Jobs at Aligned Automation

Design, develop, and optimize large-scale PySpark ETL/ELT pipelines on Databricks. Implement Delta Lake lakehouse architectures, tune Spark jobs, write complex SQL, monitor production, enable CI/CD, mentor junior engineers, and collaborate with stakeholders on scalable data solutions.

Build and maintain scalable ML pipelines and infrastructure, integrate LLMs, manage model lifecycle with MLFlow, collaborate in agile teams, write high-quality code, perform code reviews, deploy and monitor models in cloud environments.

Build, deploy, and maintain scalable ML pipelines and production models. Integrate LLMs into applications, manage model lifecycle with MLFlow, collaborate with data scientists and engineers, participate in Agile/Scrum, ensure code quality through reviews and CI workflows, and resolve infrastructure and deployment issues.

Lead digital transformation strategy and governance across multiple enterprise programs. Partner with executives to define roadmaps, drive AI/automation and analytics initiatives, ensure delivery excellence, mentor consulting teams, establish governance, and support business growth through solutioning and capability development.

Lead end-to-end delivery of enterprise transformation programs across process mining (Celonis), data & analytics, and AI/ML. Establish governance, manage cross-functional workstreams, track risks and dependencies, drive stakeholder and executive alignment, manage vendors/resources, and measure value realization through KPIs and adoption.

Design, build, and maintain scalable MLOps platforms and CI/CD pipelines. Containerize and orchestrate ML workloads, implement model versioning and monitoring, deploy models as APIs, optimize serving performance, ensure security and governance, and collaborate with cross-functional teams to productionize ML solutions.

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.

Process and manage support tickets, coordinate dispatches and replacement parts, respond to customer emails, document cases, and learn to troubleshoot enterprise servers, storage, and client systems while escalating complex issues to senior engineers. Work rotational shifts supporting global regions.

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.

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

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.