diff --git a/work.tex b/work.tex
index 35103f9..1fe8831 100644
--- a/work.tex
+++ b/work.tex
@@ -1,3 +1,18 @@
+\datedlocatedsubsection{Nov 2024 - Present}
+{SAS Institute, Glasgow, UK}
+{Senior Associate Software Developer}
+{%
+    A global leader in analytics and AI software, SAS is empowering organizations across more than 145 countries.
+    %
+    \begin{itemize}
+        \item Spearheaded the design and development of a microservices-based platform (\textbf{Go}, \textbf{Python}, \textbf{Postgres}, \textbf{Redis}), enabling massively parallel task execution at accelerated rates compared to the legacy solution.
+        \item Architected distributed task scheduling with \textbf{Ray} and \textbf{KEDA}-powered autoscaling on \textbf{Kubernetes} clusters.
+        \item Authored and maintained the platform's \textbf{unit test} suite and \textbf{CI/CD} pipelines to guarantee reliability across all services.
+        \item Triaged and fixed Viya 4 UI (\textbf{TypeScript}) and backend (\textbf{Go}/\textbf{Java}) issues.
+        \item Prototyped a lightweight isolation platform for the SAS language executor using \textbf{Linux kernel} capabilities and system calls.
+    \end{itemize}
+}
+
 \datedlocatedsubsection{Jun 2023 - Sep 2023}
 {WebHotelier | primalRES, Athens, Greece}
 {Software Engineering Intern}
@@ -29,18 +44,3 @@
         \item Authored clean and maintainable code which was tested using unit, integration, and end-to-end testing.
     \end{itemize}
 }
-
-\datedlocatedsubsection{Jul 2019}
-{InterSearch Worldwide, Dubai, UAE}
-{Intern}
-{%
-    Ranked among the 30 largest executive search firms in the world, InterSearch Worldwide has 90 offices in 50 different countries.
-    %
-    \begin{itemize}
-        \item Developed a \textbf{Python} CLI Tool to automate Candidate CV and Financial Documentation Entry, extracting information from .pdf, .doc, and .docx CVs to a \textbf{FileFinder} database.
-        \item Incorporated \textbf{XML} parsing techniques for data extraction from Microsoft Word documents, and \textbf{Optical Character Recognition} with OpenCV to interpret non-editable PDFs.
-        \item Applied \textbf{Natural Language Processing} using NLTK to categorize text tokens such as names, addresses, and skills.
-        \item Navigated database interactions using PyAutoGUI, a workaround due to limited direct database access.
-        \item Refined the E-mail spam filter to improve productivity and internal communications.
-    \end{itemize}
-}