Akshay Mittal

Member of Technical Staff

AI-Augmented DevSecOps & Secure Cloud-Native Infrastructure Expert transforming financial security at global scale

About

I build AI-driven security and DevSecOps automation for cloud-native financial infrastructure at PayPal. I am an IEEE Senior Member, author of 30+ publications, and an active peer reviewer and program committee member across IEEE and ACM venues.

LinkedIn: 15,903 followers and connections.

50M+
Daily Transactions Secured
30+
Academic Publications
119+
Peer Reviews
$2M+
Cost Savings
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About

I'm a Member of Technical Staff, Software Engineer at PayPal with over 10 years of experience designing and delivering secure, scalable cloud-native applications across the entire technology stack. Currently, I architect AI-driven security solutions for PayPal that safeguard 50+ million daily transactions and $1.53 trillion in annual transaction volume.

My expertise spans AI-driven threat detection, DevSecOps automation, cloud-native infrastructure (Kubernetes, microservices), and critical infrastructure protection. I'm passionate about building secure systems, leading cross-functional teams, and mentoring the next generation of engineers.

As an active researcher and IEEE Senior Member (top 10% of 500,000+ members), I contribute to the academic community through 30+ peer-reviewed publications, book chapters in leading volumes from Springer Nature and IGI Global, and extensive academic service including program committee memberships for IEEE, ACM, and international conferences. I also serve as Chair and Organizer of the ACM Austin professional chapter (895+ members, 4.8/5 rating) and as a judge for prestigious competitions including NASA Space Apps Challenge, MassChallenge, and cutting-edge hackathons. My research spans AI-driven security automation, autonomous cybersecurity systems, and zero-trust architectures with practical applications in enterprise environments.

Education: PhD Candidate in Information Technology, University of the Cumberlands (Expected May 2026) | M.S. in Computer Science, Texas State University

Experience

Selected roles across financial services, retail, and cloud-native platforms, focused on measurable outcomes and production impact.

PayPal
Current

Member of Technical Staff, Software Engineer

  • Architected AI-driven security controls for systems processing 50+ million daily transactions and $1.53T annual volume.
  • Improved reliability with 20% p95 latency improvement and 30% reduction in error rates.
  • Reduced false positives by 30% and automated remediation for 60% of security incidents.
  • Led AI specFixer as SME/sole contributor; recognized with PayPal CTO Innovation Award (Innovation Excellence, 2nd Runners-Up).
AI Security Cloud-Native DevSecOps Kubernetes
Cox Automotive
Previous

Software Engineer

  • Delivered scalable cloud-native services supporting enterprise workflows across automotive technology platforms.
  • Built and hardened CI/CD and operational tooling to improve release safety and developer velocity.
  • Collaborated cross-functionally to ship reliable features in high-availability environments.
Cloud-Native DevOps Distributed Systems
Home Depot
Previous

Software Engineer (Enterprise Platforms)

  • Reduced manual tax calculations by 70% through platform automation and integration improvements.
  • Improved on-time deliveries by 15% and reduced fuel costs by 10% across 2,000+ trucks.
  • Built scalable services supporting real-world operational workflows at enterprise scale.
Automation Distributed Systems Enterprise
Charles Schwab
Previous

Senior Software Engineer (Cloud Automation & Migration)

  • Engineered cloud migration automation compressing timelines by 75% (24–36 months to ~6 months).
  • Achieved 99.8% first-attempt success rate through repeatable automation and guardrails.
  • Delivered $2M+ documented cost savings via platform efficiency and operational improvements.
  • Established reusable patterns adopted across financial services teams.
Cloud Automation Platform Engineering Reliability

Featured Projects

Case studies highlighting problem context, approach, and measurable outcomes. Each item links to a demo or repository where available.

AI Agent Infrastructure
GitHub

Agent Name Service (ANS): DNS for AI Agents

Problem: Multi-agent systems need secure identity, discovery, and trust routing across cloud-native environments.

Approach: Built a Kubernetes-native trust layer supporting MCP and A2A patterns with secure discovery and routing primitives.

Outcome: Enables reproducible agent identity + routing patterns and a clear demo path for platform teams adopting agentic systems.

AI Agents Identity Kubernetes
Research Reproducibility
GitHub

GenSecAI-Ops (SEDE 2025): RAG for Vulnerability Detection

Problem: Security teams need reliable AI assistance without high hallucination rates.

