Software Architect for Autonomous Control & Decision

We are developing an advanced Command & Control platform designed to ingest and analyze large volumes of internal, customer, and external operational data in real time.

The system enables data-driven decision-making, adaptive automation, and situational awareness across multiple domains combining large-scale data engineering, distributed systems, and applied machine learning.

Responsibilities

• Define and lead the end-to-end data architecture from ingestion and streaming pipelines to storage, analytics, and model serving.
• Design real-time data infrastructure that supports multi-source data fusion, high throughput, and ultra-low latency decision cycles.
• Establish cloud and edge architectures to ensure system scalability, reliability, and performance.
• Lead the implementation of data-driven decision frameworks and autonomous process orchestration.
• Build robust MLOps foundations - model lifecycle, deployment, versioning, and continuous monitoring.
• Collaborate with algorithm, platform, and DevOps teams to deliver a unified operational picture.

Requirements

• 7+ years in Data/Platform/Big Data architecture, with experience building real-time operational systems.
• Deep hands-on expertise with streaming frameworks (Kafka, Pulsar, Kinesis) and processing engines (Flink, Spark Structured Streaming).
• Experience with Time-Series / OLAP databases and Lakehouse technologies .
• Proficiency in Kubernetes, microservices, and observability (Prometheus, Grafana, OpenTelemetry).
• Strong programming skills (Python, Scala, or Java or Node.js).
• MLOps and production ML experience (Like MLflow, Seldon, KServe, or SageMaker).
• Strong system design mindset and ability to operate in fast-paced, data-intensive environments.

Tech Highlights

Kafka · Flink · ClickHouse · Iceberg · Airflow · Kubernetes · Argo · Grafana · OpenTelemetry · gRPC · Python · MLflow · Redis.