AI Engineer

AI Engineer

Design, engineer, and implement enterprise-scale AI/ML and generative AI solutions for clinical data workflows. Deliver secure, scalable architectures independently while maintaining accountability for project delivery and technical excellence.

- Conceive, design, and implement AI solutions; analyze workflows and devise innovative technical approaches

- Design secure, scalable architectures for AI/ML, generative AI, and agentic solutions

- Design and implement emerging AI technologies (RAG, agentic workflows, agent-to-agent communication)

- Build and deploy predictive analytics and generative AI solutions to production

- Develop robust data/model pipelines, APIs, and integration layers; establish AI/MLOps best practices

- Implement CI/CD, monitoring, observability

- Own project scope and delivery accountability

- BS in Computer Science, Engineering, Mathematics, Statistics or equivalent professional experience

- 5+ years software/data/ML engineering; 3+ years deploying ML solutions in production

- AWS:
Sage Maker, EC2, S3, Lambda, RDS, Glue, Athena, DynamoDB, Postgres

- Databricks:
Platform, Delta Lake, Spark, MLflow

- Programming:
Python, Py Spark

- Dev Ops:
Git, CI/CD, Docker, Kubernetes, IaC (Terraform/Cloud Formation)

Cloud: AWS (Sage Maker, EC2, S3, Lambda, RDS, Glue, Athena), Databricks (Delta Lake, MLflow, SQL)

Languages & ML:
Python, PySpark, SQL

Dev Ops:
Git, CI/CD, Docker, Kubernetes, Terraform, Cloud Formation

AI/Data:
Generative AI frameworks, LLMs, vector databases, Apache Spark