Approach: Implemented an evaluation-driven RAG workflow with reproducible experiments and governance-oriented outputs.

Outcome: Reported strong F1 performance with low hallucination profile, packaged as reproducibility code for research and practitioners.

RAG Security Research
Security & Authentication
GitHub

Risk-Based Flexible Authentication Framework

Problem: Static authentication is brittle; security posture should adapt to risk signals.

Approach: Built a dual-agent, ML-driven risk-adaptive workflow suitable for digital banking scenarios.

Outcome: A reusable reference architecture for teams implementing risk-adaptive auth and policy-based controls.

Authentication ML Security
MLOps / Model Serving
GitHub

KServe + Kubeflow Lite: Hands-On Model Serving

Problem: Teams need a practical path from model artifact to scalable serving on Kubernetes.

Approach: Built step-by-step demos covering serving primitives, deployment workflows, and operational best practices.

Outcome: A repeatable learning and onboarding resource for platform and ML teams adopting Kubernetes model serving.

KServe Kubeflow MLOps
DevOps Automation
GitHub

AI-Augmented DevOps: Secure Pipeline Automation

Problem: Modern pipelines fail due to configuration drift, operational complexity, and slow remediation loops.

Approach: Implemented self-healing and predictive maintenance patterns with security-by-design workflow guidance.

Outcome: Practical reference implementation demonstrating how AI can reduce toil and improve deployment reliability.

DevSecOps Automation Reliability

Awards & Recognition

Recognized for outstanding contributions to technology and innovation in the industry.

2025

IEEE UEMCON 2025 Best Paper Award

First Author - Cloud Security Research

Academic Excellence Cloud Security
2025

IEEE UEMCON 2025 Best Paper Award

First Author - LLM Framework Research

Academic Excellence AI/ML
2026

IEEE CCWC 2026 Best Paper Award

First Author - Best Paper in track

Best Paper IEEE
2025

IEEE ICCA 2025 Best Paper Award

First Author - Recognized among 13 accepted papers at conference

Best Paper IEEE ICCA
2025

PayPal CTO Innovation Award

Innovation Excellence - 2nd Runners-Up | Led AI specFixer project

Industry Innovation AI Automation
2025

IEEE Senior Member

Top 10% of 500,000+ global members | Official elevation letter from IEEE President

Professional Recognition IEEE
2025

Innovative Application in Analytics Award

Semifinalist - Long Island University School of Business

Data Analytics Innovation

Technical Expertise

Comprehensive skills spanning full-stack development, AI research, and secure cloud infrastructure.

AI & Cybersecurity Research

  • AI-Driven Threat Detection
  • Machine Learning for Cybersecurity
  • Agentic AI & Autonomous Systems
  • Federated Learning for LLM Agents
  • Zero-Trust Architecture
  • Self-Healing Security Platforms

DevSecOps & Cloud Infrastructure

  • Kubernetes & Container Orchestration
  • Microservices Architecture
  • CI/CD Pipeline Security
  • GitOps & Policy-as-Code
  • AWS, Azure, GCP
  • Cloud-Native Security Automation

Programming & Tools

  • Python, Go, Java, JavaScript
  • Shell Scripting & Automation
  • Cryptographic Identity Management
  • mTLS, OPA, DIDs
  • Distributed Systems
  • Edge Computing

Leadership & Academic Service

  • IEEE Senior Member
  • ACM Local Mentoring Committee
  • Technical Program Committee Member
  • Peer Review for Top-Tier Conferences
  • Competition & Hackathon Judging
  • Community Leadership (ACM Austin Founder)

Research & Publications

Contributing original research through peer-reviewed conference papers and journal publications in AI-driven security, DevSecOps, and cloud-native infrastructure.

Journal
2020

Data Privacy and Security with Cloud Computing

Digital Health Journal

Solo-authored | 18 citations

Cloud Security Data Privacy
Journal
2025

The AI Implementation Paradox

The AI Journal

Solo-authored

AI Strategy Enterprise AI
Conference
2025

Performance Optimization of LLM-Based Agentic Workloads in Kubernetes

IEEE ICCA 2025

First Author

LLM Kubernetes Performance
Conference
2025

Secure AI-SDLC for Critical Infrastructure: Operationalizing NIST AI RMF

IEEE ICCA 2025

First Author

AI Security Critical Infrastructure
Conference
2025

SPIFFE-Based Zero-Trust Authentication for AI Agent Ecosystems

IEEE ICCA 2025

First Author

Zero-Trust AI Agents
Conference
2025

ACM SIGCITE 2025 - 3 Papers

ACM Conference

First Author on 2 | Session Chair

ACM AI Research
Conference
2025

IEEE UEMCON 2025 - Best Paper Awards

IEEE Conference

TWO Best Paper Awards | First Author

Best Paper IEEE
Conference
2026

Privacy-Driven Cloud AI: Federated Learning and Zero-Trust

ICAIC 2026

First Author | Oral Presentation

Federated Learning Privacy
30+
Total Publications
3
Journal Papers
21+
Conference Papers
4
Best Paper Awards

