Rahul Nigam

Software Engineer

Bengaluru, Karnataka, India16 yrs 8 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

Expert in SaaS modernization and cloud-native architecture.
Proven track record in optimizing distributed systems.
Hands-on experience in high-concurrency automation solutions.

Stackforce AI infers this person is a SaaS and Healthcare specialist with expertise in cloud-native solutions and automation.

Contact

Skills

Core Skills

Saas ModernizationCloud-native ArchitecturePrinter Drivers

Other Skills

distributed systemsKubernetesAWSperformance optimizationAPI throughputdatabase migrationC#JavagRPCProtobufJavaPoetApache Kafkaevent-driven architecturewxWidgetsC++

About

I’m a systems-driven engineer who naturally thinks backwards from the customer use case to technology. With strong experience in SaaS modernization, distributed systems, and cloud-native architecture, I enjoy building scalable solutions that stay simple, maintainable, and outcome-focused. My background in both enterprise platforms and independent product exploration has shaped me to be pragmatic, hands-on, and comfortable operating in ambiguity. I’m a quick learner who adapts rapidly to new domains and technologies, and I thrive in startup environments where ownership, speed, and impact matter. I focus on reducing complexity, making sound architectural decisions early, and delivering solutions that provide real business value with faster ROI.

Experience

16 yrs 8 mos

Total Experience

4 yrs 2 mos

Average Tenure

8 yrs 4 mos

Current Experience

Automation anywhere

2 roles

Staff Engineer

May 2021 – Present · 5 yrs 1 mo

In the second phase of platform modernization, the architectural exploration was largely complete and the focus shifted toward scaling, stabilization, and production hardening of the SaaS-native platform.
Worked extensively on SaaS-based process orchestration, refining distributed workflow execution to support high concurrency and long-running automation scenarios. Contributed to the phased migration of orchestration components from ActiveMQ to Temporal, improving workflow reliability, retry handling, and durable state management while ensuring backward compatibility.
Played a significant role in scaling and optimizing service containers deployed on Kubernetes and AWS. Focused on runtime efficiency, startup performance, resource utilization, thread management, connection pooling, and memory tuning. Ensured high API throughput and low latency under production-scale workloads.
Led APM-driven performance initiatives using New Relic and Grafana. Analyzed distributed traces across critical execution paths, identified bottlenecks, and implemented optimizations to meet QoS and SLA targets across multiple automation flows.
Contributed as a core member in the phased migration from MSSQL to CockroachDB, addressing distributed SQL semantics, transaction behavior changes, query tuning, and schema evolution for horizontal scalability. Ensured controlled rollout with minimal operational disruption.
This phase transitioned the platform from architectural foundation to scalable, resilient, and production-grade SaaS execution at scale.

SaaS modernizationdistributed systemscloud-native architectureKubernetesAWSperformance optimization+2

Technical Architect

Jan 2018 – Apr 2021 · 3 yrs 3 mos

In the initial phase of modernization, worked as part of the core architectural team evaluating and laying the foundation for migrating Automation Anywhere’s C#-based Enterprise platform toward a SaaS-compatible, cloud-native execution model.
Participated in structured feasibility analysis of the compilation and execution layer, evaluating C++, C#, ANTLR, and Java against criteria such as cross-platform compatibility, runtime isolation, extensibility, performance, and long-term maintainability. Contributed to selecting Java as the strategic foundation for a scalable SaaS-oriented execution engine.
Technically led the migration of bot command implementations from C# to Java, ensuring feature parity and backward compatibility. Defined abstraction layers to decouple command definitions from runtime execution, enabling a more modular and extensible SDK model aligned with cloud architecture goals.
Introduced a structured JSON-based command configuration framework to represent command metadata and execution parameters, reducing hardcoded logic and improving flexibility and maintainability across modules.
Co-designed and implemented a dynamic compilation pipeline using JavaPoet. Built mechanisms to translate JSON command definitions into generated Java source code, compile it at runtime, and execute during bot execution. Ensured controlled class loading, thread safety, and robust error handling within the execution environment.
During this foundational phase, also introduced gRPC with Protobuf for internal service-to-service communication as part of the architectural evaluation. Defined strongly typed contracts and optimized inter-service communication to reduce latency and improve reliability across distributed components.
This phase established the architectural foundation for a scalable, extensible, and cloud-aligned command execution framework that enabled subsequent SaaS scale transformation.

