Description

Experience Required

8–10+ years of experience in Software Engineering or Data Architecture.

Minimum 4+ years of hands-on experience designing, developing, and deploying AI/ML systems in production environments.

Required Skills & Qualifications

Enterprise AI Strategy

Lead the transition of AI initiatives from localized Proof of Concepts (PoCs) to scalable, enterprise-wide production systems.

AI Technology Selection

Evaluate and recommend the most appropriate AI technologies, including Deep Learning, Natural Language Processing (NLP), Computer Vision, and Generative AI, based on business requirements, cost, latency, scalability, and data privacy considerations.

AI Solution Architecture

Design end-to-end AI architectures, including data ingestion, model training and fine-tuning, deployment, monitoring, and lifecycle management.

MLOps & Infrastructure

Design and implement robust MLOps practices, including Continuous Integration (CI), Continuous Deployment (CD), and Continuous Training (CT), to ensure reliable model performance and prevent model drift.

Data & Integration

Collaborate closely with Data Engineering teams to design scalable AI data architectures, including Vector Databases, Retrieval-Augmented Generation (RAG) workflows, and enterprise data pipelines.

AI Governance & Ethics

Establish AI governance frameworks and guardrails to ensure models are fair, transparent, secure against adversarial attacks, and compliant with data privacy regulations such as GDPR and CCPA.

Cost Management

Demonstrated experience optimizing AI infrastructure costs, including GPU resource allocation, token optimization, and efficient management of large-scale AI workloads.

Database & Data Warehousing

Strong understanding of SQL and modern data warehouse platforms such as Snowflake and BigQuery for AI data pipeline orchestration.

Communication & Leadership

Exceptional communication skills with the ability to explain complex AI concepts, capabilities, and limitations to executive leadership and non-technical stakeholders.

Proven leadership experience driving enterprise AI initiatives across cross-functional teams.

Preferred Technical Skills

Generative AI

Machine Learning (ML)

Deep Learning

Natural Language Processing (NLP)

Computer Vision

Python

MLOps

CI/CD & CT Pipelines

Vector Databases

Retrieval-Augmented Generation (RAG)

SQL

Snowflake

BigQuery

AI Infrastructure & Cloud Platforms

Key Skills

Education

Bachelor's degree