APPLIED AI & PRODUCTS DEPARTMENT
Engineered at the Cutting Edge of Applied AI
Step into a division where AI isn’t just a buzzword, it’s a core engineering discipline. In our AI Products & Engineering Department, developers, data engineers, and AI specialists build real-world, enterprise-grade AI applications, autonomous agents, and intelligent automations for global markets.
What You’ll Build & Engineer
Enterprise AI Chatbots & RAG Copilots
Work on advanced Conversational AI and Retrieval-Augmented Generation (RAG) architectures that allow businesses to query millions of internal documents with sub-second latency and zero hallucinations.
AI Voice Agents & Conversational AI
Build, train, and deploy real-time voice assistants capable of executing natural inbound/outbound phone support, appointment scheduling, and automated qualification workflows.
Complex Workflow Automation
Design autonomous backend pipelines using visual orchestration platforms and custom Python scripts to eliminate manual operations across global business systems.
Multi-System CRM & Database Integrations
Connect AI models directly into enterprise tech stacks (Salesforce, HubSpot, Gorgias, custom SQL/NoSQL databases) for real-time data sync and intelligent ticket routing.
WhatsApp & Omnichannel AI Messaging
Develop high-throughput automated conversational flows over WhatsApp API and social platforms, serving thousands of simultaneous customer interactions natively.
Custom AI Products & Proprietary SaaS
Participate in the full-lifecycle development of our internal proprietary AI software products, from initial architecture and prompt tuning to scalable deployment.
Enterprise Toolstack & Tech You Will Master
We give our engineering teams direct access to top-tier developer tools, cloud infrastructure, vector databases, and automation frameworks:
Our Technology Stack
Foundation Models & APIs: OpenAI (GPT-4o), Anthropic (Claude), Hugging Face, DeepSeek
Frameworks & Orchestration: LangChain, LlamaIndex, n8n, Make, Zapier
Vector DBs & Search: Pinecone, Weaviate, Qdrant, Milvus
Conversational AI & Voice: Dialogflow, Retell AI, ElevenLabs, Vapi
Core Stack & Languages: Python, Node.js, React, TypeScript, FastAPI
Cloud & Infrastructure: Google Cloud AI, AWS, Docker, REST/GraphQL APIs
Our Engineering & Development Lifecycle
Discovery & Planning
Mapping business logic, system inputs, and defining model selection based on cost, latency, and accuracy.
Data Collection
Cleaning, tokenizing, and chunking unstructured datasets for vector embeddings and contextual retrieval.
AI Model Development
Building RAG pipelines, system prompts, fine-tuning open-source models, and setting up guardrails.
Integration & Testing
Connecting models into existing frontends, CRMs, or messaging endpoints using secure, asynchronous microservices.
Deployment
Deploying containerized AI workloads on cloud environments with full fail-safe mechanisms and zero downtime.
Monitoring & Optimization
Tracking model drift, response latency, token consumption, and accuracy metrics in real production environments.