Engineering Manager (SCM Planning) - Product Engineering
Engineering Manager - SCM Planning
Work Location: Bangalore
Five Days onsite
About the Role
As an Engineering Manager - SCM Planning at Avathon, you will lead the design and delivery of scalable data infrastructure and AI platforms powering industrial intelligence solutions in the areas of demand forecasting, supply planning, inventory & Manufacturing and S&OP decision support for customers across energy, mining, manufacturing, and logistics.
You will drive cloud-native architectures, production-grade data pipelines, and AI-ready systems that enable advanced analytics and Generative AI applications. Partnering with Engineering, Product, and Applied Science teams, you will translate complex industrial challenges into secure, scalable technology solutions while shaping Avathon's platform engineering strategy. With 8+ years of experience including team leadership, you will build and grow a high-performing engineering team across onshore and offshore locations.
You Will
- Build and lead an engineering team responsible for Avathon's data and AI platform infrastructure
- Architect scalable industrial data platforms capable of handling high-velocity IoT and telemetry streams
- Design resilient real-time and batch data pipelines that power predictive maintenance, anomaly detection, and optimization use cases
- Establish MLOps frameworks to support continuous model training, deployment, and monitoring
- Partner with AI/ML, Product, and Service Engineering teams to deliver production-ready solutions to customers
- Ensure seamless production handoffs with strong documentation, observability, and SLAs
- Drive cloud infrastructure, DevOps best practices, and security compliance standards
- Scale engineering processes for multi-customer deployments in regulated and government environments
You'll Have
- 8+ years of experience in software engineering, data engineering, or AI platform engineering
- 2+ years leading technical teams (onshore + offshore preferred)
- Experience designing cloud-native data architectures across AWS, GCP, or Azure
- Strong experience with:
- Distributed data processing (Spark, Databricks)
- Streaming technologies (Kafka, Kinesis, IoT Core)
- Workflow orchestration (Airflow, Dagster, Prefect)
- Containerization and orchestration (Docker, Kubernetes)
- Experience building and operating production MLOps systems including CI/CD for ML, model registry, experiment tracking, and drift detection
- Strong programming expertise in Python and Django
- Familiarity with React frontend development
- Experience with CI/CD pipelines (Travis CI, Jenkins)
- Experience working with large-scale time-series or industrial telemetry data
- Solid understanding of system reliability, fault tolerance, and high-availability architectures
- Experience managing projects with customer-facing delivery components
- Excellent cross-functional communication skills
Preferred Qualifications
- Experience in SCM Planning, industrial AI, manufacturing, energy, utilities, or government sectors
- Exposure to edge computing architectures and data ingestion from industrial systems (OPC UA, Modbus, Ignition, PI Historian)
- Experience working with secure or regulated cloud environments, including on-prem and air-gapped deployments
- Familiarity with data governance and compliance frameworks
- Understanding of predictive maintenance or asset performance use cases
- Experience with LLM observability and evaluation tooling in production environments
Knowledge of graph databases or knowledge graph platforms
Interview Process
As part of the interview process, you will be asked to complete a technical case study assessment. Expect atleast two-three rounds of Technical interviewing rounds and one onsite round.
