AI & Data Architect

EPAM·Colombia·Удалённо·5д. назад

We are seeking an experienced AI & Data Architect with a strong background in technology, AI architecture, data and advanced analytics in the cloud. In this role, you will assess, redesign and evolve AI and data ecosystems in production within financial or insurance organizations. You will combine AI architecture vision, data governance, MLOps, integration of structured and unstructured data and the definition of technical capabilities needed to enable generative AI, agentic AI and intelligent automation solutions in regulated environments, ensuring that data is available, governed, traceable and suitable for feeding AI models, agents and production use cases.

Responsibilities

Review and evaluate the client's current AI and data architecture on GCP, AWS and internal platforms
Conduct an inventory of existing capabilities and platforms
Assessment of quality, completeness, availability, governance and accessibility of historical data for model training and operation
Identify technical gaps between the current state and the capabilities required for AI solutions in production
Proposal of the target AI and data architecture, maximizing the reuse of existing capabilities in GCP and AWS
Evaluate the maturity of current models, data pipelines, MLOps capabilities and observability mechanisms
Definition of responsible AI and data architecture guidelines aligned with SFC regulations
Assess the technical feasibility of AI use cases from the perspective of data, models, governance and operations
Build a map of AI use cases prioritized by impact, technical feasibility and data availability
Identify gaps in governance, lineage, privacy and data quality that may affect AI implementation
Definition of critical technical pivots for insurance processes such as claims, underwriting, issuance and administrative support
Present findings, risks, gaps and architectural recommendations to the Steering Committee

Requirements

Minimum of 8 years of experience in technology with at least 4 years in AI architecture, data or advanced analytics in the cloud
Expertise in Google Cloud Platform including Vertex AI, BigQuery and Cloud Storage
Proficiency in Google Cloud Cloud Run, Pub/Sub and Dataflow along with Data Catalog
Skills in Amazon Web Services including S3, RDS and Lambda as well as API Gateway, EventBridge and SQS
Knowledge of generative AI and agentic AI architectures including RAG pipelines, embeddings and agent orchestration with LLM in production
Background in cloud data architectures such as data lakehouse, query optimization and high-volume processing
Competency in data governance covering cataloging, lineage, data quality along with access policies, privacy and habeas data compliance
Understanding of MLOps including model training, versioning and drift monitoring as well as retraining and model observability
Capability to integrate unstructured data through documents, OCR and embeddings along with information extraction and classification
Familiarity with responsible AI including explainability, decision traceability and bias management with human-in-the-loop design
Skills in data security including encryption, masking and granular access control with IAM in regulated environments
Proficiency in data orchestration tools such as Apache Airflow, Cloud Composer or equivalent
Expertise in data observability covering quality monitoring, anomaly alerts and operational dashboards
Knowledge of C4 architecture and TOGAF methodology
Understanding of SFC guidelines on AI, data, explainability, auditability and automated decision-making