Jobs at Aligned Automation

Owns the architecture and production delivery of enterprise data and AI solutions. Responsibilities include building data pipelines, governance integrations, semantic layers, AI agents, LLM applications, and readiness frameworks; applying technologies such as LangGraph, LangChain, RAG, and DataRobot; improving performance and scalability; and leading, mentoring, and managing a technical delivery team while engaging enterprise clients.

Business Analyst focused on data engineering and analytics, responsible for requirements gathering, stakeholder management, SQL analysis, data profiling, quality validation, reconciliation, reporting, and documentation. The role requires understanding ETL/ELT, pipelines, data warehousing, data modeling, databases, and Agile delivery. Experience with Python, PySpark, Airflow, cloud data platforms, APIs, and AI/ML data use cases is advantageous.

Leads enterprise data management, modernization, governance, and AI transformation initiatives. The role architects scalable cloud data platforms and AI-ready data products, including GenAI and agentic AI solutions using LLMs, RAG, vector databases, knowledge graphs, and semantic layers. Responsibilities include executive client engagement, consulting, solution architecture, program and team leadership, delivery governance, financial performance, pre-sales, account growth, and mentoring senior data and AI professionals.

Leads enterprise Data and AI consulting, solution architecture, presales, and delivery. Designs data management, cloud modernization, governance, analytics, GenAI, and agentic AI solutions using modern data and semantic technologies. Develops proposals, RFP/RFI responses, SOWs, estimates, roadmaps, business cases, and reusable accelerators. Conducts executive client workshops, guides implementation teams, and ensures scalable solutions deliver measurable business value and ROI.

Manage end-to-end delivery of enterprise transformation initiatives spanning Celonis process mining, data and analytics, AI/ML, and Agentic AI. Responsibilities include program governance, stakeholder alignment, scope and dependency tracking, risk and issue management, resource planning, vendor coordination, executive communications, KPI monitoring, benefits realization, and delivery health reporting.

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.

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.

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.

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 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 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 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.

Support end-to-end recruitment and HR operations including sourcing, resume screening, interview coordination, onboarding, employee record maintenance, HR documentation, attendance and leave tracking, and assisting employee engagement activities while ensuring confidentiality and compliance.

Consultant Business Analyst delivering supply chain and inventory analytics, data storytelling, and GenAI-enabled productivity. Analyze inventory and supply chain data, build dashboards, run root-cause analysis, create BRDs/FRDs and executive presentations, run stakeholder workshops, support UAT, and drive actionable optimization recommendations.