.png){kind=logo}
Ragamalika Karumuri
Mid-level AI Engineer specializing in LLM apps, RAG pipelines, and multi-agent systems
Connect with Ragamalika
Ragamalika already has a relationship with Reval, so a warm intro from us gets a much better response than cold outreach.
Recommended
Already have an account?
About
AI Engineer at Humanitarian AI who has built and productionized both a LangGraph-based multi-agent workflow system and a RAG pipeline (OpenAI embeddings + vector DB) with rigorous evaluation/guardrails. Reports strong measurable impact (60% faster workflow delivery, 40% fewer incidents, 70% reduced research time) and has prior enterprise modernization experience at Infosys migrating ETL to microservices with zero production incidents.
Find your next great hire
Our AI agents source, screen, and vet candidates for your open roles. Get qualified candidates within 48 hours.
Key Strengths
- Built and shipped an end-to-end LangGraph multi-agent workflow system (frontend, backend, data, infra) to production in <6 weeks
- Delivered measurable ops impact: ~60% faster workflow delivery and ~40% fewer production incidents
- Productionized RAG with OpenAI embeddings + vector DB; improved research time ~70% with source-accurate answers
- Strong evaluation/guardrails mindset (accuracy/relevance/task completion scoring, faithfulness checks, latency testing, alerting) enabling shipping without human-in-the-loop review
- Legacy modernization leadership: refactored ETL into microservices via parallel runs, feature flags, incremental cutover with zero production incidents
- Effective stakeholder translation (vague CPO goal to prioritized roadmap; shipped smaller MVP first, iterated from user feedback)
- High-autonomy execution across parallel projects with minimal oversight; timeboxed work and shipped working code quickly
- Productionizes LLM prototypes with modular stages, standardized schemas, and monitoring
- Improves reliability via soft validation, retries, and fallback prompts to handle real-world inputs
- Uses measurable SLO-style thresholds (latency, accuracy, failure rates) to ensure quality
- Systematic real-time debugging using logs/traces/metrics and reproduction with real inputs
- Collaborates transparently with customers to validate fixes quickly and build trust
- Delivers effective developer workshops (hands-on RAG agent to production workflow progression)
- Supports deal closure and adoption by building tailored PoCs and live demos addressing reliability/scalability concerns
Like what you see? We'll introduce you to Ragamalika directly.
Experience
Education
Skills
Languages
Certifications
Browse Similar
Interested in Ragamalika?
We'll personally introduce you - no strings attached.
Build your dream team with Reval
Our AI agents source, screen, and vet candidates for your open roles. Get qualified, high-intent candidates on your desk within 48 hours.
Discover more candidates like Ragamalika
Search across thousands of pre-screened, high-quality, high-intent candidates on Reval.
Search Talent