Jobs at Aligned Automation

Processes technical support tickets, coordinates field-service dispatches and replacement parts, responds to customer emails, documents resolutions, and troubleshoots hardware across enterprise servers, storage, and client systems. The role supports global 24/7 operations through rotational shifts, escalates complex issues, follows SLAs, and develops expertise in IT infrastructure and support tools.

Lead enterprise AI and machine learning strategy, architecture, development, and production deployment. Design predictive analytics, generative AI, LLM, RAG, and agent solutions; establish MLOps, governance, monitoring, and responsible AI practices; align initiatives with business value and ROI; communicate with executives and stakeholders; prioritize and deliver AI programs; and mentor data scientists, ML engineers, and analysts.

Design, develop, and maintain Power BI dashboards, reports, and data models. Translate business requirements into scalable BI solutions using DAX and Power Query, ensuring data accuracy, performance, governance, and effective visualization. Collaborate with stakeholders and cross-functional teams, troubleshoot reporting issues, and provide actionable insights. SQL, cloud data platforms, data integration, and AI exposure are advantageous.

Early-career consulting role supporting digital transformation and AI initiatives. Responsibilities include requirements gathering, business process analysis, documentation (BRDs/FRDs/user stories), coordinating Agile delivery, supporting testing and UAT, preparing basic analytics/dashboards, and working with stakeholders while learning enterprise technologies and consulting practices.

Deliver end-to-end digital transformation and AI-enabled solutions by gathering requirements, designing functional solutions, coordinating cross-functional teams, executing SDLC activities, supporting testing and deployment, and driving business adoption. Use analytics, automation, and AI where applicable and maintain governance, documentation, and continuous improvement.

Lead end-to-end delivery of digital transformation and AI initiatives, establish project governance, manage resources and stakeholders, drive Agile execution, mentor consultants, and ensure on-time, high-quality business outcomes and adoption.

Extracts, validates, reconciles, and analyzes manufacturing data from SAP, MES, L&D, and other operational systems. Builds Power BI or Tableau dashboards, recurring KPI reports, and traceable datasets within a GxP-regulated environment. Applies ALCOA+ data integrity principles, documents lineage and validation workflows, supports audits, investigates discrepancies, collaborates with Manufacturing, Quality, and IT teams, and improves reporting automation and data governance.

Design, build, and optimize scalable ETL/ELT data pipelines using PySpark and Python. Model and tune MongoDB for large datasets, develop data ingestion and validation frameworks, integrate REST APIs, monitor and troubleshoot pipelines, and collaborate with analysts and data scientists while applying data governance and CI/CD practices.

Design, develop, and deploy enterprise GenAI and Agentic AI solutions. Build multi-agent workflows, RAG systems, vector database integrations, scalable Python APIs, and microservices. Implement LLM orchestration, prompt engineering, evaluation, monitoring, and observability. Integrate AI with enterprise applications and data platforms while meeting security, governance, SDLC, and deployment standards. Collaborate with stakeholders to convert business use cases into production-ready systems.

Design, develop, and deploy enterprise-scale GenAI and agentic AI solutions. Build multi-agent workflows and RAG systems using vector databases and enterprise knowledge sources. Develop Python APIs and microservices, implement LLM orchestration, prompt engineering, evaluation, monitoring, and observability, and integrate AI with enterprise applications and data platforms. Collaborate with stakeholders to deliver production-ready systems while following software development, security, governance, and deployment standards.

Provide end-to-end technical and functional support for enterprise HSE SaaS applications in a regulated pharma environment. Manage incidents, user requests, vendor coordination, configuration, qualification per IT & Cyber Security policy, ensure regulatory compliance, and support integrations with PowerApps and SharePoint while collaborating with cross-functional teams.

Lead QA for MES implementations: define testing strategy, lead test team, create and execute test plans (functional, regression, integration, performance, UAT), integrate automated tests into CI/CD, act as quality gate for releases, support CSV/GxP activities, manage defects, and report testing metrics to stakeholders.

Lead end-to-end AI/ML-driven transformation projects: translate business requirements, design experiments, analyze results, operationalize models with data science and engineering teams, drive agile delivery, stakeholder alignment, and mentor teams to deliver measurable business impact.

Lead procurement digital transformation programs using analytics, automation, and strategic sourcing to drive cost savings, implement procurement platforms (e.g., SAP Ariba), develop dashboards, identify AI/RPA opportunities, manage stakeholders globally, and track program benefits including sustainability initiatives.

Lead end-to-end cross-functional projects and programs, synthesize data into insights, and produce executive-quality PowerPoint presentations. Validate datasets, manage stakeholders, track action items, and maintain documentation and dashboards. Use AI prompt-engineering tools to accelerate research and improve deliverables while driving alignment and securing leadership sign-off.

Lead enterprise AI-native transformation by designing and deploying multi-agent systems, agent orchestration, and RAG-based workflows. Work with executives to translate strategy into production-grade prototypes, scalable accelerators, and human-in-the-loop governance to improve portfolio management, delivery orchestration, and operational intelligence.

Lead DevOps engineering for an MES programme: design and run CI/CD pipelines, manage toolchain and environments (Syncade), implement IaC and monitoring, support CSV/GxP validation, improve deployment metrics, and act as escalation authority for infrastructure and disaster recovery.

Lead programme governance, delivery excellence, and AI-augmented PMO operations across enterprise clients. Coordinate between technical teams and executives, manage planning, reporting, documentation, incident/problem analysis, risk and change management, and continuous improvement while maintaining high quality and stakeholder communication.

Lead end-to-end ML and AI initiatives: problem framing, modeling, deployment, monitoring, and MLOps. Architect and deliver GenAI and agentic systems, mentor data science teams, align solutions with business outcomes, and own production model health.

Serve as a techno-functional business analyst: gather and translate requirements, design functional specifications, support integrations and data flows (APIs, databases, cloud), collaborate with architects and developers, support UAT and deployment, and drive process improvements and change management for digital transformation initiatives.