Shashank N S

Software Engineer

India1 yr 9 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Built AI-driven tools adopted by major OEMs.
Resolved critical MongoDB issues under zero-downtime.
Earned multiple Spot Awards for exceptional contributions.

Stackforce AI infers this person is a Backend Engineer specializing in AI-powered SaaS solutions.

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Skills

Core Skills

PythonMicroservicesAi-powered ApplicationsSystem DesignMachine Learning

Other Skills

JiraFlaskREST APIsMongoDBKubernetesLLMsAIOllamaJavaDatabasesDeep LearningMySQLNoSQLAmazon Web Services (AWS)Docker

About

I build backend systems that ship to production and stay there. As a Senior Engineer at Samsung Semiconductor India Research, I've spent 2+ years designing Python microservices, distributed automation pipelines, and AI-powered tooling used by 10+ OEM teams including Dell, Lenovo, HP, and Samsung. My core stack is Python (Flask, FastAPI), C++, MongoDB, REST APIs, Kubernetes, and Elastic Stack (ELK). I own end-to-end delivery — from system design and API architecture to CI/CD pipelines and production stabilization. I also integrate LLM-based capabilities where they solve real engineering problems: I built an offline, secure LLM workflow using Ollama that lets teams run AI-driven code analysis without cloud dependency. A few things I'm proud of: earning back-to-back Spot Awards at Samsung for resolving a critical MongoDB data corruption issue under zero-downtime constraints, clearing the Samsung SWC Advanced Exam, and building an AI PDF analysis tool now used by 10+ OEM partners for release comparison. I hold an M.Tech in Computer Science from NIT Calicut and a B.Tech from IIIT Dharwad. I'm currently open to Backend Engineer, Software Engineer, and Platform Engineer roles where systems scale, data flows fast, and engineering rigor matters.

Experience

1 yr 9 mos

Total Experience

1 yr 9 mos

Average Tenure

1 yr 9 mos

Current Experience

Samsung semiconductor

2 roles

Senior Engineer

Aug 2024 – Present · 1 yr 9 mos · Bengaluru

Led integration of end-to-end test automation across NVMe, SATA, Performance, Power, and Mass domains, reducing cross-team onboarding time by ~40% by owning core platform modules and standardizing service interfaces.
Designed and deployed 5+ Python microservices (Flask, REST APIs, MongoDB) consumed by 3 cross-functional teams, improving service reliability by resolving critical Kubernetes and MongoDB infrastructure bugs under zero-downtime constraints.
Built an AI-driven PDF analysis and release comparison tool using LLMs, adopted by 10+ OEM teams (Dell, Lenovo, HP, Samsung), cutting manual report review time by an estimated 60%.
Developed an OS-agnostic device discovery microservice and enabled secure offline LLM workflows via Ollama, expanding platform coverage to air-gapped environments used by enterprise clients.
Recognized with Spot Awards (2x) for resolving a production MongoDB corruption incident and for enabling in-house LLM-based code optimization — both delivered without service disruption.

JiraSystem DesignPythonFlaskREST APIsMongoDB+2

Student Trainee

Jan 2024 – Jul 2024 · 6 mos · Bengaluru

Contributed to backend service development during a 7-month internship, building foundational modules later integrated into production automation pipelines used by cross-functional engineering teams.
Gained hands-on experience with the full Samsung SSIR tech stack (Python, MongoDB, Flask, REST APIs, ELK), enabling direct transition to a full-time Senior Engineer role in August 2024.

JiraSystem Design

Intellect design arena ltd

Stipendary General Trainee

Jan 2021 – Jun 2021 · 5 mos · Mumbai · Hybrid

Developed Java-based backend modules integrated with relational databases using JDBC, building foundational knowledge of enterprise application architecture and data access patterns.
Delivered assigned modules within sprint timelines in a hybrid Agile environment, developing collaboration practices across distributed teams in a financial technology context.

JavaDatabases

Technocolabs softwares inc.

Machine Learning Intern

Oct 2020 – Nov 2020 · 1 mo · Remote

Built a spotify song recommendation engine and credit default analyzer using collaborative filtering in Python, applying ML fundamentals to a real dataset and delivering a working prototype within a 2-month remote engagement.

PythonMachine Learning