C#Javacloud-native architecturegRPCProtobufJavaPoet+1

Self employed

Independent Product Exploration – Automation-Driven Inventory Ordering

Feb 2015 – Dec 2017 · 2 yrs 10 mos · Bangalore, India

Took a planned career break to explore a product idea (Pharmaji) focused on solving operational challenges in pharmaceutical wholesale-to-retail supply chains. The objective was to prevent stock-outs at retail outlets through simple, automated replenishment while minimizing system complexity. The Pharmaji domain was registered under my name, and the web application was hosted on AWS using Drupal for rapid front-end enablement.
Started from the customer workflow and worked backwards to design a lightweight automation layer that integrated with existing systems instead of replacing them. Leveraged open-source platforms including GnuCash (C++-based) for accounting and inventory tracking, and Magento for order management. Built custom plugins to enable embedded database queries and structured data extraction with minimal intrusion into core applications.
Designed and implemented a Java-based microservice as the orchestration layer. The service extracted stock position updates from GnuCash, published inventory events to Kafka for decoupled processing, and maintained a dedicated database table tracking the latest product-level stock status.
Implemented threshold-based automation where reorder limits were configured in Magento. At a scheduled time, the system evaluated stock levels and automatically created replenishment orders via Magento’s internal backend API when thresholds were breached. Supported both manual confirmation and auto-confirm workflows to balance automation with compliance needs in the pharmaceutical domain.
Applied event-driven architecture, idempotent order handling, and clear separation of business rules from integration logic. Prioritized simplicity, maintainability, and fast time-to-market. Built working prototypes validating technical feasibility and operational reliability before deciding not to commercialize after market evaluation.

AWSApache Kafkaevent-driven architecture

Efi

Principal Engineer

May 2013 – Jan 2015 · 1 yr 8 mos · Bangalore · On-site

Project: Cross-Platform Printer Driver UI & Fiery Controller Integration
Overview
Contributed as a core maintainer to a large-scale, wxWidgets (wxWizard)–based cross-platform printer driver/application used to manage printer properties, printing preferences, and job-level configurations.
The project also included a multithreaded client–server subsystem responsible for retrieving real-time Fiery Controller capabilities and dynamically adapting the UI based on supported device features.

wxWidgetsC++multithreadingPrinter Drivers

Amd

Senior Software Engineer

Oct 2008 – Apr 2013 · 4 yrs 6 mos · Bengaluru · On-site

Schematic Review Tool was a software application developed at AMD to assist engineers in reviewing electronic schematics for compliance requirements. The tool accepted schematic checklists and netlists as inputs, automatically validated the schematics against predefined compliance rules, and generated detailed review reports highlighting issues and deviations.
The application was designed to operate as a standalone solution as well as an online, fully automated system, enabling consistent, repeatable, and efficient schematic reviews while reducing manual effort and review time.

C++C#

Siemens information systems ltd

Senior Systems Engineer

Aug 2006 – Oct 2008 · 2 yrs 2 mos · Bengaluru · On-site

Quantification (Quant) Database was my first project at SISL. It is a customized Siemens database designed to persist and manage large-scale medical image and video data for clinical and analytical reference purposes.
The database architecture was optimized for high-volume, high-definition media handling. Primary database indexes were maintained on the main node using RAID standards, while lightweight metadata tuples were stored as references to the actual media locations. High-definition images and video files were distributed across multiple storage nodes to enable faster access, effective load balancing, and parallel retrieval of video frames for improved performance.

C++Medical Imaging