Arjun Dogra

Software Engineer

Bengaluru, Karnataka, India3 yrs 8 mos experience

AI ML PractitionerAI Enabled

Key Highlights

Led teams to design and deploy Generative AI solutions.
Reduced legal analysis time from weeks to minutes.
Enhanced front-end applications, improving usability and performance.

Stackforce AI infers this person is a Full Stack Developer specializing in AI-driven solutions within LegalTech and Web Development.

Contact

Skills

Core Skills

Software DevelopmentFastapiLangchainRagAngularFull-stack Development

Other Skills

Agentic AI DevelopmentOpenaiCascading Style Sheets (CSS)Front-end DevelopmentLLMsGraphRAGVectorDBReactGen aiCeleryRabbitMQLarge Language Models (LLM)JavaScriptDockerArtificial Intelligence (AI)

About

I’m a Full Stack Developer with 3+ years of experience delivering high-impact AI-powered applications from backend microservices to front-end UI. At Infosys, I’ve led teams to design and deploy Generative AI solutions using LLMs, LangChain, GraphRAG, and template-based guardrails. My tech stack includes FastAPI, Python, Docker, PostgreSQL, MongoDB, and VectorDB on the backend, with Angular and React on the frontend. I focus on building AI-powered solutions such as RAG pipelines, AI safety frameworks, and legal risk assessment systems.

Experience

3 yrs 8 mos

Total Experience

3 yrs 6 mos

Average Tenure

3 mos

Current Experience

Siemens

Software Engineer

Jan 2026 – Present · 3 mos · India · On-site

Software DevelopmentAgentic AI Development

Infosys

2 roles

Specialist Programmer

Apr 2025 – Feb 2026 · 10 mos · Bengaluru, Karnataka, India · Hybrid

Software DevelopmentOpenai

Digital Specialist Engineer

Jul 2022 – Mar 2025 · 2 yrs 8 mos · Bengaluru, Karnataka, India · Hybrid

Architected backend FastAPI microservices to support AI inference, integrating with Docker for scalable execution.
Developed AI-driven Legal Agents using LangChain, GraphRAG, and LLMs to automate legal use-case evaluation, reducing analysis time from weeks to minutes.
Designed and implemented a template-based LLM guardrail framework to detect and block jailbreaks, prompt injections, and policy violations in real-time.
Created a prompt-driven risk classification pipeline with RAG and vector databases, mapping AI use cases to defined legal risk categories.
Enhanced front-end applications in Angular and React by adding modular reusable components, improving usability by 2× and reducing page load time by 40% through lazy loading and code splitting.

Cascading Style Sheets (CSS)Front-end DevelopmentFastAPILangChain