Jobs at Agentic Dream

Leads and mentors AI engineering teams, designs and implements scalable AI/ML solutions using Azure, guides adoption of Copilot and AI Agents, and translates business needs into AI-driven solutions while ensuring technical excellence, performance, and best practices.

Analyzes and triages customer and internal support requests, distinguishing bugs, configuration issues, training gaps, and feature needs. Coordinates among Support, Product, Engineering, Sales, and Account Management; translates technical and customer requirements; documents user stories and tickets; manages escalations, SLAs, expectations, and incident communications. The role requires diplomatic conflict resolution, cross-functional influence, analytical problem-solving, and familiarity with ticketing and project management tools.

Lead program-level standardization and governance of backend systems for the Apex platform. Establish backend, API, repository, and development standards; create reusable patterns and frameworks; oversee endpoints and services; conduct code reviews and architecture assessments; and collaborate with DevOps and technical teams. The role focuses on scalable multi-tenant and multi-client architectures, enterprise authentication integration, and consistent execution across development teams.

Owns end-to-end product strategy for a complex, scalable platform, including vision, roadmap prioritization, requirements, delivery oversight, modernization, and cross-functional alignment. Manages platform capabilities involving data architecture, APIs, integrations, analytics, and core services. Defines KPIs and OKRs, supports data-driven decisions, manages risk, budgets, and schedules, and partners with technical and business stakeholders across multiple product areas.

Owns the translation of ambiguous business processes into precise, testable specifications for data pipelines and AI agents. Responsibilities include EARS requirements, Gherkin scenarios, data dictionaries, schemas, source-to-target mappings, business rules, guardrails, workflow models, UAT, SQL-based data profiling, stakeholder workshops, and requirements traceability. The role partners with product, data engineering, and AI engineering teams to define acceptance criteria, validate implementations, and document operational metrics.

Build and maintain enterprise-scale ETL/ELT pipelines integrating global ERP data into data lakes and warehouses. Develop data connectors, implement bronze/silver/gold architectures, standardize and cleanse master data, and support BI and AI/ML use cases. Collaborate on data architecture, modeling, governance, documentation, and staging environments while enabling scalable global data transformation initiatives.

Lead the audit, redesign, and migration of HIPAA-compliant infrastructure to a self-hosted, multi-tenant SaaS environment. Build automated CI/CD for Laravel and Angular applications, enable white-label deployments, maintain tenant data isolation, and implement security hardening, centralized logging, encrypted backups, monitoring, and scalable cloud architecture with minimal downtime.

Lead integration and automation projects across their full lifecycle, translating business needs into functional requirements and technical documentation. Manage UiPath automations, GlobalCapture workflows, intelligent document capture, data mapping, architecture diagrams, and SQL-based data validation. Act as the bridge between business stakeholders and development teams while ensuring alignment, process accuracy, and successful technical execution.

Designs, operates, and optimizes scalable cloud infrastructure across AWS, Azure, or GCP. Responsibilities include Infrastructure as Code, automation, CI/CD, monitoring, cloud networking, cost optimization, security, incident recovery, container orchestration, and DevSecOps collaboration. The role requires scripting, troubleshooting, reliability improvements, and cloud performance optimization.

Develop and deploy machine learning models for predictive analytics, recommendation systems, NLP, and computer vision. Perform statistical analysis, experimentation, feature engineering, and model optimization. Collaborate with data and AI engineers to build scalable solutions, use cloud AI services, and implement MLOps practices for deployment and monitoring. Preferred work includes generative AI, RAG, graph analytics, anomaly detection, optimization, and knowledge graphs.

Senior QA Automation Engineer responsible for auditing and rebuilding unstable test automation, expanding functional and regression coverage, and integrating reliable tests into CI/CD pipelines. The role includes manual, exploratory, performance, API, and end-to-end testing; test strategy and documentation; environment stabilization; root-cause analysis; and release quality ownership. The engineer collaborates with Development, DevOps, Product, and leadership teams to reduce defect leakage and provide clear release decisions.

Build and maintain backend APIs and services for a cloud-native Transportation Management System using .NET, C#, and Python. Develop features across database, backend, and frontend layers; optimize SQL queries and stored procedures; contribute to React components, CI/CD deployments, serverless AWS services, and microservices modernization. Collaborate with multiple teams on API and schema design, troubleshoot database performance, and support agile delivery.