---
title: "Nikhil Ranjan - Technical Program Manager in Greater Bengaluru Area | Tal"
description: "Meet Nikhil Ranjan, GenAI & AI-Platform Leader | Agentic Workflows, RAG, LLM Evaluation & MLOps at Scale | Technical Program Manager @ Reliance Intelligence | Ex-EXL (Media Vertical), Optum | Databricks Certified | IIT-KGP · IIM-L based in Greater Bengaluru Area. AI stack includes aistudio, anthrop..."
image: "https://tal.club/meet/nikhil-ranjan-1/share-image"
---

# Nikhil Ranjan on Tal

## Headline

GenAI & AI\-Platform Leader \| Agentic Workflows, RAG, LLM Evaluation & MLOps at Scale \| Technical Program Manager @ Reliance Intelligence \| Ex\-EXL \(Media Vertical\), Optum \| Databricks Certified \| IIT\-KGP · IIM\-L

## About

I build production GenAI systems — and the platforms and teams that keep them running\. Over 9\+ years across media, telecom, and healthcare, I've worked at the intersection of applied AI, data\-platform engineering, and program leadership: taking AI from slide\-deck pilots to monitored, production\-grade systems with measurable business outcomes\. Today, as a Technical Program Manager at Reliance Intelligence \(Consumer Intelligence\), I'm helping build an AI\-powered consumer product — agentic orchestration, memory & personalization, and voice/multimodal experiences — coordinating data, personalization, and product\-metrics workstreams across a dozen\-plus delivery pods\. Before that, at EXL, I led the AI engagement for a major US OTT streaming account, where I designed and led an enterprise Agentic AI Data Quality Platform — multi\-agent workflows and RAG pipelines \(BigQuery VectorStore \+ Vertex AI embeddings, semantic retrieval, RAGAS evaluation\) that autonomously detect anomalies and cut ticket\-resolution time by \~50%\. I also ran rigorous LLM evaluations \(text\-to\-SQL benchmarking across GPT\-4, Gemini, Llama 3 and specialized SQL models\) and scaled the MLOps backbone — 300\+ Airflow DAGs on GKE moving 1TB\+/day, 15\+ production ML models on Vertex AI\. What I focus on: • GenAI agents, LLM orchestration, RAG & retrieval\-based QA, agentic workflows • LLM evaluation & LLMOps \(benchmarking, RAGAS, prompt versioning, multi\-model routing\) • Scalable ML & data platforms \(Vertex AI, Airflow, GKE, Databricks, Spark, BigQuery, Snowflake\) • "Pilot → production" AI transformation and MLOps at scale • Technical program leadership, stakeholder governance, and team building I bring an engineer's depth \(IIT Kharagpur\) with a strategist's lens \(IIM Lucknow\) — Databricks Certified ML Associate — to turn complex AI ambitions into durable, working systems\.

## Location

Greater Bengaluru Area

## AI stack

aistudio

anthropic apis

claude code

claude

codex

deepseek

## Work experience

Technical Program Manager at Reliance Intelligence, Mar 2026 \- Aug 2026 · 5 mo, Bengaluru, Technical Program Manager in the Consumer Intelligence org, helping build an AI\-powered consumer application spanning agentic orchestration, memory & personalization, and voice/multimodal experiences\. Own data, personalization, and product\-metrics workstreams across a dozen\-plus delivery pods\. • Co\-designed a Personalization Engine on an enterprise customer\-profile platform — a layered architecture \(signal ingestion → profile enrichment → candidate generation → low\-latency serving → feedback loop\) built for sub\-200ms serving\. • Stood up the program's metrics & instrumentation framework, with full lineage from each metric back to its source event — making product dashboards trustworthy and traceable\. • Designing an Agentic SDLC — an agent\-driven program\-management layer \(bug\-tracing, spec\-compliance, release\-readiness, and status\-rollup agents\) to automate routine engineering workflow\. • Authored the cross\-cloud integration architecture connecting the app to an enterprise customer\-profile platform, defining data planes, latency SLOs, and the authentication stack\. • Drive delivery governance, release management \(dev→SIT→prod\), and third\-party AI/observability vendor evaluation across the program\.

Engagement Manager at EXL, Feb 2024 \- Jan 2026 · 2 yrs, Bengaluru, Engagement Manager leading GenAI innovation and delivery for a major US OTT streaming account\. GenAI Architecture & Builder Leadership: Designed and led end\-to\-end development of an enterprise\-grade Agentic AI Data Quality Platform — multi\-agent workflows \(QA, SQL, ticketing, incident, monitor\) and RAG pipelines \(BigQuery VectorStore \+ Vertex AI embeddings, semantic chunking, MMR & conversation\-aware retrieval, RAGAS evaluation\) — enabling autonomous anomaly detection and reducing ticket resolution time by 50%\. LLM Evaluation & Conversational BI: Built a natural\-language\-to\-SQL\-to\-visualization BI system and ran a rigorous text\-to\-SQL benchmark across 200 questions on a novel schema, evaluating GPT\-4, Gemini, Llama 3, Mistral, and specialized SQL models to select the production model\. Commercial Strategy & Account Growth: Owned business\-case creation and ROI modeling to secure internal investment — pitching a $500K R&D initiative for GenAI adoption that drove vertical expansion and a 30% revenue uplift within 9 months; secured two new verticals contributing \~20% further uplift\. Executive Stakeholder Management: Managed C\-Suite and VP relationships via quarterly SteerCos and data\-driven QBRs, translating technical constraints into value narratives, achieving 95%\+ CSAT and securing renewals\. Program Governance & Risk Management: Orchestrated 5\+ concurrent global workstreams with RAID logs, quality gates, and release planning, sustaining consistent on\-time delivery across distributed regions\. Platform Engineering: Directed the Clean Room migration from BigQuery to Snowflake \(Snowpipe\-based ELT, privacy governance\) for secure, compliant integration of 1st\- and 3rd\-party data\.

