Sai Akshay Gandlapalli

Software Engineer

India3 yrs 8 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in building high-performance FX trading systems.
Proficient in full-stack development with modern frameworks.
Strong background in cybersecurity and machine learning.

Stackforce AI infers this person is a Backend-heavy Fullstack Developer with expertise in Fintech and Cybersecurity.

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Skills

Core Skills

Backend EngineeringDistributed SystemsFrontend DevelopmentCybersecurityMachine LearningFull Stack Development

Other Skills

JavaC++Financial SystemsMarket ConnectivityIncident ManagementLinuxSQLD2CClient RelationsResponsive Web DesignUser Experience Design (UED)TeamworkInterpersonal SkillsSecurity ResearchCyber Operations

About

I’m a Computer Science graduate with experience building scalable software systems across full-stack development, distributed systems, and backend engineering. At ION Group, I worked on high-performance FX trading systems using Java and C++, contributing to core trading workflows and post-trade infrastructure. My work involved optimizing FIX message latency, improving system throughput through log analysis, and implementing order normalization mechanisms that significantly improved execution reliability in fast-moving markets. I also worked with CI/CD pipelines and production-grade systems where performance, reliability, and security were critical. Previously at Ford Motors, I developed full-stack web applications using Angular, Node.js, and Express, building features such as location-based search, SEO optimization, and scalable backend services. Beyond industry experience, I enjoy building impactful systems through projects. I’ve built platforms such as Relief Connect, a disaster response coordination platform, and CivicTracker, a microservices-based civic issue tracking system. I’m also exploring Generative AI, RAG systems, and agentic architectures to build intelligent real-time applications. My core interests lie in: • Backend and distributed systems • High-performance and scalable software • AI-powered applications and modern developer infrastructure

Experience

3 yrs 8 mos

Total Experience

1 yr 9 mos

Average Tenure

1 yr 4 mos

Current Experience

Ion

Technical Software Analyst

Jan 2025 – Present · 1 yr 4 mos · Hyderabad · On-site

Developed FX trading products using Java and C++, contributing to core trading and post-trade workflows.
Normalized FX orders and implemented new functionalities for Pegged Order execution, enabling consistent processing by the trading engine and achieving faster and more accurate fills.
Optimized FIX message latency by 0.097 ms and automated probe recovery scripts using Bash, minimizing downtime during rapid market movements.
Gained hands on deployment experience through Bitbucket and Bamboo pipelines. Remediated vulnerable codes to ensure security and compliance standards by generating Change Gateway Report.

JavaC++Financial SystemsMarket ConnectivityIncident ManagementLinux+5

Salesforce

Cyber Security Analyst

May 2024 – Jul 2024 · 2 mos · Hyderabad · On-site

Worked on XDR (Extended Detection and Response) solutions for continuous threat detection and endpoint security, supporting efforts to improve detection accuracy and reduce false positives through analysis. Collaborated with security engineers to understand real-world attack patterns, incident response workflows, and mitigation strategies. Contributed to strengthening scalability and gained hands-on exposure to cybersecurity, EDR, and large-scale security systems.

Security ResearchCyber OperationsXDRTenable NessusCybersecurity

Samsung india

PRISM intern

Oct 2023 – May 2024 · 7 mos · Bengaluru, Karnataka, India · Remote

Designed and developed a lightweight pet action recognition search engine using ANN and RNN models, optimized for low-dimensional video representations. Built behavior classification models using skeleton-based features extracted from video tracking pipelines, providing a discrete classification of animal behaviors using low-dimensional representations of videos (such as skeletons provided by tracking algorithms). Our approach combines strong supervision, weak supervision, and self-supervision to improve model performance and has achieved an accuracy rate of 94% by self-tuning each of the RNN and ANN models.

Computer VisionMachine Learning

Ford motor company

Full Stack Developer - Intern

Sep 2023 – Jan 2024 · 4 mos · Chennai, Tamil Nadu, India · On-site

I led the development and launch of a static web application focused on the early detection of tumour-based diseases using deep learning models, and also deployed, & implemented search Search Engine Optimization techniques, including server-side rendering, to enhance performance on the Google web browser.

Cross-team CommunicationProject ManagementBusiness UnderstandingFull Stack Development