Hi, I'm Srivatsa Gadicherla,
Software Engineer
Building scalable, production-ready solutions with AWS and modern technologies. Specializing in Cloud & AI Systems, I transform complex challenges into efficient and scalable software.
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Writing
Blog
Cloud, AI systems, and building software what I work on and learn. Pick a post and dive in.
OpenClaw: Runtime Efficiency vs Security Boundaries in a Viral Agent Stack
February 18, 2026
OpenClaw normalized the agent runtime: a single gateway, streaming tool calls, and a skills ecosystem that made deployment frictionless. The same choices expanded the trust boundary and the security story is still catching up.
Read more →Super Bowl LIX: Home vs. Philly
February 10, 2026
Same game. Two cities. Completely different feelings.
Read more →Open-Weight LLMs in 2026: Qwen, Llama, and GPT-OSS Dominate the Ecosystem
February 10, 2026
By early 2026, the open LLM landscape has shifted dramatically Chinese-developed models lead in usage and capability, with Qwen, Llama, and GPT-OSS defining the top tier.
Read more →Experience
Software Engineer Intern
Capgemini - Financial Services
June 2025 - October 2025 • Malvern, PA
- •Built and deployed a production AI-powered contact center platform using AWS (Amazon Connect, Lex V2, Lambda, Bedrock, S3, CloudWatch), supporting 24/7 customer service and reducing average customer wait times by 60–80%.
- •Developed Retrieval-Augmented Generation (RAG) pipelines integrating vector search and enterprise knowledge bases, improving response accuracy and reducing hallucinations using Claude, Amazon Titan, and LLM validation layers.
- •Designed and implemented backend services and REST APIs for call routing, conversation state management, analytics ingestion, and model orchestration using Python and AWS Lambda.
- •Implemented system observability and monitoring using AWS CloudWatch, Glue, Athena, and QuickSight, enabling real-time performance tracking and analytics dashboards.
- •Automated infrastructure provisioning using Infrastructure-as-Code (AWS CloudFormation) and implemented CI/CD pipelines for deployment validation and rollback safety.
- •Collaborated cross-functionally with product managers, ML engineers, and DevOps teams to deliver scalable cloud-native architecture supporting high concurrency workloads.
- •Authored technical architecture documentation and presented system design and business impact analysis to senior engineering leadership and stakeholders.
Software Engineer Intern (Cloud & AI Systems)
Proton Software Service (IONIX AI)
May 2024 – June 2025 • Chester Springs, PA
- •Designed, deployed, and maintained cloud-native backend infrastructure on AWS (EC2, IAM, VPC, Route 53, S3, ECS), supporting AI-powered production systems with high availability, scalability, and security.
- •Built and optimized backend services using Java (Spring MVC) and Python, implementing data validation, business logic, and microservice-based workflows to support real-time and batch inference pipelines.
- •Developed and maintained REST APIs for internal tooling, analytics ingestion, and model orchestration across distributed services.
- •Implemented CI/CD deployment workflows and container-based deployments using AWS ECS and Docker to reduce release time and improve system reliability.
- •Designed and deployed a relational database system to replace Confluence-based workflows, reducing data retrieval times by 60% and improving operational efficiency across engineering teams.
- •Built full-stack internal dashboards using JavaScript, HTML, Tailwind CSS, Node.js, and React, improving access to critical resources and increasing team productivity by 30%.
- •Developed Python-based batch processing pipelines for large-scale datasets using numerical optimization techniques (Black–Scholes modeling and Newton–Raphson method) to improve predictive accuracy and computational performance.
- •Automated ETL workflows to normalize and process large CSV and Excel datasets, improving data consistency and reducing manual processing overhead.
- •Collaborated with AI researchers, backend engineers, and DevOps teams to deliver scalable AI infrastructure supporting multi-tenant workloads.
Certifications
Skills
Cloud & Infrastructure
AWS (EC2, Lambda, S3, CloudWatch, ECS, IAM, VPC, Route 53, Amazon Connect, Lex V2, Bedrock, Glue, Athena, QuickSight, CloudFormation)DockerCI/CDInfrastructure-as-Code
Languages
PythonJavaJavaScriptTypeScriptSQL
Frameworks & Libraries
ReactNext.jsNode.jsSpring MVCTailwind CSS
AI/ML
RAG (Retrieval-Augmented Generation)Vector SearchLLM Integration (Claude, Amazon Titan)Batch ProcessingNumerical Optimization
Tools & Technologies
REST APIsMicroservicesETL PipelinesDatabase DesignSystem ObservabilityAnalytics Dashboards
Contact
I'm always open to discussing new opportunities, interesting projects, or just connecting with fellow engineers.
Feel free to reach out via email or LinkedIn.