2026SHIPPED
InfrastructureCloudDeveloper Tools
GitHub Readme Stats Deployment
Production infrastructure & self-hosting
A production-style deployment of GitHub Readme Stats, hardened behind Nginx with TLS and hosted on Oracle Cloud.
Open to high-impact engineering opportunities
Engineer.
Builder.
AI Innovator.
I build production AI and data systems across RAG, backend engineering, cloud infrastructure and automation.
02 / Engineering signal
Built across the stack, grounded in systems.
AI / MLBackend SystemsCloud InfrastructureSystem DesignFull-Stack EngineeringProduction Deployment
03 / Selected work
Systems worth talking about.
Production work, active builds and architecture explorations are presented as engineering case studies—not just screenshots and technology lists.
2026SHIPPED
AI / MLBackendDeveloper Tools
Production RAG Agent
Hybrid retrieval, reranking & grounded generation
A production-oriented retrieval-augmented generation system built around hybrid search, reranking, grounded answers and a publicly deployed demo.
2026IN PROGRESS
AI / MLBackendSecurity
Sentinel AI
AI digital media forensics platform
An architecture-first forensic platform designed to analyze digital media with production-grade APIs, persistence and extensible AI pipelines.
04 / Experience
Engineering with measurable impact.
I build intelligent software systems at the intersection of AI/ML, backend engineering, data engineering and cloud infrastructure—with an emphasis on reliability, automation and production readiness.
AI Engineer · Azure Data Engineer · ML EngineerProfessional summary
Download ResumeAI Engineer and Azure Data Engineer at Tata Consultancy Services with hands-on experience building production AI systems, Azure data pipelines, ETL workflows, CI/CD automation and backend APIs in the BFSI domain.
CIBC — CCDWM · BFSI
Production engineeringAI Engineer / Azure Data Engineer
Tata Consultancy Services (TCS) · September 2024 — Present · Bhubaneswar, Odisha
15 min → 30 secdocument lookup time
90%daily RAG adoption
~90%retrieval accuracy
12production Databricks notebooks
2 wk → 3 daysengineer onboarding
~70%pipeline maintenance reduction
1 hr → 10 mindeployment effort
~4 hrsregression time saved / release
2 days → 2 hrsAzure provisioning
Current focus
AI / ML / Generative AIBackend EngineeringData EngineeringCloud & InfrastructureMLOps / DevOps
Based in
Bhubaneswar, Odisha, India
Selected engineering evidence
Built and deployed a document-aware RAG knowledge assistant using Python, FastAPI, LangChain, Azure AI Search, text-embedding-3-large, Docker, Kubernetes and Azure Functions.
Built 12 production-ready Azure Databricks notebooks covering data ingestion, ETL, QA validation, ML preprocessing and deployment checks across four teams.
Engineered Azure Data Factory pipelines for data movement, orchestration, transformation and validation across three projects.
Built Azure DevOps CI/CD pipelines with automated testing, linting, static analysis, Docker builds, artifact publishing, environment promotion and rollback.
Streamlined QA regression testing with Python and Bash and developed Linux/Bash automation for connectivity, logs and service management.
Orchestrated Azure environment provisioning with ARM Templates and Azure CLI and systematized routine cloud operations with Python and Azure CLI.
05 / Growth
From infrastructure to intelligent systems.
A progression built through increasingly complex engineering problems, from self-hosted infrastructure to architecture-first AI platforms.
Current level
1,450 XPSystems Builder
23% progression
XP is a lightweight exploration layer. The engineering work itself is the real progression.
01
Linux · VMs · Networking
VM setup
Started building practical infrastructure fundamentals around Linux and self-hosted environments.
02
Docker · Docker Compose
Docker deployments
Moved from manually configured environments toward reproducible containerized workloads.
03
Nginx · TLS · DNS · Oracle Cloud
Reverse proxy + TLS
Learned to operate services behind a controlled public boundary with DNS, Nginx and HTTPS.
