Headline

Software Engineer | AI/ML Systems | FastAPI, LLM & Cloud Infrastructure | MS in Data Science

About

Computer Science Engineer with experience in contributing to production-grade backend, multimodal, and cloud-native systems across AI/ML, video intelligence, and data platforms. Experienced in architecting scalable pipelines using LLMs, RAG, vector search, microservices, and distributed cloud infrastructure. Proven track record in optimizing high-throughput systems, deploying agentic AI workflows, and engineering enterprise-ready solutions using AWS, GCP, and modern observability stacks.

Location

Mohali district

AI stack

deepmind

langfuse

manus

midjourney

Work experience

Junior Security Engineer at Extern, Apr 2026 - Present · 3 mos, Mohali district, India, Built and secured an MQTT-based IoT pipeline using Python, TLS encryption, and device certificates to simulate and protect real-time water monitoring systems. Conducted security testing, including replay attack simulations and TLS performance benchmarking, identifying vulnerabilities and tuning defenses. Developed a real-time security dashboard using Streamlit to monitor pipeline health, detect threats, and track system status.

Healthcare Data Scientist at Extern, Apr 2026 - May 2026 · 2 mos, Tracy, California, United States, Conducted exploratory data analysis on publicly available healthcare datasets, examining infection trends through variables like case counts, demographics, and time patterns to uncover meaningful insights. Leveraged AI tools such as ChatGPT and Claude to guide data discovery, generate research prompts, and support the creation of visualizations, dashboards, and reports on infection-related public health trends. Produced synthesis reports and presentations covering key areas including infection trends, data limitations, population insights, public health implications, and recommendations for stakeholder action.

Artificial Intelligence Engineer at Extern, Feb 2026 - Apr 2026 · 3 mos, Tracy, California, United States, Built AI pipelines to process pharmaceutical vendor files using OCR (Tesseract, PaddleOCR) and RAG for data extraction and classification. Developed a RAG-based document retrieval system with LlamaIndex, optimized with chunk tuning and open-source LLMs (Mistral, Phi-2). Conducted end-to-end evaluation of the document intelligence system—benchmarking OCR accuracy, RAG retrieval quality, and routing performance. Delivered a technical report outlining model trade-offs, optimization strategies, final deployment recommendations, and built a UI for demo purposes.

Software Developer at Modern Streaming, Dec 2025 - Present · 7 mos, Remote, Built a multimodal processing pipeline to analyze and index 500+ hours of unstructured telemetry data using YOLOv8, OpenCV, and LLM-based components, enabling searchable retrieval for auditing use cases. Reduced data processing overhead by ~40% by implementing a multi-threaded extraction pipeline with frame-skipping logic, improving throughput for high-resolution video streams. Developed validation workflows combining deep learning models with classical computer vision techniques (e.g., HSV thresholding) to support compliance-related checks. Improved inference efficiency by applying model optimization techniques such as KV caching and quantization, reducing latency for multimodal query workloads.

Full Stack Developer at ITScybersecurity, Sep 2025 - Present · 10 mos, Washington, District of Columbia, United States, As a core architect and engineer, I led the technical deployment of GOV4D, a sovereign AI governance platform designed for high-stakes public-sector and enterprise environments. I specialized in operationalizing complex AI policy into scalable, "policy-as-code" infrastructure, ensuring distributed AI deployments remain secure, compliant, and fully auditable. I engineered the core GOV4D engine based on a proprietary 10-pillar framework, developing a D1–D10 logic flow that automates the pipeline from raw data ingestion to the generation of immutable, SIEM-ready audit evidence. I built and managed critical integrations between enterprise governance tools (Collibra, OneTrust, Fiddler) and security systems (IBM QRadar, ServiceNow), unifying disparate workflows into a centralized governance source of truth. I developed the microservices, REST APIs, and data pipelines required to automate PII detection, adversarial risk scoring, and compliance mapping across frameworks such as NIST AI RMF, GDPR, and SOC 2. A key focus was architecting air-gapped and on-premise deployment patterns to meet strict national data residency and sovereignty requirements for government clients. On the full-stack side, I built real-time observability dashboards using Python and Streamlit, alongside Node.js backend services to monitor live governance traces and AI risk metrics. I also contributed to strategic system design for "Agentic Governance" modules, including multi-agent orchestration and persistent memory auditing, within a high-velocity, GitHub-based agile environment.

