[ GENERATIVE AI ENGINEER ]

Srijan Jaiswal

Generative AI Engineer

I don't just use AI. I architect it.

B.Tech AI student at SRM Institute, building end-to-end GenAI systems from RAG pipelines to LLM inference optimization. Google Certified Generative AI Professional. AWS ML Specialty. 4 production-grade AI systems shipped. Seeking Generative AI / ML Engineer internship.

#1 GSSoC Rank of 42,000+ contributors
0 AI Systems
0ms LLM Latency
0% F1-Score
02

Systems

production-grade builds, measured by latency, relevance, and reliability

DEVSECOPS Feb 2026 - Mar 2026

PatchPilot

Upload a codebase or GitHub URL → get SAST, dependency, and secret scan results → generate fixes → download a compliance evidence pack.

Automates code security triage end-to-end: upload a ZIP or import a GitHub repo URL, aggregate findings from Semgrep (SAST), OSV-Scanner (dependency vulns), and Gitleaks (secret detection), propose LLM-generated remediations for selected findings, run sandboxed verification, and export a ZIP evidence pack for audit/compliance. FastAPI backend + React/Vite/Tailwind frontend.

3 scanners aggregated SAST + deps + secrets Compliance evidence pack
PythonFastAPIReactViteTailwind CSSSemgrepOSV-ScannerGitleaksLLM Inference
GENERATIVE AI Dec 2025 - Apr 2026

Lexivault

Ingest PDFs, DOCX, TXT, or URLs → ask questions → get grounded answers with chunk-level citations streamed in real time.

Production-grade RAG system built with async FastAPI, LangChain orchestration, persistent ChromaDB vector store, and GPT-4o-mini generation. Retrieves top-20 chunks, cross-encoder reranks to top-5, and streams answers via SSE. Includes MMR retrieval, confidence scoring, SQLite analytics, a feedback loop, drift monitoring, Docker Compose deployment, and a dark glassmorphism frontend with zero build steps.

Sub-200ms retrieval Cross-encoder reranking SSE streaming answers PDF, DOCX, TXT, MD
PythonFastAPILangChainChromaDBOpenAI GPT-4o-miniVector SearchSQLiteDocker
ML SYSTEMS Mar 2026 - Apr 2026

Nethrex

End-to-end phishing detection pipeline: ingest from MongoDB, validate schema, train classifiers, serve predictions via FastAPI, and sync artifacts to S3.

Full MLOps pipeline for network threat detection. Loads phishing data from MongoDB, validates input schema and train/test drift, applies KNNImputer preprocessing, trains multiple classifiers and selects the best by F1 score, logs to MLflow/DagsHub, and saves artifacts. FastAPI inference endpoint serves predictions as HTML tables and CSV. GitHub Actions CI/CD builds and pushes to Amazon ECR for deployment.

Best model by F1 score MongoDB → S3 pipeline MLflow experiment tracking ECR + CI/CD deploy
PythonScikit-learnFastAPIMongoDBMLflowDockerAWS EC2AWS S3GitHub Actions
ML SYSTEMS Dec 2025 - Apr 2026

Driftmark

Ensemble tabular + NLP + sequence models into a calibrated churn probability, generate SHAP reason codes, produce campaign CSVs, and monitor feature drift.

End-to-end churn prediction system that builds weekly customer snapshots, trains LightGBM tabular, NLP ticket-text, and sequence models, ensembles them with a time-aware stacker + isotonic calibration, and generates SHAP-based explanation reason codes. Outputs a campaign CSV for CRM activation, a drift report with PSI per feature, and serves scores via FastAPI with batch and per-customer endpoints. CI-ready with Poetry and pytest.

Tabular + NLP + Sequence ensemble SHAP reason codes Drift monitoring FastAPI batch scoring
PythonLightGBMFastAPIPolarsSHAPPoetryScikit-learnMLOps
03

Record

signals from clubs, open source, research, and credentialed work

Experience

Achievements

Education

SRM Institute

B.Tech in Artificial Intelligence | GPA: 8.8/10 | 2024–2028

Certified

Google GenAI Professional

Plus AWS ML Specialty, Accenture AI, CISCO Data Science, JP Morgan SWE, Deloitte & TCS GenAI

Open Source

20+ Developers Adopted My Work

LangChain integration examples & RAG utilities on GitHub

Research Speaker

2 Internal Research Sessions

Presented RAG architectures and model fine-tuning to faculty and peers at SRM

04

Technical Stack

tools arranged as working nodes, not buzzword confetti

LLMsLangChainRAGVector DatabasesPrompt OptimizationModel Fine-TuningLLM Inference OptimizationHugging FaceNLP
Scikit-learnXGBoostTensorFlowPyTorchNeural NetworksCNNRNNTransformersPandasNumPyFeature EngineeringMLOps
AWS EC2AWS S3DockerKubernetesCI/CDGitHub ActionsModel Deployment MonitoringMLOps
PythonSQLJavaScriptC++
FlaskFastAPIREST APIsReactViteTailwind CSSGitGitHub

Certifications

Google Generative AI Professional2026
AWS ML Specialty2025
Accenture AI2025
CISCO Data Science2025
JP Morgan Software Engineering2025
Deloitte Data Analytics2025
TCS GenAI2025

[ OPEN CHANNEL ]

Let's Build
Something Real.

I'm actively seeking Generative AI and ML Engineer internships. If you're working on something that pushes the limits of what AI can do, I want to hear about it.