04
Python · FastAPI · AI/ML · PostgreSQL
AI pipelines
Expanded from infrastructure into architecture-first AI and backend systems.
05
FAISS · BM25 · RRF · Reranking · Hugging Face
Production RAG
Built and publicly deployed a hybrid RAG system with dense + lexical retrieval, reranking and grounded generation.
06 / Skills
A capability map, not a badge wall.
The stack reflects technologies and engineering practices used across professional work, projects and ongoing learning.
PythonLangChainLLMsRAGAI AgentsHugging Face TransformersPyTorchScikit-learnMLflowVector SearchText EmbeddingsOpenAI ModelsGarak
Azure DatabricksPySparkAzure Data FactoryAzure StorageADLSETL / ELTData IngestionData TransformationSQL
DockerKubernetes (AKS)Azure DevOps PipelinesGitHub ActionsCI/CDAutomated TestingStatic AnalysisARM TemplatesAzure CLI
Azure MLAzure AI SearchAzure FunctionsAzure Container InstancesAzure Container RegistryAzure Web AppsAzure MonitorAzure AD
FastAPIREST APIsLinuxBashGitPostmanVS Code
Linear AlgebraMultivariable CalculusProbability & StatisticsOptimization Theory
Cybersecurity FundamentalsOWASPAI / LLM SecurityPrompt Injection DefenceAzure Security Center
Engineering lab
House Prices — Advanced Regression
An end-to-end regression experiment exploring feature engineering, target transformation, cross-validation, hyperparameter optimization, and ensemble stacking.
Feature EngineeringLog Target Transformation10-Fold Cross ValidationOptunaXGBoostLightGBMCatBoostRidge Stacking
07 / About
Curious about systems that have to work.
I am an AI Engineer and Azure Data Engineer at Tata Consultancy Services, building production AI systems, Azure data pipelines, backend services, CI/CD automation and cloud tooling in the BFSI domain. Outside work, I build independently deployed systems such as a production-oriented RAG Agent and architecture-first platforms such as Sentinel AI, with a strong preference for measurable outcomes and production-minded engineering.
Professional engineering impact is separated from independently shipped work and from architecture-stage projects so the portfolio never presents planned systems as production software.
Architecture first.Evidence over hype.Build for evolution.
08 / Education & Learning
Foundations that support the build.
Formal foundations, completed learning and current certification goals that support the engineering work shown above.
Bachelor of Technology (B.Tech)
Computer Science and Engineering
Silicon University · Bhubaneswar, Odisha · September 2024
Engineering practice
Relevant coursework
Learning record
Certifications & learning
Intro to Machine LearningKaggle
Intermediate Machine LearningKaggle
Practical Deep Learning for Codersfast.ai
NLP CourseHugging Face
In progress
Microsoft Certified: Azure AI Engineer Associate (AI-102)Microsoft
In progress · Month 6AWS Certified Machine Learning — SpecialtyAWS
In progress · Month 9Microsoft Certified: Azure Administrator (AZ-104)Microsoft
In progress09 / Engineering badges
Depth, not decoration.
Explore the work to unlock lightweight recognition for engineering domains. The badges are a navigation aid—not a substitute for evidence.
Locked · +150 XP
Production Deployment Architect
Explore the GitHub Readme Stats production deployment.
Locked · +200 XP
AI Forensics Builder
Explore the Sentinel AI case study.
Locked · +200 XP
Grounded Retrieval Engineer
Explore the Production RAG Agent case study.
Locked · +100 XP
Architecture Explorer
Explore the architecture of a flagship project.
Locked · +150 XP
Systems Builder
Explore multiple engineering domains across the portfolio.
Locked · +150 XP
Cloud Systems Architect
Explore deployment and cloud engineering evidence.
10 / Contact
Have a hard problem? Let's build it.
I'm interested in ambitious engineering problems across AI, backend systems, infrastructure and product engineering.