Siva Datta Koneru

I’m a Senior AI & Full Stack Engineer with 9+ years of experience building enterprise systems at Bloomberg and Upland Software. I specialize in architecting production LLM applications, RAG pipelines, and high-throughput microservices that teams can trust in real operations.

At Upland Software, I built an enterprise RAG pipeline and AI content-curation system using Azure OpenAI and semantic vector search, scaling to 11,000+ users. I optimized LLM inference and API utilization across LangChain and vLLM to reduce latency by 20% and cut AI operational costs by 35% through token caching and batch processing. I also improved generative output quality and content creation efficiency by 60% with dynamic prompts, retrieval tuning, and optimized context windows.

I’ve led engineering teams to modernize platforms and raise reliability standards. I led a 5-engineer team to modernize legacy systems into scalable React SPAs and .NET microservices, automating CI/CD to reduce operational overhead by 30%. I mentored engineers and established strong observability with New Relic, cutting incident detection time by 30% and supporting two internal team promotions within 18 months.

Earlier at Bloomberg, I designed and scaled Fixed Income analytics aggregation systems with Apache Druid and Elasticsearch, processing 100 million records/day while reducing data processing time by 60% using Splunk and Grafana. I also migrated legacy UNIX systems to Linux and implemented Jenkins CI/CD. In my recent contract role at GoodNotes, I triaged 100+ production defects and built AI-powered engineering workflows integrating Jira, Slack, and Notion MCPs.