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About

8+ years of shipping systems that other people depend on

Applied AI Engineer with 8+ years building production ML and large-scale distributed data systems. Ships agentic LLM applications end to end — multi-agent orchestration on LangGraph, RAG grounded in knowledge graphs, human-in-the-loop guardrails, and evaluation harnesses — on top of AWS streaming and batch pipelines processing 10M+ records daily. Research background in neural information retrieval and dense ranking.

Experience

  1. Apple

    Oct 2025Present

    Applied AI Engineer

    Bangalore, India

    • Architected a production applied-AI SRE platform running autonomous incident investigation on LangGraph-orchestrated multi-agent workflows — stateful graphs with explicit tool nodes, checkpointing, and retry semantics — scaling automated RCA across 10k+ daily alerts and driving a 30% reduction in MTTR.
    • Built the RAG retrieval layer over a domain-specific knowledge graph, runbooks, prior postmortems, and live telemetry, with persistent long-term memory across incidents, so every generated root cause is grounded in cited evidence rather than inferred.
    • Shipped human-in-the-loop approval gates and guardrails on all consequential remediation actions, capturing engineer accept/reject decisions as labeled evaluation signal to measure agent precision, robustness, and business impact over time.
    • Led backend development of the execution engine, integrating real-time telemetry pipelines with graph-driven automated remediation workflows in Python on AWS.
    LangGraphPythonRAGKnowledge GraphsAWS
    Read the case study
  2. Block Scholes

    Sep 2024Sep 2025

    Senior Software Engineer

    London, Remote

    • Architected a high-throughput streaming and batch pipeline on AWS Kinesis and S3 processing 10M+ daily records, with end-to-end monitoring, logging, and metrics.
    • Cut storage costs 40% via PySpark Parquet compaction and partition tuning, while raising test coverage by 30% to harden the pipeline for production.
    AWS KinesisS3PySparkParquetAthena
    Read the case study
  3. TikTok Live (ByteDance)

    Dec 2022Dec 2023

    Senior Software Engineer

    Singapore

    • Led backend development of creator observability pipelines, serving real-time analytics dashboards at 350K+ QPS.
    • Architected an Anti-Money Laundering (AML) surveillance system applying risk-detection models over streaming behavioral signals to monitor 7M+ live rooms daily.
    • Migrated core storage to a Redis architecture, reducing read latency 65% for high-concurrency queries.
    GoKafkaRedisRisk ModelsStreaming
    Read the case study
  4. Goldman Sachs

    Jan 2018Nov 2022

    Associate / SDE-II (L4)

    Bangalore, India

    • Led an observability platform indexing 11M+ queries/day across Elasticsearch, powering firmwide search and alerting.
    • Built fault-tolerant AWS microservices and a batch orchestration layer governing 10k+ scheduled jobs, reducing production incidents to near zero.
    JavaElasticsearchAWSSpring BootKibana
    Read the case study

Research

Automatic Information Retrieval for Short Documents

IIIT Hyderabad · advisor Dr. Vikram Pudi · May 2016 Aug 2018

  • Built an NLP-based information retrieval system achieving 31% screening time saved at 100% recall across 117K+ PubMed documents.
  • Developed NITBUG, a BERT-based dense retrieval model using triplet learning and inter-document context, achieving 10–15% higher recall and 61–65% Recall@1 across Mozilla, Eclipse, and NetBeans corpora.
Read the case study

Education

  • M.S. by Research, Computer Science and Engineering

    International Institute of Information Technology, Hyderabad

    Aug 2016Apr 2018 · GPA 8.6/10.0

  • B.Tech (Honours), Computer Science and Engineering

    International Institute of Information Technology, Hyderabad

    Aug 2012Apr 2016 · GPA 8.6/10.0

Achievements

  • 3rd place, Google Cloud Developer Challenge (South Asia)
  • Rank 15, Google APAC 2017
  • ACM-ICPC Asia Regionalist
  • Dean's Merit List (Top 5%), IIIT Hyderabad

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