Platform Support Engineer ( AI/ML )

Client Note: We need someone who can support the platforms our developers use, rather than build AI/GenAI solutions themselves.


Core Technical Skills

Vector Databases: Hands-on experience with Elasticsearch or similar; understanding of
similarity search, indexing strategies, and embedding management.
Linux Systems: Strong command-line skills; shell scripting; system-level monitoring and
debugging.
Python Programming: Proficient in automation scripting; experience in building AI
models, data pipelines, and OpenAI integrations.
Big Data Technologies: Familiarity with Hadoop-based platforms like MapR and
Hortonworks.

AI Platform; Production Support
Experience supporting predictive AI workloads in production.
Troubleshooting across data ingestion, model inference, and deployment layers.
Familiarity with CI/CD pipelines and containerization (Docker, Kubernetes).
On-call support for GenAI and predictive pipelines (1 week every 6 8 weeks).
Understanding of enterprise disaster recovery (DR) solutions including backup and
restore.

Observability; Monitoring
Ability to define and implement observability strategies for AI systems.
Experience with tools such as Splunk, Grafana, ELK stack, OpenTelemetry.
Proactive monitoring of model failures, latency, and system health.

Bonus Qualifications
Multi-cloud Experience: Exposure to Google Cloud Platform and Azure environments.
Data Science Lifecycle: Involvement in full-cycle projects including problem definition,
data exploration, modeling, evaluation, training, scoring, and operationalization.
MLOps Principles: Understanding of model lifecycle management and collaboration with
data scientists to deploy solutions.