Senior Data & AI Platform Engineer - Immediate Requirement

Senior Data & AI Platform Engineer
Location: [City, State] | Remote‑friendly | Full‑time

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About the Role

We are seeking a seasoned Data & AI Platform Engineer who lives at the intersection of data architecture, backend engineering, and machine‑learning integration. In this role you will design and build the next‑generation data platform that powers our analytics, AI products, and business‑critical applications. You’ll own end‑to‑end data flows—from ingestion and transformation to unified data models and AI‑enabled services—while ensuring the system is highly scalable, performant, and reliable.

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Key Responsibilities

Area	What You’ll Do
Backend & System Design	• Architect and develop high‑throughput Python services (Flask/Django/FastAPI). • Optimize code and infrastructure for latency, throughput, and cost.
Data Architecture	• Define data‑modeling strategies (OLTP ↔ OLAP, star/snowflake schemas). • Design data‑lake and data‑warehouse solutions (Snowflake, BigQuery, modern lakehouse).
Ingestion & Transformation	• Build robust ETL/ELT pipelines (batch & streaming) using Airflow, dbt, Spark, or equivalent. • Implement data‑quality, lineage, and monitoring frameworks.
Unified Data Models	• Create and maintain a single source of truth across transactional, analytical, and AI workloads.
AI/ML Integration	• Design reusable ML‑enabled components (pattern detection, anomaly detection, relationship mapping). • Collaborate with data‑science teams to operationalize feature pipelines and model serving.
Cross‑functional Collaboration	• Partner with product, analytics, and infrastructure teams to align data solutions with business goals.
Reliability & Scalability	• Drive capacity planning, auto‑scaling, and fault‑tolerance across the platform. • Implement observability (metrics, logs, tracing) and incident‑response processes.

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Required Technical Skills

Category	Must‑Have Experience
Programming	Python (3.9+), strong OOP, async patterns, testing (pytest).
APIs	Design & implementation of RESTful services (FastAPI/Flask/Django).
Data Engineering	Data modeling (OLTP/OLAP), data‑warehousing concepts, data‑lake architecture, ETL/ELT design.
SQL & NoSQL	Advanced SQL (Snowflake, BigQuery, PostgreSQL, Redshift) and familiarity with document/graph stores.
Distributed Systems	Understanding of CAP theorem, consistency models, and micro‑service patterns.
Cloud Platforms	Hands‑on with at least one major cloud (AWS, GCP, Azure).
Orchestration	Airflow, Prefect, Dagster, or similar workflow engines.
ML Ops	Experience building feature pipelines, model versioning, and serving (e.g., TensorFlow Serving, TorchServe, Sagemaker, Vertex AI).
Version Control & CI/CD	Git, GitHub/GitLab, automated testing, containerization (Docker) and orchestration (K8s).

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Nice‑to‑Have

• Real‑time streaming (Kafka, Pulsar, Pub/Sub).
• Data‑lakehouse frameworks (Delta Lake, Iceberg, Hudi).
• Infrastructure‑as‑Code (Terraform, Pulumi).
• Experience with AI‑assisted coding tools (GitHub Copilot, Claude, Cursor).
• Side‑project or open‑source contributions in data/AI tooling.

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What We Value

• Curiosity & Self‑Learning – You stay ahead of emerging data & AI trends and love experimenting with new tools.
• Rapid Prototyping – Ability to spin up MVPs, iterate fast, and validate ideas with stakeholders.
• Collaboration – Strong communication skills to translate complex technical concepts for non‑technical partners.
• Ownership – You take end‑to‑end responsibility for the reliability and evolution of the platform.

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Experience

• 6–8 years of professional experience in data engineering, backend development, and/or AI platform engineering.
• Proven track record delivering production‑grade data pipelines and services at scale.

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Benefits & Perks

• Competitive salary + performance bonus.
• Comprehensive health, dental, and vision plans.
• Flexible remote‑work policy & generous PTO.
• Professional development stipend (conferences, courses, certifications).
• Access to cutting‑edge AI tools and a culture that encourages experimentation.

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How to Apply

Submit your résumé, a brief cover letter highlighting a recent data platform you built (including tech stack, scale, and impact), and any relevant GitHub/portfolio links to [recruiter@company.com] with the subject line “Senior Data & AI Platform Engineer – [Your Name]”.

We look forward to building the future of data‑driven intelligence together!