Systems, scale, signal.
Software engineer building backend systems, AI platforms, and production-grade software.
Software Engineer working across distributed systems, AI-enabled platforms, backend services, and cloud infrastructure with Java, Python, Kafka, and AWS.
$ engineer.profile
name = "Jeshwin William James"
focus = ["Java", "Python", "Kafka", "AWS", "AI Platforms"]
current = "State Street"
strength = "Backend platforms, distributed systems, AI-enabled products"
research = "Improved Security on Mobile Payments Using IMEI Verification"
Code
GitHub
Public repositories, architecture-heavy builds, and ongoing engineering work.
→ github.com/jeshwinwilliam
Career
LinkedIn
Experience, credentials, and professional network.
→ view profile
Publication
Springer Publication
Published work on IMEI-based mobile payment security.
→ read paper
Direct
Email
Reach out for roles, collaborations, speaking, or technical consulting.
→ jeshwin.w.james@gmail.com
Core Skills
Grouped by the engineering capabilities I bring to production software.
Backend Engineering
Java, Spring Boot, REST APIs, gRPC, Spring Security, Hibernate, JPA, service design
Distributed Systems
Kafka, JMS, asynchronous workflows, retry strategies, dead-letter queues, resiliency patterns
AI Platforms
Python, workflow orchestration, AI-assisted review systems, platform integration, evaluation-minded tooling
Cloud, Data & Operations
AWS, GCP, Docker, Kubernetes, PostgreSQL, Oracle, Redis, Prometheus, Grafana, ELK, CI/CD
Experience
Experience spanning financial systems, commerce platforms, and production engineering.
2026-Now
Software Engineer · State Street
Built low-latency fund transaction and reconciliation services with Java, Spring Boot, Kafka, JMS, Oracle, PostgreSQL, Docker, Kubernetes, Jenkins, and AWS.
● Jan 2026 - Present
- Improved platform throughput by 40% through event-driven transaction pipelines.
- Reduced database query latency from 3.2s to under 1.1s in production.
- Enabled operations teams to resolve breaks 35% faster with workflow dashboards.
2022-24
Software Engineer · Accenture | Flipkart
Delivered backend systems for large-scale checkout and payment flows using Java, Spring Boot, Kafka, Cassandra, MySQL, Redis, Elasticsearch, Docker, Kubernetes, Jenkins, and GCP.
Feb 2022 - Dec 2024
- Improved payment success rate by 12% with smart-retry payment orchestration.
- Reduced end-to-end API latency by 35% through performance tuning.
- Cut infrastructure overhead by 22% via scaling and cloud optimization.
Featured Builds
Projects that show engineering breadth, systems thinking, and implementation depth.
01
Open Repo
PR Intelligence Platform
AI-assisted pull request analysis platform with event-driven review orchestration, persistent review history, and observability-first service design.
AI Platform Highlights
- Spring Boot microservices
- Kafka-based orchestration
- Persistent review history and failure recovery
- Docker-based local deployment and metrics hooks
02
Open Repo
Distributed Order Processing Platform
Order, payment, inventory, and logistics workflow architecture with Kafka-driven orchestration, idempotent processing, and resilient failure recovery across service boundaries.
Distributed Systems Highlights
- Saga-style order workflow
- Retry handling and dead-letter isolation
- API-first ingestion and monitoring hooks
- Horizontally scalable consumer design
03
Open Repo
Mobile Payment Security System
Security-focused software system based on IMEI-driven device verification to strengthen mobile payment authentication, trust, and fraud-aware decision flows.
Security Platform Highlights
- Research-backed implementation
- Authentication design lens
- Payment security use case
- Publication-connected project story
System Design Library
Architecture case studies grounded in my own backend, platform, and AI-oriented work.
Each case study focuses on requirements, event flow, key decisions, trade-offs, and failure handling instead of generic interview diagrams.
Distributed Order Processing Platform
API gateway, order service, payment, inventory, and logistics workflows connected by Kafka with idempotency, retries, and saga-style recovery.
ClientGatewayOrder Service
KafkaPaymentInventoryLogistics
- 50,000 events per minute design assumption
- No duplicate payment execution
- Replayable event flow and audit trail
PR Intelligence Platform
GitHub webhook ingestion, Kafka queues, analysis workers, AI-assisted review services, and resilient result delivery with observability and rate limiting.
GitHubWebhook APIKafka
WorkersAI ServiceReview Store
- Webhook burst absorption
- Failure-aware async review flow
- Rate limiting and worker isolation
Real-Time Transaction Reconciliation System
Trade ingestion, validation, ledger updates, duplicate detection, and reconciliation workflows designed for high-integrity financial operations.
TradesValidationKafka
LedgerReconciliationOps
- Low-latency reconciliation path
- Consistency versus throughput trade-offs
- Partitioned processing and auditability
Internal/private implementation - case study generalized from production work.
Mobile Payment Security System
IMEI-aware mobile payment security architecture with device identity validation, authentication orchestration, risk checks, and fraud-aware recovery flows.
Mobile AppAuth APIRisk Engine
IMEI CheckDevice StorePayment Decision
- Device identity validation
- Payment fraud reduction lens
- Research-connected system design
Publication
Peer-visible work beyond code repositories.
Peer-Reviewed Springer Conference Paper
Improved Security on Mobile Payments Using IMEI Verification
Peer-reviewed conference paper published in Springer's Advances in Intelligent Systems and Computing proceedings for ICSADL 2022, focused on a stronger mobile payment security model centered around IMEI-based device verification.
W. Jeshwin et al., “Improved Security on Mobile Payments Using IMEI Verification,” Sentiment Analysis and Deep Learning, Springer, 2023, pp. 183–193.
Credentials
Formal grounding plus current specialization.
AWS Certified Solutions Architect - Associate
Issued March 2026. Aligns with cloud-native architecture, reliability, and scalable platform design.
MS in Computer Science
Oklahoma City University, Oklahoma City, Oklahoma, United States. Graduation year: 2026.
B.Tech in Computer Science and Engineering
Hindustan University. Graduation year: 2022.
Contact
Open to software engineering roles across backend, distributed systems, and AI platforms.
I am especially interested in backend platforms, AI-enabled software, event-driven architecture, cloud infrastructure, and developer-facing systems where reliability, scale, and product thinking matter.
