R&D Engineer

Tech R&D Engineer Research & Innovation Focus

Role Summary

The Tech R&D Engineer at Netcore Cloud leads advanced research and innovation initiatives, deeply evaluating emerging backend and AI engagement technologies to incubate pioneering capabilities for high-scale omnichannel marketing platforms. This role emphasizes technology scouting, deep benchmarking, experimental design, and technical analysisbuilding proof-of-concept systems, driving comparative studies on tech stacks, and shaping the adoption of novel engineering practices within Netcores cloud infrastructure.

Key Responsibilities

• Conduct in-depth technical research and comparative benchmarking of backend, AI, and infrastructure technologies to identify opportunities for performance, eliability, and scalability improvements.
• Drive systematic evaluation of new architectures (e.g., distributed systems, KV stores, vector DBs, stream processors), through rigorous experimentation, scaling studies, and technical documentation of findings.
• Lead the incubation and prototyping of emerging technologies, producing detailed analyses, design docs, and recommendations for organizational adoption or integration.
• Regularly scout, investigate, and analyze frontier technologies relevant to customer engagement, personalization, and real-time decisioning pipelines; present actionable insights to product and platform leadership.
• Collaborate with engineering, data science, and product teams to evaluate build/buy strategies for new capabilities, providing research summaries and experimental data to guide decisions.
• Develop proof-of-concept systems and experimental frameworks to stress-test new patterns in distributed messaging, ML/AI personalization, and ultra high-throughput computing.
• Author whitepapers, RFCs, and technical articles to share research discoveries across Netcore engineering and the broader tech community.

Minimum Qualifications

• Bachelors or Masters in Computer Science, Engineering, or a related field with strong foundations in algorithms, distributed systems, and research methodologies.
• 3+ years of experience in backend engineering / research, with proven skills in analyzing, benchmarking, and evaluating new system architectures and technologies at scale.

Preferred Qualifications

• Hands-on contributions to open-source research projects or experience publishing technical papers on benchmarking, distributed systems, or cloud platform innovation.
• Experience running comparative studies of technology stacks (e.g., messaging systems, Databases, cloud runtimes), with expertise in prototype design, and data-driven reporting.
• Familiarity with tech incubation and the transition from experimental prototypes to production deployments.

Tools and Technologies

• Extensive experience in GCP & AWS cloud platforms
• Extensive experience with system benchmarking tools (YCSB, Sysbench, HammerDB), profiling frameworks, and cloud-native instrumentation stacks.
• Proficiency in Python, Go, Java, or similar systems languages for rapid technology prototyping and evaluation.
• Deep understanding of event-driven systems, real-time analytics, and AI/ML integration patterns in cloud-native environments.
• Deep Understanding of technologies like Kafka, Apache Spark, Apache Storm, Cassandra, MongoDB, Aerospike, Vertica, BigQuery, Redshift, Druid, Vector

Databases & Graph Databases.

Impact Metrics

• Number of successful experimental prototypes incubated and adopted by engineering teams.
• Published benchmarks, whitepapers, or technical reports that inform strategic technology decisions.
• Measurable improvements in platform scalability, reliability, or engagement attributed to research findings and new tech integrations.