Senior AI Software Transformation Engineer (Distributed Computing)

Create an advanced AI-powered software transformation framework to speed up the modernization of complex analytical applications.

Develop architectural patterns and transformation methodologies for converting outdated computational tools into scalable cloud-native solutions.

Utilize AI agents, LLMs, and emerging AI engineering techniques to automate software analysis, code transformation, validation, and optimization.

Work with distributed computing specialists to design target architectures that leverage Spark-based execution models for large-scale data processing.

Lead technical investigations into restructuring, decomposing, or re-implementing existing software systems for efficient operation in distributed environments.

Develop reusable transformation pipelines, automation tooling, and engineering frameworks for large-scale software modernization.

Establish validation strategies and quality frameworks to ensure that transformed systems maintain functional correctness and reproducibility.

Make architectural decisions regarding scalability, maintainability, performance, and long-term platform evolution.

Collaborate with domain experts to understand application requirements and translate them into scalable technical solutions.

Prototype and assess new AI-assisted engineering approaches to enhance transformation speed, engineering productivity, and software quality.

Contribute to the organization's long-term strategy for AI-driven software modernization and engineering automation.

Proficiency in Apache Spark, PySpark, or similar distributed computing frameworks.

Competence in evaluating and enhancing application scalability, performance, and infrastructure efficiency.

Experience in modernizing legacy applications or transitioning software to new architectures.

Familiarity with working on data-intensive applications, analytics platforms, or high-performance computing systems.

Prior exposure to workflow orchestration, automation frameworks, or platform engineering.

Strong proficiency in Python, Scala, and developing Spark-based applications is desirable.

Knowledge of cloud-native data processing architectures is an added advantage.

Experience with scientific computing, computational biology, bioinformatics, or other computationally intensive analytical applications.

Exposure to high-performance computing (HPC), GPU computing, or large-scale parallel computing.

Prior involvement in building AI agents or autonomous software engineering workflows.

Familiarity with compiler technologies, static code analysis, program transformation, or source-to-source translation.

Experience with workflow orchestration platforms such as Airflow, Nextflow, or similar technologies.

Contribution to open-source frameworks or widely adopted developer tools is a plus.

Curiosity: Demonstrates ongoing interest in understanding project details and underlying principles, reflecting a continuous learning mindset.

Clarity and Understanding: Actively seeks clarity to ensure accurate and effective project implementation.

Insightful Approach: Proficient in grasping and addressing the fundamental needs and objectives underlying a project.

Implementation Proficiency: Able to outline and describe the phases of project implementation, breaking down complex tasks into manageable steps.

Effective Communication: Strong verbal and written communication skills, capable of tailoring messages appropriately for different audiences with clarity, relevance, and empathy.

Attractive salary package.

Generous vacation allowance, including flexible holidays.

Comprehensive health insurance and full support as per local labor laws.

Opportunities for professional development.

Provided lunches and access to coffee, tea, and snacks.

Additional benefits as per labor laws, ensuring support for your growth and well-being.

PEGASI – IT Recruitment Consultancy | Email: recruit@pegasi.com.vn | Tel: +84 28 3622 8666