Book Chapters & Publications

Contributing to leading academic publications from prestigious publishers including Springer Nature and IGI Global on cloud computing, AI security, and automated software engineering.

Published 2026

AI-Enabled DevSecOps

Springer Nature

Comprehensive chapter exploring AI-driven DevSecOps solutions for cloud infrastructure, focusing on automated security, policy enforcement, and secure deployment strategies in multi-tenant environments.

Full title: AI-Enabled DevSecOps for Secure Cloud Deployments

DevSecOps Cloud Security AI Automation
Approved 2025

Predictive Risk Intelligence for DevSecOps

IGI Global – Predictive Analytics and Risk Intelligence in AI-Driven Cybersecurity

Book chapter on building predictive risk intelligence pipelines for AI-Augmented DevSecOps in cloud-native environments.

Full title: Predictive Risk Intelligence for AI-Augmented DevSecOps in Modern Cloud Architectures

Risk Intelligence DevSecOps Cloud Security
Approved 2025

Risk-Intelligent Cloud-Native Cybersecurity

IGI Global – Predictive Analytics and Risk Intelligence in AI-Driven Cybersecurity

Framework chapter describing risk-adaptive AI-Augmented DevSecOps for securing cloud-native systems.

Full title: AI-Augmented DevSecOps for Predictive Cloud-Native Cybersecurity: A Risk Intelligence Framework

Cloud-Native DevSecOps Risk Framework
Forthcoming

AI-Powered Cloud-Native DevSecOps

Springer Nature Monograph

Comprehensive monograph on AI-powered DevSecOps for cloud-native systems. Under contract with Springer Nature.

Monograph Cloud-Native DevSecOps
Approved 2025

Securing Hybrid Cloud for Industrial IoT

IGI Global – Cybersecurity for Industrial IoT in Hybrid Cloud Environments

Chapter on deployment frameworks, strategic advantages, and security considerations for industrial IoT workloads running on hybrid cloud infrastructure.

Full title: Designing and Securing Hybrid Cloud Infrastructures – Deployment Frameworks, Strategic Advantages, and Security Considerations for Industrial IoT

Hybrid Cloud Industrial IoT Security Architecture
Approved 2025

AI Decision-Making for Cloud-Native Threats

IGI Global – Harnessing AI, Machine Learning, and Autonomous Agents to Combat Cross-Industry Threats

Chapter describing AI-augmented decision workflows for detecting and mitigating cross-industry security threats in cloud-native platforms.

Full title: AI-Augmented Decision-Making to Combat Cross-Industry Security Threats in Cloud-Native Environments

AI Security Decision-Making Cloud-Native

Academic Service & Judging

Contributing to the academic and professional community through peer review, program committee memberships, and judging prestigious competitions.

119+
Peer Reviews
83
Web of Science Verified
8+
Program Committees
10+
Judging Panels

Peer Review

Web of Science verified profile: ResearcherID NWG-9697-2025

  • IEEE Transactions on Cloud Computing
  • ACM Conference on Cloud Computing Security
  • IEEE Symposium on Security and Privacy
  • ACM SIGCITE 2025 (12 papers)
  • USRSE 2025
  • IJGIS Journal
  • IGI Global Book Chapters (35 reviews)
  • Cloud Security Alliance Standards
  • Verified peer reviews (selected venues):
    • International Conference on Computer and Applications (ICCA): 27
    • International Carnahan Conference on Security Technology (ICCST): 17
    • International Conference on AI in Cybersecurity (ICAIC): 10
    • International Conference on Artificial Intelligence in Information and Communication (ICAIIC): 8
    • IEEE International Conference on Information and Communications Technology: 8
    • IEEE International Conference on AI Engineering and Innovation: 6
    • IEEE Annual Computing and Communication Workshop and Conference (CCWC): 6
    • International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies: 5
    • International Conference on Informatics and Computational Sciences: 5
    • Colloquium for Information Systems Security Education (CISSE): 4

