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Vijaya Karthik

@vijayakarthik

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I build production multimodal RAG platforms with agentic AI, guardrails, and MLOps.

India

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What I'm looking for

I'm looking to build production-grade generative AI systems where retrieval quality, agentic workflows, safety guardrails, evaluation, and reliable MLOps are treated as core product requirements.

I built and shipped MAGIK, a production multimodal agentic RAG knowledge assistant for finance on AWS. It combines seven isolated ingestion pipelines, hybrid Qdrant retrieval, cross-encoder reranking, MMR diversification, and self-hosted open-weight LLM inference.

I designed agentic routing for RAG, web, hybrid, and finance-tool queries, with a 0.917 routing regression floor. I also added evidence-grounded answer verification, achieving 0.94 grounding success and 0.86 citation accuracy.

I treat safety and reproducibility as product requirements: MAGIK includes guardrails across 28 pipeline surfaces, tenant isolation, CI-gated evaluation, and 2,265 automated tests. I deployed it through 43 tagged releases with AWS, Docker, Terraform, GitHub Actions, MLflow, Prometheus, Grafana, and OpenTelemetry.

Experience

Work history, roles, and key accomplishments

Generative AI Engineer

Self-Directed Practice

Jun 2025 - Aug 2026 (1 year 2 months)

Delivered MAGIK to production in under six months across 43 tagged releases, with trunk-based Git workflow and CI gates. Built a full-time foundation in mathematics, Python, machine learning, deep learning, transformer architectures, NLP, MLOps and Responsible AI.