We review applications weekly. Shortlisted candidates hear back within 5–7 business days.
Intro call → technical task or live coding → system/design discussion → culture fit and offer.
You’ll design reliable data pipelines and productionize AI features that create real business value. Work spans ELT/ETL, modeling and warehousing, orchestration, and serving analytics or LLM-powered capabilities (retrieval, RAG, agents). You’ll enforce data quality, monitor models, and ship with security and cost in mind.
Experience: 3–5+ years across data engineering and/or applied AI.
Data: SQL mastery, dimensional modeling, dbt, orchestration (Airflow/Prefect).
Warehouses: BigQuery/Redshift/Snowflake/Postgres; streaming with Kafka/Kinesis is a plus.
AI/LLM: Python, vector search (pgvector/FAISS/Pinecone), LangChain/LlamaIndex, prompt design, evaluation.
MLOps: Containers, CI/CD, experiment tracking/monitoring (MLflow/Evidently).
Location/Type: Remote-friendly (Lahore HQ) • Full-time.
Must-have
Strong Python + SQL, data modeling, and pipeline development (batch and/or streaming).
dbt or equivalent transformations; orchestration with Airflow/Prefect.
Building and serving LLM features (RAG, embeddings, safety/guardrails).
Testing, observability, and cost/performance tuning on a major cloud (AWS/Azure/GCP).
Excellent documentation and stakeholder communication.
Nice-to-have
Feature stores, real-time pipelines, or graph data.
Classic ML (scikit-learn/XGBoost) and basic statistics for evaluation.
Security/compliance awareness (PII handling, access controls, encryption at rest/in-transit).
