Staff Augmentation

Skilled data & AI engineers, ready to contribute

Extend your team with engineers who are screened by practitioners, not just keyword-matched, so they deliver from the first sprint.

Roles we provide

Specialists across the data & AI lifecycle

Glue, EMR, Spark, Redshift, Athena, Kinesis. Builds and operates reliable pipelines.

Owns data platform design, mentors the team, and sets engineering standards.

Lakehouse, warehouse and governance design across AWS, Snowflake and Databricks.

dbt, SQL and semantic layers that turn raw data into trusted metrics.

Model development, feature engineering and deployment on SageMaker.

Pipelines, model registry, monitoring and CI/CD for machine learning.

RAG, agents, Amazon Bedrock, vector search and LLM evaluation.

Terraform, CDK, CI/CD, networking and security for data workloads.

Hiring models

Scale capacity up or down for a project or a peak period.

Evaluate fit on real work before making a permanent offer.

We source and screen; you hire full-time onto your team.

Process

Role, skills, seniority, timeline and how your team works.

Candidates are assessed by practicing data and AI engineers.

You meet a small set of strong, relevant candidates.

We stay engaged to make sure the engagement succeeds.

For engineers

We are always interested in talking with strong data engineers, ML engineers and GenAI practitioners.

Email your resume and a short note about the work you enjoy most to info@praitna.com.

Tell us about the role and your timeline. We will come back with a plan and qualified candidates.