The Client Project
SWARM Engineering with AI engineers is an industry that provides intelligent decision-support tools to help organizations automate complex workflows and improve operational efficiency.
They needed an AI Staff Augmentation service to strengthen their engineering capabilities by accelerating development, enhancing software quality, and advancing their AI initiatives.
Requirements
ClickIT has been a key partner in AI staff augmentation for SWARM Engineering, focused on leveraging AI to improve performance, automate processes, and support data-driven decision-making.
AI software developers
QA testers
Data Scientists
Implemented Services
ClickIT’s AI engineering team strengthened the client’s AI ecosystem by optimizing pipelines, modernizing cloud infrastructure, enhancing testing strategies, and improving model performance, all delivered under Agile/Scrum, CI/CD, peer reviews, and cloud-native architectures.
Optimized data and ML pipelines to reduce latency, increase reliability, and improve algorithm robustness, including manual-to-automated transitions in early-stage ML workflows (PyTorch, Scikit-learn).
Implemented automated QA and data-validation flows with Selenium, Python, SQL, enhanced Cypress + TypeScript automation, and JMeter performance testing for AI chat workloads under high concurrency.
Strengthened data engineering foundations by improving ETL robustness, refining cloud data processes, and supporting multi-project coverage during client staff absences to maintain operational continuity.
Enhanced cloud infrastructure using Docker, Kubernetes, and multi-cloud setups (AWS, Azure, GCP), alongside early migrations of Tableau dashboards into scalable React + TypeScript web apps deployed via serverless workflows in Vercel.
Developed and extended backend and agent capabilities for AVA the enterprise AI assistant, building new features in Python, Go, LangGraph, and Azure/OpenAI while improving prompt reliability, factual accuracy, and debugging cross-provider model inconsistencies.
Improved model performance using TensorFlow, PyTorch, XGBoost, and MLflow for tracking, reproducibility, and better cost/distribution outcomes in production environments.
Reinforced CI/CD automation for microservices, ML pipelines, frontend dashboards, and data workflows using GitHub pipelines and serverless deployment strategies.
Our Tech Stack
TensorFlow
PyTorch
LangGraph
LangChain
Python
Open AI
SQL
Azure DevOps
Databricks
Kubernetes
Docker
Azure
AWS
GCP
Azure AKS
GitLab
GitHub
Airflow
Azure Data
Factory
PySpark
mlFlow
GraphQL
Go
Couchbase
Selenium
XGBoost
The Results
Overlap with U.S. working hours ensures real-time communication, faster decisions, and rapid iteration. Engineers proactively participate in standups, planning sessions, and async discussions to keep teams aligned. We deliver:
- Strong Communication & Ownership
- High Adaptability to U.S. Engineering Standards
- Proactiveness in Problem-Solving
- Cultural Alignment With U.S. Work Ethic
ClickIT engineers had a high sense of ownership, taking responsibility for deliverables, unblocking themselves quickly, and escalating issues early.
LATAM engineers tend to raise opportunities for improvement before being asked.