIndex.
Application Development: Experience with web/app frameworks (FastAPI, Flask, Node.js, React) and rapid prototyping tools (Streamlit, Gradio).
Deployment & DevOps: Familiarity with CI/CD pipelines, containerization (Docker), orchestration (Kubernetes), and cloud services (Azure, AWS, GCP).
Software Quality: Knowledge of testing, version control (Git), secure coding practices, and performance optimization for AI-driven applications.
05
DATA SCIENTISTS
Role:
Applies expertise in machine learning, LLMs, deep learning, and statistical modeling to uncover patterns in data and build models that solve business challenges. Bridges advanced analytics with practical deployment by leveraging cloud platforms, ML frameworks, and MLOps practices to deliver scalable, AI-driven solutions.
Technology expertise:
Programming & Libraries: Proficiency in Python (pandas, scikit-learn, TensorFlow, PyTorch, LangChain, Streamlit)
Big Data & Distributed Computing: Databricks, Apache Spark, MLlib
Azure: Machine Learning, Cognitive Services, Data Factory, Azure OpenAI Service
AWS: SageMaker, EC2, S3, Lambda
Statistical & Enterprise Analytics: SAS (Base, Enterprise Guide, Miner, Viya)
Additional Competencies: Generative AI solutions, Natural Language Processing (NLP), Computer Vision, and Responsible AI practices
06
DATA ENGINEERS
Role:
Designs and maintains scalable data pipelines and platforms that make high-quality, reliable data accessible for analytics and AI/LLM workloads. Ensures data is efficiently ingested, processed, and integrated to support business insights and machine learning applications.
Technology expertise:
Programming & Query Languages: Python, SQL, Spark, Scala, Java, SAS 4GL
Data Platforms & Orchestration: Kafka, Databricks, Apache Airflow, Snowflake
Azure Data Stack: Data Factory, Synapse Analytics, Data Lake, Azure DevOps
AWS Data Stack: S3, Redshift, Glue, Athena, DynamoDB
Enterprise Data Management: SAS (Data Integration Studio, Base, Macro, Management Console)
Additional Competencies: Data modeling, data governance, real-time & batch processing, and performance optimization
07
MLOps / AIOps / DevOps
Role:
Builds, automates, and maintains scalable pipelines for deploying, monitoring, and optimizing AI/ML systems in production. Integrates continuous integration/continuous deployment (CI/CD) practices with robust infrastructure management to ensure reliability, scalability, and performance of AI workloads. Implements monitoring, alerting, and automated remediation strategies using AIOps principles to detect and resolve issues proactively. Collaborates with data scientists, software engineers, and architects to operationalize models and AI services efficiently.
Technology expertise:
Infrastructure as Code (IaC): Terraform, AWS CloudFormation, Azure Resource Manager (ARM)
Containerization & Orchestration: Docker, Kubernetes, Helm
CI/CD & Automation: Jenkins, GitLab CI/CD, GitHub Actions, ArgoCD
Monitoring & Observability: Prometheus, Grafana, ELK/EFK Stack, OpenTelemetry, DataDog
Cloud & Platforms: Azure ML, AWS SageMaker, GCP Vertex AI, Kubernetes-native ML platforms
AI/ML Model Operations: Model deployment, monitoring, governance, drift detection, reproducibility, lineage tracking
AIOps & Automation: Event-driven monitoring, anomaly detection, automated remediation, workflow orchestration
Security & Compliance: Secrets management, role-based access control, secure pipelines, regulatory compliance (GDPR, HIPAA)
08
BI DEVELOPERS
Role:
Transforms business data into actionable insights by gathering requirements, validating sources, and designing reports and dashboards. Creates clear, impactful visualizations that enable data-driven decision-making across the organization.
Technology expertise:
BI & Visualization Tools: Power BI, Tableau, SSAS, SSIS, SSRS, Microsoft Fabric
Data Modeling & Scripting: DAX, M (Power Query)
Database & Querying: SQL Server, T-SQL, relational and analytical databases
Security & Access Management: Row-level security, data gateway configuration, user permissions
Data Integration & ETL: Experience with ETL pipelines, data cleansing, transformation, and integration from multiple sources
09
SAS EXPERTS
Role:
Delivers end-to-end SAS solutions across analytics, data management, BI/visualization, and system administration. Applies deep expertise in SAS platforms to design, develop, integrate, and optimize data-driven processes, ensuring robust reporting, modeling, and operational excellence.
