I am a results-oriented software engineer with a proven track record of building scalable, production-grade systems and AI-driven platforms. I enjoy leading cross-functional teams, designing distributed architectures, and delivering high-impact products. I thrive on solving complex problems and turning ideas into reliable, data-driven software. I currently serve as Founding Software Engineer at PandasAI (YC W24) in Munich, where I design LLM agent pipelines, RAG workflows, and secure prompt engineering. I also guide technical strategy as CTO and Co-Founder of E-Mareez Care, shaping end-to-end development and cloud-based deployments. My background spans data science, AI research, and scalable software engineering across startups and consulting engagements.

Arslan Saleem

I am a results-oriented software engineer with a proven track record of building scalable, production-grade systems and AI-driven platforms. I enjoy leading cross-functional teams, designing distributed architectures, and delivering high-impact products. I thrive on solving complex problems and turning ideas into reliable, data-driven software. I currently serve as Founding Software Engineer at PandasAI (YC W24) in Munich, where I design LLM agent pipelines, RAG workflows, and secure prompt engineering. I also guide technical strategy as CTO and Co-Founder of E-Mareez Care, shaping end-to-end development and cloud-based deployments. My background spans data science, AI research, and scalable software engineering across startups and consulting engagements.

Available to hire

I am a results-oriented software engineer with a proven track record of building scalable, production-grade systems and AI-driven platforms. I enjoy leading cross-functional teams, designing distributed architectures, and delivering high-impact products. I thrive on solving complex problems and turning ideas into reliable, data-driven software.

I currently serve as Founding Software Engineer at PandasAI (YC W24) in Munich, where I design LLM agent pipelines, RAG workflows, and secure prompt engineering. I also guide technical strategy as CTO and Co-Founder of E-Mareez Care, shaping end-to-end development and cloud-based deployments. My background spans data science, AI research, and scalable software engineering across startups and consulting engagements.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
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Work Experience

Founding Software Engineer at PandasAI (YC W24)
September 1, 2023 - Present
Led design and development of the PandasAI library, building LLM agent pipelines, RAG workflows, vector store integrations (Chroma, Qdrant), and secure prompt engineering. Built PandasBI, a production analytics platform using TypeScript (Node.js, Express) and Python (FastAPI), with a React and Next.js frontend deployed on AWS Lambda and EC2. Developed PandaETL, an OCR-based document processing and ETL platform for unstructured PDFs, enabling vectorization, AI-powered data extraction, and LLM-based chatbots. Designed event-driven, parallel processing architectures and deployed scalable ETL and inference pipelines on AWS ECS. Built a data analytics platform enabling LLM-powered chat over CSV files and production databases with a semantic layer supporting joins across datasets. Integrated enterprise data sources including BigQuery, Databricks, Snowflake, PostgreSQL, and MySQL, with dataset storage on AWS S3. Built real-time analytics and AI dashboards, including event-based user tracking
CTO and Co-Founder at E-Mareez Care
January 1, 2022 - September 1, 2023
Owned technical strategy and system architecture, leading end-to-end development and aligning platform design with business and customer requirements. Developed and maintained web and mobile applications using JavaScript, TypeScript, React, Next.js, and React Native. Led backend development and REST API integrations, ensuring secure, scalable, and high-performance systems. Designed and implemented CI/CD pipelines on AWS, enabling automated deployments and improved reliability. Collaborated with cross-functional teams and mentored engineers while enforcing best practices for performance, security, and maintainability.
Data Scientist at Quant Data Solutions
June 1, 2020 - December 1, 2021
Analyzed over 10 years of historical market data across equities, options, and crypto to generate and validate 50+ trading hypotheses with measurable alpha potential. Built visualization and research frameworks that reduced hypothesis validation time by 40 percent, accelerating strategy iteration and research throughput. Developed high-performance trading algorithms in C++ using Intel intrinsics, improving backtest and simulation runtimes by 3x. Led code reviews to resolve performance bottlenecks and memory issues, reducing production system latency by 25 percent and improving system stability. Delivered forecasting models for US, Korean, and crypto markets used by hedge fund clients to support live trading and portfolio decisions.
Technical Team Lead at Automotive Artificial Intelligence
June 1, 2017 - June 1, 2020
Led the ReplicaR team, coordinating frontend and backend developers to deliver advanced simulation systems. Developed scenario parameterization modules, improving test coverage for drive safety and robustness. Optimized performance by enabling parallel execution of parameterized scenarios, significantly improving testing speed and system scalability. Designed and implemented an incident detection module to identify live simulation incidents and convert them into testable scenarios. Built a domain-specific language parser and executor for OpenScenario M-SDL using C++ and ANTLR4.
Junior Software Engineer at Zigron
June 1, 2016 - November 1, 2017
Contributed to large-scale big data analytics projects using Apache Spark, Hadoop, Kafka, Amazon Kinesis, and Cassandra. Built a network analytics pipeline to ingest data from Amazon Kinesis, store in Cassandra, and analyze using Apache Spark with Java. Developed a VPN analytics application to track and predict user churn using Apache Spark. Researched and evaluated migration of FraudLens databases from SQL to NoSQL, including MongoDB, Cassandra, and HDFS.

Education

Bachelor of Science at National University of Computer and Emerging Sciences (FAST-NUCES), Islamabad
June 1, 2012 - June 1, 2016

Qualifications

Applied Data Science Module I
January 11, 2030 - February 19, 2026
Applied Data Science II: Machine Learning and Statistical Analysis
January 11, 2030 - February 19, 2026
Python 3 Deep Dive Part 1
January 11, 2030 - February 19, 2026
Agile Scrum Fundamentals
January 11, 2030 - February 19, 2026
New Manager Training in Essential Skills
January 11, 2030 - February 19, 2026

Industry Experience

Software & Internet, Professional Services, Healthcare, Media & Entertainment, Education