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Pune, Maharashtra, India
Hybrid
Aera Technology is a pioneer in the growing category of Decision Intelligence Platforms and a Leader in the Gartner® Magic Quadrant™ for 2026 – the technology to digitize, augment, and automate decision-making processes with AI and machine learning. Through our AI decision automation platform, Aera Decision Cloud™, we are helping the best-known brands in the world make smarter, faster decisions.
Privately-held and VC-funded, we have a global team of over 400 Aeranauts – and we’re growing. We deliver Decision Intelligence innovation and services that enable enterprises to automate and scale decision making with accuracy and speed. We continue to be the trusted choice of market leaders for our proven ability to generate value and unlock opportunities that were previously unattainable.
The Modeling Sustaining Engineer is a hands-on role responsible for diagnosing, troubleshooting, and resolving complex production issues related to customer decision models, data pipelines, recommendations, and business logic running on the Aera platform. This is a cross-functional role where you will partner closely with Customer Success, Product, Engineering, and Modeling teams to identify root causes, drive resolutions, and improve platform reliability.
The ideal candidate combines strong analytical skills, data modeling expertise, and a deep understanding of enterprise business processes. You will become a subject matter expert (SME) for customer implementations and platform modeling capabilities.
Investigate and resolve complex customer production issues related to decision models, Modeling, recommendations, data ingestion, and business processes.
Analyze model execution, recommendation generation, data transformations, and platform behavior to identify root causes.
Triage and prioritize high-priority customer issues while ensuring timely communication and resolution.
Work closely with Engineering and Product teams to drive permanent fixes and platform improvements.
Develop deep expertise in customer implementations and become an SME for specific platform capabilities.
Perform impact analysis and validate fixes before deployment.
Create and maintain troubleshooting guides, runbooks, and knowledge base articles.
Proactively identify recurring issues and recommend improvements to reduce support volume.
Support root cause analysis (RCA) activities and contribute to continuous improvement initiatives.
Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field.
4+ years of experience in enterprise application support, data analytics, business intelligence, modeling, or related areas.
Strong SQL skills and experience analyzing large datasets.
Experience troubleshooting data pipelines, ETL processes, data models, or analytics platforms.
Strong analytical and problem-solving skills with the ability to diagnose complex production issues.
Ability to understand business processes and translate technical findings into actionable insights.
Experience working with logs, monitoring tools, and debugging distributed systems.
Excellent communication and stakeholder management skills.
Passion for becoming a subject matter expert and driving customer success.
Willingness to learn new technologies and business domains.
Leverage AI-assisted engineering tools such as Claude, ChatGPT, Cursor, and similar technologies to accelerate troubleshooting, root cause analysis, documentation, and productivity.
Experience with enterprise planning, supply chain, finance, procurement, or operational business processes.
Familiarity with Python, Java, or scripting languages.
Experience with cloud platforms, data warehouses, and analytics tools.
Knowledge of decision intelligence, AI/ML, or optimization concepts is a plus.
