Jobs at aKube Inc

Design, build, deploy, and maintain AI agents and workflow automations for enterprise business processes. Integrate Workday, Slack, email, HR, finance, legal, and IT systems through REST APIs, webhooks, JSON, OAuth, and event-driven architectures. Translate business requirements into scalable technical workflows, rapidly prototype solutions, optimize manual processes, and support production integrations. Collaborate with business and technical stakeholders while applying MCP concepts, orchestration platforms, and cloud-native architectures.

Leads the design and development of scalable batch and streaming data platforms for experimentation, A/B testing, analytics, personalization, and machine learning. Builds dimensional models, reusable datasets, data quality and governance systems, CI/CD pipelines, monitoring, and observability. Partners with product, engineering, data science, and analytics teams; optimizes cloud data infrastructure; mentors engineers; and establishes technical best practices.

Build and deploy production NLP classification models for customer messages and call transcripts. Develop intent, topic, sentiment, and multi-label taxonomies; clean and prepare sensitive text data; create scalable Python and PySpark pipelines; design labeled datasets and annotation workflows; detect trends and anomalies; and monitor precision, recall, confidence, confusion patterns, false alerts, and model drift.

Build production AI agent platforms, API gateways, middleware, secure tool and content access patterns, and event-driven microservices. Develop agentic workflows for mastering, localization, and delivery while implementing tracing, audit logging, governance, approvals, and fallback paths. Lead design reviews, mentor engineers, and coordinate technical delivery across engineering, ML, and product teams. Convert AI prototypes into reliable, observable, and scalable cloud services using containers, infrastructure as code, and CI/CD.

Designs and builds scalable batch and real-time data pipelines, ingestion workflows, analytical processes, data products, and intelligent APIs. Ensures data quality, reliability, and performance while supporting Azure-based architecture for BI and AI/ML use cases. Collaborates with cross-functional teams, participates in code reviews, and follows DevOps, Agile, and CI/CD practices.

Build and enhance a knowledge graph-based application using React, Go, and GraphQL. Develop scalable APIs, distributed-system integrations, and production-ready features from prototype through deployment. Collaborate with product, architecture, platform, data, and engineering teams; conduct code reviews, testing, documentation, troubleshooting, and reliability improvements. Use AI-assisted development tools responsibly to improve productivity while maintaining code quality.

Migrate Azure Data Factory pipelines to native Snowflake solutions using Snowpark, Python, Tasks, Streams, and SQL. Build and optimize scalable Bronze, Silver, and Gold data layers, transform data from multiple systems, and support enterprise data warehouse reporting and analytics. The role includes Snowflake warehouse performance and cost optimization, scheduled job development, secure implementation, REST API integration, and Agile/Scrum delivery.