Project Manager at EXL, Jan 2022 \- Feb 2024 · 2 yrs 2 mos, Bangalore Urban, MLOps Strategy & Pilot\-to\-Production Scaling: Defined and enforced the ML SDLC and built a reusable pilot\-to\-production framework; steered the lifecycle of 15\+ production models \(CLV, Reactivation, Habituation, Churn\) on Vertex AI and MLflow with champion\-challenger retraining and data\-drift monitoring \(KS, PSI\), improving campaign/engagement metrics by 20%\. Data Platform Engineering: Architected multi\-tenant Airflow on GKE across 300\+ DAGs processing 1TB\+/day \(Kubernetes Executor, SSO, Helm, DAG\-level permissions\), improving SLA adherence to 90% and platform reliability to 95%\+ while reducing operational overhead by 30%\. ML Data Quality Framework: Built a cloud\-agnostic framework across six data\-quality dimensions, monitoring 200\+ tables with 2,000\+ daily automated checks and 100\+ ML models \(Isolation Forest \+ SHAP, Prophet, SynapseML\)\. Org Building & People Leadership: Led a 14\-member cross\-functional team \(Data Engineering, MLE, Full\-Stack\) with competency matrices, structured onboarding, and career coaching — achieving 95% retention and a 30% reduction in hiring cycle time\. Security & Automation: Engineered a self\-service IAM provisioning system \(Python/FastAPI\) with a LangChain natural\-language\-to\-SQL layer, automating access workflows across GCP/AWS and reducing turnaround time by 40%\.

Assistant Project Manager at EXL, Jun 2020 \- Jan 2022 · 1 yr 8 mos, Bengaluru, Pipeline Modernization & Cloud Transformation: Orchestrated the migration of legacy on\-premise ETL workflows to a cloud\-native stack \(GCP \+ Airflow on Kubernetes\), optimizing DAG performance to reduce data latency by 25% with zero downtime\. Streaming Data Engineering: Built streaming pipelines \(Apache Beam/Dataflow, Pub/Sub, BigQuery, Bigtable\) moving data from the source platform to a CDP and downstream activation systems\. Operational Excellence: Developed Python\-based monitoring frameworks providing real\-time pipeline\-health visibility, ensuring a 95%\+ job success rate\. Stakeholder Enablement: Translated complex data insights into actionable recommendations for senior leadership, contributing to a 10% improvement in productivity\.

Program Manager Intern at Amazon, Apr 2019 \- May 2019 · 2 mos, Hyderabad Area, India, Program Manager Intern in Operations / Transportation Analytics, optimizing packaging and unloading efficiency across Amazon India's transportation network\. Network Analytics: Analyzed 37\.1M\+ packages to identify Bagging Potential Fluids using a 3\-flag classification algorithm \(volume, dimension, weight\) combined with box\-barcode logic\. Impact Quantification: Established a strong positive correlation \(R² = 0\.85 across 500 delivery stations\) between fluid ratio and average unload time, and derived per\-package unload times \(bag 0\.91s vs fluid 4\.07s\) to quantify \~1,100 hours/week of unloading\-time savings, plus a network\-wide reduction in package damage\. Data Quality: Extracted and cleaned data from the India transportation database, reducing a 3% data\-inconsistency rate to under 1% by cross\-referencing tables, validated at a 98% confidence interval\. Dashboarding & Rollout: Built an automated daily dashboard \(day\-on\-day fluid view, top\-5 defaulting origin nodes\) for pan\-India Ops rollout, driving action items with Ops and ACES leadership — node audits, revised bagging guidelines, and associate training\.

Software Engineer at UnitedHealth Group, Jul 2015 \- May 2018 · 2 yrs 11 mos, Bengaluru Area, India, Big Data Engineering: Migrated legacy MapReduce systems to an optimized Spark/Scala stack, improving performance by 500%; designed Spark\-Scala algorithms for unstructured healthcare data, enhancing usability by 35%\. Data Platform & ETL: Engineered the data\-acquisition \(ETL\) layer pulling pharmacy and claims data from 9 source systems into a Hadoop data platform; built the ingestion pipeline \(inbound landing → workflow orchestration → raw zone → Avro conversion → curated store\) and the Hive processing and publication jobs exposed via JDBC for downstream analytics\. Process Transformation & Automation: Delivered real\-time reporting applications, reducing manual effort by 60% and improving SLA compliance to 90%; analyzed 100GB\+ weekly HIPAA/PHI\-regulated healthcare datasets, improving on\-time SLA adherence by 15% YoY\. Storage Optimization: Developed compression and columnar storage solutions \(Avro, ORC, Parquet\), cutting storage costs by 20% and accelerating query performance\. Stack: Hadoop, HDFS, Hive \(HQL, partitioning, SerDes\), MapReduce, Spark, Scala, YARN, Sqoop, Java, SQL, Bash\. Fast\-track promotion within 8 months\.

Summer Intern at Bhabha Atomic Research Centre, May 2013 \- Jul 2013 · 3 mos, Mumbai Area, India

## Education

Master of Business Administration \- MBA, Indian Institute of Management, Lucknow

Bachelor of Technology \(BTech\) \+ Master of Technology \(MTech\), Electrical, Electronics and Communications Engineering, Indian Institute of Technology, Kharagpur

## Public links

- github: https://github\.com/nikiit007

[View the original profile](https://tal.club/meet/nikhil-ranjan-1)

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