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I am Rajan J, an AI / NLP & GenAI Engineer with 5+ years of experience building and supporting NLP-driven systems, and more recently focusing on large language model prompting, evaluation, and safety testing. I have a strong foundation in enterprise chatbot and NLU platforms, with hands-on experience in prompt design, retrieval-augmented generation workflows, and LLM evaluation across internal and client-facing use cases. I am comfortable in cloud-based environments and cross-functional teams, with a delivery-focused approach to building reliable and maintainable AI solutions. I enjoy collaborating with data annotation, safety, and ML operations teams to push experiments from prototype to production, while prioritizing safety, grounding, and user experience.…I am Rajan J, an AI / NLP & GenAI Engineer with 5+ years of experience building and supporting NLP-driven systems, and more recently focusing on large language model prompting, evaluation, and safety testing. I have a strong foundation in enterprise chatbot and NLU platforms, with hands-on experience in prompt design, retrieval-augmented generation workflows, and LLM evaluation across internal and client-facing use cases. I am comfortable in cloud-based environments and cross-functional teams, with a delivery-focused approach to building reliable and maintainable AI solutions. I enjoy collaborating with data annotation, safety, and ML operations teams to push experiments from prototype to production, while prioritizing safety, grounding, and user experience.

Rajan J

AI Prompt Engineer, AI Engineer, Data Scientist, +2

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I am Rajan J, an AI / NLP & GenAI Engineer with 5+ years of experience building and supporting NLP-driven systems, and more recently focusing on large language model prompting, evaluation, and safety testing. I have a strong foundation in enterprise chatbot and NLU platforms, with hands-on experience in prompt design, retrieval-augmented generation workflows, and LLM evaluation across internal and client-facing use cases. I am comfortable in cloud-based environments and cross-functional teams, with a delivery-focused approach to building reliable and maintainable AI solutions. I enjoy collaborating with data annotation, safety, and ML operations teams to push experiments from prototype to production, while prioritizing safety, grounding, and user experience.…I am Rajan J, an AI / NLP & GenAI Engineer with 5+ years of experience building and supporting NLP-driven systems, and more recently focusing on large language model prompting, evaluation, and safety testing. I have a strong foundation in enterprise chatbot and NLU platforms, with hands-on experience in prompt design, retrieval-augmented generation workflows, and LLM evaluation across internal and client-facing use cases. I am comfortable in cloud-based environments and cross-functional teams, with a delivery-focused approach to building reliable and maintainable AI solutions. I enjoy collaborating with data annotation, safety, and ML operations teams to push experiments from prototype to production, while prioritizing safety, grounding, and user experience.

Available to hire

I am Rajan J, an AI / NLP & GenAI Engineer with 5+ years of experience building and supporting NLP-driven systems, and more recently focusing on large language model prompting, evaluation, and safety testing. I have a strong foundation in enterprise chatbot and NLU platforms, with hands-on experience in prompt design, retrieval-augmented generation workflows, and LLM evaluation across internal and client-facing use cases.

I am comfortable in cloud-based environments and cross-functional teams, with a delivery-focused approach to building reliable and maintainable AI solutions. I enjoy collaborating with data annotation, safety, and ML operations teams to push experiments from prototype to production, while prioritizing safety, grounding, and user experience.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

Prompt Engineer at Google

November 1, 2024 - Present

Led prompt design and optimization for LLMs (GPT-4 style and Google-supported models), focusing on improving response clarity, reasoning quality, and consistency. Supported retrieval-augmented generation (RAG) workflows with document ingestion, chunking strategies, and embedding-based retrieval to improve grounding. Built and refined LLM-powered backend services using Python and FastAPI for internal experimentation, evaluation, and knowledge-access workflows. Implemented NLP preprocessing pipelines with spaCy and NLTK; supported semantic and hybrid search by tuning embeddings and retrieval parameters. Contributed to content-safety practices with safe prompt structures and refusal handling; designed modular prompt and agent-style workflows for tool calling and multi-step reasoning. Maintained data ingestion pipelines for structured/unstructured sources and collaborated on cloud deployment, monitoring, and CI/CD for GenAI experiments. Iterated prompts based on feedback, logs, and error a

Prompt Engineer at Scale AI

June 1, 2023 - October 1, 2024

Designed and refined prompt templates (few-shot, role-based, chain-of-thought) for evaluating multiple model families. Built Python-based scripts for synthetic data generation, test-case creation, and automated prompt evaluation. Participated in adversarial testing and red-teaming to surface safety and instruction-following weaknesses; tested prompt injection/jailbreak patterns under established guidelines. Defined expected output formats, maintained prompt versioning, and tracked results to analyze performance trends. Assisted RAG experiments by tuning embeddings and retrieval parameters, and supported lightweight internal APIs for running evaluations and aggregating results. Worked with data annotation, safety, and ML Ops teams to improve prompt quality and evaluation coverage for large-scale testing.

NLP - AI Platform Engineer at Accenture

June 1, 2019 - August 1, 2021

Developed NLU solutions for enterprise chatbots using Microsoft LUIS and Python, implementing intent classification, entity extraction, and multilingual support. Built dialogue flows with Power Virtual Agents and integrated REST APIs to fetch dynamic content. Created reusable text preprocessing components and supported annotation/training workflows; performed model evaluation using standard NLP metrics and iterated to reduce misclassification. Supported deployment and monitoring of NLP services in Azure Functions with CI/CD pipelines for reliability under high traffic.