Software Developer at Triveni IT, Aug 2025 - Apr 2026 · 9 mos, New Jersey, United States, I gained hands-on experience in data collection, data cleaning, and data analysis while working with real-world datasets. I developed a solid understanding of statistical methods and machine learning fundamentals and applied them to practical business and analytical problems. I worked with tools such as Python, SQL, and data visualization platforms to analyze datasets, validate data quality, build analytical workflows, and develop simple predictive models. I also presented insights and findings in a clear and structured manner to support decision-making. I contributed to projects in collaborative environments, strengthened my problem-solving abilities, and became increasingly confident in handling tasks independently while proactively seeking guidance when required.

AI & ML Engineer at Smart Rewards Inc., Aug 2025 - Feb 2026 · 7 mos, Automating HR & Marketing Workflows: Build end-to-end pipelines on N8N to post job openings on CJNNow, YouTube, and LinkedIn automatically, reducing manual effort by ~60%. Email Automation: Design and manage automated HR email campaigns, including candidate notifications and interview reminders, saving ~10–15 hours/week. Social Media Content Management: Create, schedule, and publish posts on LinkedIn using ML-driven content optimization for higher engagement and relevance. Workflow Reliability & Monitoring: Implement logging, error handling, and performance checks within N8N to ensure stable and repeatable operations. Collaboration & Iteration: Partner with HR, marketing, and IT stakeholders to define requirements, validate workflow outputs, and continuously improve automation efficiency. Tech & Tools: N8N, Python, REST APIs, YouTube API, LinkedIn API, Automation Workflows, Scheduling, Basic ML/NLP, Git, Documentation

AI Intern at Smart Rewards Inc., Jun 2025 - Aug 2025 · 3 mos, Delivered a production RAG assistant that materially improved support KPIs: ~25% ticket deflection, ~70% reduction in manual search, and hours saved per agent per week in resolution time. Drove adoption from a 20-person pilot to 4 departments (120+ DAUs; ~500 MAUs), handling 10,000+ queries/month with p95 <500 ms and 150+ concurrent users. Full-stack ownership: corpus curation of ~5M internal docs, 768-d embeddings, ~50 GB Pinecone index; LangChain-based orchestration and evaluation harness for ongoing quality. Productionized on GCP (Cloud Run + autoscaling), Dockerized services, and GitHub Actions CI/CD; implemented OpenTelemetry tracing and Grafana observability. Reduced per-query costs by ~35% and nearly halved latency (p95 ~900 ms → ~500 ms) via caching, batching, and system-level performance tuning. Increased trust and usage with citations, confidence scores, and feedback loops; led training and authored runbooks, driving 60% adoption lift; showcased by CTO and featured in customer-facing materials; live with roadmap-backed expansion.

Data Science Intern at Smart Rewards Inc., Jan 2025 - Jun 2025 · 6 mos, Scaled clinical analytics across ~6 Phase II/III trials (~2,500–3,000 patients, ~40 sites) by integrating ~20M+ records from EDC, CTMS, LIMS, and ePRO; daily/weekly data refreshes for operational currency. Designed the analytics “product”: reusable Power BI templates and standardized ETL in Python/SQL Server that harmonized KPIs and accelerated new-study rollout. Sole owner of enrollment and deviation monitoring dashboards with RLS for PHI segmentation; automated lab/ePRO pipelines with Git versioning and Airflow scheduling. Embedded robust data governance: HIPAA and 21 CFR Part 11 compliance, de-identification, automated QC/anomaly detection, and cross-source reconciliation. Delivered measurable operating leverage: ~60% reduction in manual work (~100 hours/month), ~3-day faster query resolution, and ~2-week improvement to database lock on two key trials. Influenced study strategy via early SAE trend surfacing and variance analysis, reducing audit findings and regulatory exposure. Drove adoption through bi‑weekly readouts to Clinical Ops/Biostats/Regulatory and periodic steerco updates; work highlighted at the R&D townhall to senior leadership.

Education

Master of Science - MS, Data Science, Drexel University College of Computing & Informatics

Bachelor of Technology, Computer Science, SRM IST Chennai