• SAS Developers & BI/Visualization Analysts
• SAS Data Scientists & Analysts
• SAS Data Warehouse, Integration & Data Quality
• SAS CI & FM Consultants
• SAS Administration & Installation Specialists
Technology expertise:
SAS Platforms: SAS Viya, SAS 9.4
Data Management & Quality: SAS Data Management, Event Stream Processing, Information Governance, Data Quality
Analytics & AI/ML: SAS for Machine Learning, AI modeling, advanced analytics
BI & Visualization: SAS Visual Analytics, Business Intelligence, reporting, dashboards
Decisioning & Customer Solutions: SAS Intelligent Decisioning, SAS Customer Intelligence 360
Integration & Administration: Data integration, ETL pipelines, SAS environment setup, deployment, and administration
HIRE TOP TALENT IN 48 HOURS
Discover how AI & Data Science Staff Augmentation helps companies move faster.
We bring in specialized Talent who integrate seamlessly with your team from day one — ensuring stability, scalability, and lasting impact.
Contact us and explore how we can support your business!
ENGAGEMENT MODELS
Team extension - managed by you
You control the development process by managing resources,
allocation, and planning. You are responsible for the results.
Dedicated team - managed by us
We control the development proces while you keep the focus on
building your business. We are responsible for the results.
WHY BUILD AN OFFSHORE DATA SCIENCE TEAM IN POLAND?
Highly Skilled Workforce
Poland is recognized for its tech talent in Data Science. With a strong pool of STEM graduates and a significant presence on Kaggle, the country has cultivated a talented pool of well-qualified professionals.
Cost-Effective Solution
Compared to other Western European or US locations, Poland offers more competitive pricing with excellent quality. This cost efficiency can make it an appealing destination for outsourcing.
Time Zone Alignment
For companies in Europe, Poland's time zones are aligned. For the US, this alignment allows a 16-hour working window to speed up development time.
Regulatory Compliance
Being part of the European Union, Poland adheres to strict regulations and standards, providing a secure legal framework for business collaboration.
AI/ML Reputation
With a reputation as one of the world leaders in Data Science, Poland has a track record of delivering innovative and high-quality solutions and stay at the forefront of technological advancements in these fields.
Cultural Compatibility
Poland shares many business practices and cultural values with other Western countries, reducing the potential friction that can occur in cross-cultural collaboration.
Strong English Proficiency
Many Polish professionals in the tech industry are proficient in English, making communication straightforward for international collaboration.
Robust Technology Infrastructure
Poland's investment in technology and infrastructure ensures a stable and efficient environment for conducting data science activities.
SUCCESS STORIES
hire scientists
and engineers
in 5 steps
and engineers
in 5 steps
01
Contact us
Send us short info about your needs.
02
Introduction
Let’s discuss your requirements with our experts.
03
Select CV
We share the CVs of our Talents who have the skill sets required for your project.
04
Interviews
Once you shortlist the CVs of engineers or scientists you wish to work with, we schedule the interview with them.
05
Hire Resources
An engineer who meets your requirements may be hired by you and work as part of your extended team.
We solve recent Data Science challenges
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Talent shortage
Poland is sitting on a gold mine of tech talent and is one of the world leaders in Data Science and Machine Learning, ranking 4th globally in STEM graduates, dominating Kaggle leaderboards regularly.
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Diverse skill sets
Access a versitile team of engineers tailored to your project's needs. If requirements change, you can scale up or down the team size at any time.
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Costs challenges
We expertly handle taxes, medical insurance, admin costs, sports reimbursements, English courses, events, modern offices, tech, recruitment expenses, and keep our team up-to-date with the latest advancements.
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Short deadlines
Our skilled team dives into projects from day one, swiftly delivering outstanding results and outshine the competition.
Access AI Talents
in 48 hours
in 48 hours
Discover our AI/ML expertise, understand our engagement process, and learn about our competitive rates. Let's talk.