Technical Program Committees

  • MLOps World 2025 (Technical Core Committee)
  • IEEE MCSoC 2025
  • IEEE ETECOM 2025
  • SEDE 2025
  • ICIN 2026
  • ICAIIC 2026
  • CCNCPS 2026
  • CISSE 29th Colloquium

Competition & Hackathon Judging

  • NASA International Space Apps Challenge (RiverHacks)
  • MassChallenge (650+ participants)
  • Nexathon (770+ participants)
  • United Hacks (1,250+ participants)
  • F1 Hackathon (650+ participants)
  • AI Collective Lovable Hackathon ($10K prize pool)
  • Vibe Demo Day ($30K grants)
  • Digital Health Hub Foundation
  • Airia AI Hackathon

Community Leadership & Mentoring

  • Chair & Organizer, ACM Austin (895+ members, 4.8/5 rating)
  • Co-organizer, Kubernetes Austin community (1,500+ members)
  • Technical Team Member, MLOps Community (volunteer contributor)
  • Ambassador, IEEE Day
  • Ambassador, Data Science Salon (Austin)
  • Technical Advisory Member, The AI Collective
  • Alumni Advisor, Texas State University Center for Analytics and Data Science (TXST CADS)
  • Organizer, PyTexas Foundation
  • Mentor, CodePath
  • Software Programming Instructor, Code2College
  • Topmate mentor: 5/5 rating with 9+ testimonials, Top 1% mentor recognition (Topmate profile)

Speaking & Media

Leading global conversations on AI innovation, security, and DevSecOps through keynotes, conferences, and thought leadership platforms.

Feb 18, 2026

Data Science Salon ATX 2026

Expert Speaker & Panelist

One of five expert panelists discussing AI and data science innovations.

Conference Panel
Jan 13, 2026

GSDC AI in Action 2026

Featured Speaker

International organization (19,945+ LinkedIn followers).

International AI
Jan 24, 2026

The AI Space Podcast

Featured Guest

29,300+ YouTube subscribers.

Podcast Media
Jan 23, 2026

AI in the Real World Podcast

Featured Guest

Palo Alto Networks podcast.

Podcast Security
2025

IEEE GenAI Summit 2025

Speaking Engagement

IEEE Computer Society event.

IEEE GenAI
2025

MLOps World 2025 – Agent Name Service (ANS)

Featured Speaker

Conference session on Agent Name Service (ANS) for secure AI agent identity and trust in cloud-native environments.

MLOps Conference

Selected Work

A showcase of impactful projects spanning security systems, scalable platforms, and enterprise applications.

PayPal

AI-Driven Security for Financial Infrastructure

Architected security controls protecting 50+ million daily transactions and $1.53 trillion in annual transaction volume. Reduced false positives by 30%, automated remediation for 60% of security incidents, achieved 20% latency improvement and 30% error rate reduction.

50M+ Daily Transactions
$1.53T Annual Volume
30% Error Reduction
AI Security Financial Infrastructure PayPal
Charles Schwab

Cloud Migration Automation Framework

Engineered AI-powered automation frameworks compressing migration timelines by 75% (24-36 months to 6 months) with 99.8% first-attempt success rate. Documented $2+ million in cost savings and established methodologies adopted across financial services.

$2M+ Cost Savings
75% Time Reduction
99.8% Success Rate
Cloud Migration Automation Financial Services
Research

Agent Name Service (ANS)

DNS for AI Agents - Kubernetes-native trust layer for AI agent identity and security. Open-source implementation enabling secure multi-domain collaboration.

AI Agents Zero-Trust Kubernetes

Open Source Repositories

Production-grade open-source projects advancing AI agents, DevSecOps, and cloud-native infrastructure. Many are backed by active research and published work (including SEDE and ICCA 2025).

Let's Connect

I'm always interested in discussing new opportunities, technical challenges, or potential collaborations.

Podcast Feature

Deep-dive conversation on AI-Augmented DevSecOps, agent identity, and secure cloud-native infrastructure.

2025–2026

Featured Podcast Conversation on AI-Powered DevSecOps and Agent Trust

Guest Speaker

Discussing Agent Name Service (ANS), zero-trust architectures for AI agents, and practical patterns for securing large-scale cloud-native systems.

Podcast AI Security DevSecOps