AI Solution Architect

The AI/ML Solution Architect is responsible for designing and leading end‑to‑end AI and machine learning solutions, from data ingestion and feature engineering to model deployment and monitoring, with a strong focus on data management, governance, and scalability. The role works closely with product, data, and engineering teams to translate business problems into robust, production-grade AI solutions that deliver measurable business impact Key responsibilities Design end‑to‑end AI/ML architectures covering data ingestion, data pipelines, feature stores, model training, deployment, and monitoring on cloud or hybrid environments. Collaborate with business stakeholders to understand requirements and convert them into technical AI/ML solution designs, architecture diagrams, and implementation roadmaps. Work with data engineering teams to define data models, data flows, and integration patterns ensuring data quality, lineage, security, and governance across sources and platforms. Provide hands‑on guidance to data scientists and ML engineers on model selection, feature engineering, experiment design, and performance optimization Establish and promote best practices for MLOps, including CI/CD for ML, model registry, monitoring (drift, performance, bias), and retraining strategies. Evaluate and recommend AI platforms, tools, and frameworks (e.g., cloud AI services, ML frameworks, vector databases) in line with enterprise standards and cost constraints. Lead technical workshops, proofs of concept, and solution demos with internal stakeholders and customers to validate AI/ML approaches and demonstrate value. Ensure non‑functional requirements such as security, compliance, scalability, reliability, and performance are embedded into AI/ML solution designs. Document solution architectures, data flows, and design decisions, and ensure knowledge transfer to engineering and operations teams. Stay current with advancements in AI/ML, data platforms, and best practices, and act as a subject matter expert within the organization. Data management experience 3+ years of practical experience in data architecture or data engineering aspects within analytics/AI projects. Strong SQL skills and experience with relational databases and at least one modern data warehouse or data lake platform (e.g., Snowflake, BigQuery, Redshift, Azure Synapse, Delta Lake). Experience designing data models, schemas, and data pipelines for analytics and ML, including batch and/or streaming ingestion (e.g., ETL/ELT tools, Spark, Kafka, or similar). Good understanding of data governance concepts: data quality, cataloging, metadata management, access control, and compliance (PII, GDPR or similar). Job Type: Contract Pay: $116,139.07 - $139,866.41 per year Application Question(s): Are you okay to work on full time ? What is your annual Salary expectation ? We have $140K annual with benefits will that work for you ? What is your current location ? Experience: AI/ML: 10 years (Required) MLOps: 10 years (Required) CI/CD: 10 years (Required) Snowflake, BigQuery, Redshift, Azure Synapse, Delta Lake: 10 years (Required) ETL/ELT tools, Spark, Kafka, or similar: 10 years (Required) Work Location: On the road