AS

Akaash Nidhiss Shanmugapandian

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Lead AI Platform Engineer focused on building repeatable internal systems for consulting delivery. I ship workflow and agent platforms that improve throughput, reduce turnaround time, and create reusable artifacts teams can trust engagement after engagement.

Work Experience

Lead AI Engineer, Core AI Innovation Team

KEARNEY (FORMERLY A.T. KEARNEY CONSULTING)

Gurugram, India

03/2023 - Present

  • Architected an Agents-as-a-Service platform so teams could query structured and unstructured knowledge for supplier discovery, peer benchmarking, and market intelligence.
  • Scaled search across 1.5M+ suppliers and 200+ peer companies with dockerized workers on Azure serverless compute and centralized PostgreSQL telemetry state.
  • Implemented Agentic RAG over the Databricks lake using tree-search retrieval to improve extraction quality from sparse supplier and procurement records.
  • Designed orchestrator plus specialist sub-agent execution for parallel low-latency runs, supporting 50+ daily active users across 10+ internal projects.
  • Built and scaled AI Workflows-as-a-Service so project teams could run repeatable AI pipelines for data cleanup and procurement insights.
  • Enabled procurement teams to build high-fidelity spend visibility in hours across multi-year spend data from 10,000+ suppliers.
  • Built event-driven execution with capacity-aware Databricks scheduling, low-latency job state updates, and deterministic plus LLM-as-judge quality checks.
  • Delivered spend categorization and supplier/SKU harmonization pipelines used across telecom, retail, machinery, logistics, and banking sectors.
  • Drove roughly 8x throughput and about 90% faster turnaround on core procurement deliverables across platform-enabled engagements.
  • Prototyped a multimodal operational agent for a USD 200B+ retailer and shaped client-facing AI value narratives tied to process redesign.
  • Defined product vision, led biweekly demos for Partners/CXOs, authored decision memos and roadmaps, and mentored junior engineers.

Machine Learning Engineering Intern

ABB GROUP

Bengaluru, India

06/2023 - 08/2023

  • Built an LSTM model for predictive maintenance in an IoT-powered plant and reached high breakdown-prediction quality with controlled false flags.
  • Reduced populated sensor clusters from 52 to 2 through clustering, correlation analysis, and feature engineering.
  • Worked on anomaly detection, pattern detection, IoT data cleaning, and exploratory analysis workflows.

Business Development Intern

ENTELYST

Doha, Qatar

12/2020 - 01/2021

  • Facilitated workshops and developed GTM presentations for Entelyst cybersecurity offerings aimed at company leaders and C-level executives.

Education

Bachelor of Technology - Information Technology

Delhi Technological University

New Delhi, India

08/2019 - 05/2023

  • 7.80/10.0

CBSE - Class XII

DPS Modern Indian School, Doha

Doha, Qatar

2018 - 2019

  • 79.4%

Skills

Agentic AI SystemsLangGraphLangChainDurable ToolingRAGMCPAzure ACA / Blob / FunctionsDatabricks SparkSQLVector DBsFAISSChromaDBPythonAsync orchestrationAPIsDistributed pipelinesExperiment designUser researchROI framingClusteringCorrelation analysisFeature engineeringAnomaly detectionPattern detectionIoT sensor dataData cleaningEDALeadershipTeam mentorshipProduct visionExperimentation strategyDecision memosRoadmaps

Languages

English