99.7%
Deployment reliability
Made production releases steadier by tracing failures through Jenkins, Docker runtime behavior, and AWS EC2 deployment paths.
Parvez Shaik - Software Developer / Full-Stack / Backend
Software that ships.
Software Developer experienced in building web applications, backend services, APIs, and database-driven systems across the software development lifecycle. I work across React, TypeScript, Node.js, Python, Java, SQL databases, Docker, Jenkins, AWS EC2, and AI retrieval systems, with a strong focus on performance, testing, deployment reliability, and practical product impact.
Open to Software Development Engineer, full-stack, backend, cloud, and AI retrieval roles.
01 - Impact
Measured engineering impact.
420 -> 295 ms
PostgreSQL latency reduction
Improved SQL-backed workflows by tightening indexes, query paths, and the backend data access layer.
35 min
Release time saved per sprint
Moved configuration, smoke-test, and integration checks earlier so release cycles had fewer avoidable surprises.
23%
Review effort reduced
Added agent-assisted evaluation to an AI content workflow while keeping human review and measurable feedback in the loop.
02 - Role Lens
Pick the signal you need.
Selected lens
Backend/API
Production services, data access layers, REST/GraphQL/gRPC integrations, auth-aware APIs, and SQL tuning.
420 -> 295 ms PostgreSQL latency
Django and GraphQL analytics APIs
gRPC vector database services
Node.jsExpress.jsDjangoFlaskFastAPIGraphQLgRPCPostgreSQL
03 - Work
Featured projects.
Featured project
Agentive Med
A multi-agent Alzheimer care assistant with supervisor orchestration, PubMed-backed FAISS retrieval, citation checks, and separated nutrition and medical agents for more verifiable responses.
PythonAG2FAISSPubMed RAGLLMsMulti-Agent Systems
Results
AG2 supervisor orchestration
PubMed-backed FAISS RAG
Medical citation checks
Featured project
Distributed Vector Database for AI Applications
A distributed vector database prototype using gRPC service communication, RocksDB storage, GraphRAG, LlamaIndex, and AWS S3 support for large-scale retrieval workloads.
PythongRPCRocksDBLlamaIndexAWS S3GraphRAG
Results
140M+ embedding target
93 ms average query latency
Context-aware search at scale
04 - Experience
Professional experience.
01
Aug 2024 - May 2026
Research Software Developer
Luddy School of Informatics, Indiana University Bloomington
Indiana, US
PythonFlaskMySQLRedisGraphRAGLlamaIndexAutoGen
Built research-backed software systems for educational content workflows, combining backend engineering with applied AI retrieval.
23%
Less manual evaluation time
2,800+
Assessment items supported
72% -> 83%
Content relevancy lift
18%
Faster model evaluation
- Worked on Python services, data pipelines, review tooling, and LLM-assisted retrieval workflows designed for real evaluator feedback rather than isolated demos.
- Connected databases, retrieval frameworks, and cloud deployment pieces into workflows that supported repeated content review and model evaluation cycles.
- Balanced AI automation with practical verification needs so generated content could be reviewed, measured, and improved over time.
02
Sep 2022 - Apr 2024
Software Development Engineer II
IBM
Bengaluru, India
Node.jsExpress.jsPostgreSQLReactDockerJenkinsAWS EC2
Owned production application work across backend services, database performance, frontend modules, and release reliability.
420 -> 295 ms
Data retrieval latency
45%
Fewer deployment failures
99.7%
Deployment reliability
78 -> 91
Lighthouse score
- Worked through the full delivery loop: implementing services, improving SQL-backed workflows, supporting React interfaces, and reducing deployment friction.
- Partnered with DevOps and QA teams to diagnose runtime issues and make Jenkins, Docker, and AWS EC2 deployments more predictable.
- Treated performance and reliability as product work, connecting backend latency, frontend responsiveness, and release quality to user-facing outcomes.
03
Aug 2021 - Sep 2022
Software Development Engineer
Cognizant
Hyderabad, India
ReactGraphQLDjango APIsDockerJenkinsAWS EC2
Built internal analytics and reporting applications where frontend responsiveness, API integration, and reliable delivery mattered for daily business use.
21.6%
Faster data rendering
82 -> 39 min
Environment setup time
17%
Fewer manual deployment errors
- Connected React dashboards with GraphQL and Django APIs so internal users could work with fresher operational data.
- Improved dashboard refresh behavior by looking at API fetching, component rendering, and the handoff between frontend and backend systems.
- Supported containerized backend environments so teams could set up, test, and release with fewer manual steps.
04
Jan 2021 - Jul 2021
Software Developer
Widhya
New Delhi, India
PythonTensorFlowSpaCyPandasScikit-learnRNN
Started in applied machine learning and data workflow automation, building discipline around repeatable experiments and measurable model quality.
88.4% -> 93.2%
Validation accuracy
27%
Less repetitive testing time
- Worked on text classification, preprocessing, experiment scripting, and model evaluation with a focus on reproducibility.
- Built the habit of measuring changes carefully, which still shapes how I approach backend performance, testing, and AI retrieval workflows.
05 - Strengths
Engineering focus.
Backend and APIs
Service layers, REST and GraphQL APIs, auth flows, SQL-backed workflows, and production debugging.
Cloud and Delivery
Dockerized deployments, Jenkins and GitHub Actions workflows, smoke checks, and AWS-based runtime support.
AI Retrieval
RAG and GraphRAG workflows grounded by vector search, evaluation loops, citation checks, and multi-agent orchestration.
06 - Skills
Technical toolkit.
Languages
PythonJavaScriptJavaTypeScriptC
Web Development
React.jsReduxTypeScriptJavaScriptHTMLCSSTailwind CSSLighthouse
Backend and API
Node.jsExpress.jsFlaskFastAPIDjangoREST APIsGraphQLgRPCOAuth 2.0JWT
Databases and Storage
PostgreSQLMySQLMongoDBRedisRocksDBFAISSSQL QueriesQuery Optimization
Cloud and DevOps
AWS EC2AWS S3AWS LambdaAzureDockerKubernetesJenkinsGitHub ActionsTerraformApacheBashCI/CD
Testing and Quality
Unit TestingIntegration TestingSmoke TestsDebuggingTroubleshootingRoot Cause AnalysisProduction Support
ML and Data
TensorFlowPandasScikit-learnRNNData PreprocessingModel EvaluationData Pipelines
AI and Retrieval
RAGGraphRAGPubMed RAGLlamaIndexFAISSAutoGenAG2SpaCyLLMs
07 - Education
Education.
Aug 2024 - May 2026
Master of Science in Computer Science
Indiana University Bloomington
Bloomington, IN, USA
Graduate study focused on computer science foundations and software systems, alongside research software development work at the Luddy School of Informatics.