Headline

Agentic AI Architect | Senior AI Engineer | AI Security | Multi-Agent Systems · RAG · MCP · LLMOps | IBM

About

I design and build enterprise Agentic AI platforms — multi-agent systems that combine LLM reasoning, RAG, tool calling, MCP, evaluation, and production-grade AI security. At IBM, I lead the architecture and delivery of Agentic AI solutions across security automation and enterprise workflows, working with a team of engineers to take systems from architecture through production deployment. What I’ve built Enterprise Agentic AI Platform: Built and deployed MCP servers exposing enterprise APIs as governed tools, integrated through ContextForge with watsonx Orchestrate. Designed reusable multi-agent workflows using RAG and tool/function calling across fact validation, motor insurance claims, and banking payment exceptions. AI Security Platform: Architected an end-to-end multi-agent platform spanning Architecture Review, Threat Modeling, AppSec/Code Review, and Privacy Impact Assessment. Architecture Analysis: Converts PRDs/LLDs into context graphs, generates attack paths, and performs security analysis using hybrid deterministic + LLM reasoning — resolving ~30–40% of architecture gaps without LLM calls. Threat Modeling: Maps architecture risks to STRIDE and MITRE ATT&CK, combining knowledge-driven threat reasoning with product-specific attack scenarios. AppSec: Correlates application and code context with security knowledge to generate actionable findings while using persistent memory to reduce repeated noise and false positives by ~40%. AI Security & Guardrails: Designed layered controls for prompt injection, jailbreaks, tool-use boundaries, policy enforcement, schema validation, auditability, and validator/judge-agent based output governance. SOC Automation — IBM ATOM: Built specialist agents for IOC extraction, IP/domain reputation, hash validation, investigation, and summarisation. Added LLM evaluation for faithfulness/relevance and OpenTelemetry/Grafana-based observability. Conversational Analytics — GenBI: Built an NL-to-SQL assistant using CodeLlama, Granite, and Milvus, enabling analysts to query enterprise data using natural language. Technology LangGraph · LangChain · MCP · ContextForge · RAG · watsonx Orchestrate · GPT-4o · Granite · Mistral · Milvus · FAISS · FastAPI · Docker · OpenShift · Kubernetes · OpenTelemetry · Grafana · MITRE ATT&CK · STRIDE · OWASP 12+ years across AI/ML, NLP, Generative AI, and enterprise AI engineering, with additional specialization in AI security architecture. Interested in Senior AI Engineer, Agentic AI Architect, AI Solution Architect, and AI Security Architect opportunities.

Location

Bengaluru

AI stack

cursor

hugging face

langchain

langgraph

openai

ChatGPT

Work experience

Sr.Data Scientist at IBM, May 2024 - Present · 2 yrs 5 mos, Bangalore Urban, Karnataka, India, At IBM, I design and build enterprise Agentic AI systems using LLMs, multi-agent orchestration, RAG, and tool calling to automate complex security and business workflows. My work spans AI security architecture, threat modeling using STRIDE and MITRE ATT&CK, LLM guardrails, and SOC automation, including specialist agents for IOC extraction, IP/domain validation, threat enrichment, and investigation summarization. I also architect reusable agentic platforms using LangGraph, LangChain, MCP, watsonx Orchestrate, and OpenShift, extending the same architecture beyond cybersecurity into enterprise workflow automation.

Senior Data Scientist at Cognizant, Feb 2022 - Jun 2024 · 2 yrs 5 mos, Delivered Vertex AI / Gemini / Mistral solutions for an AI marketplace (Google client), including a RAG assistant that improved discovery of internal tools and reduced manual search effort.

Sr.associate at Cognizant, Feb 2022 - May 2024 · 2 yrs 4 mos, Bangalore, Sr. Associate — Data Scientist Cognizant · Full-time | Feb 2022 – May 2024 | Bengaluru - Delivered Vertex AI / Gemini / Mistral solutions for an AI marketplace (Google client) — RAG assistant that improved internal tool discovery and reduced manual search effort - Built AI360 Insights Hub for media sentiment analysis and CV-to-job matching - Developed BERT-based SLA root-cause classifier — ~80% F1 score - Automated HR and payroll workflows using Flask, Snowflake, Azure, CI/CD

Senior Data Analyst at Accenture, Jun 2019 - Feb 2022 · 2 yrs 9 mos, Built NLP and clustering pipelines for survey data modelling using TF-IDF, K-means and LSTM/GloVe, improving call-centre insight generation.

Data Scientist at Accenture, May 2019 - Feb 2022 · 2 yrs 10 mos, bangalore

Machine Learning Engineer at SPi Global, Oct 2018 - May 2019 · 8 mos, Chennai Area, India, Built Doc2Vec-based research-paper classification workflows to improve automated categorisation and document discovery.

Data Scientist at PayZello, Jan 2017 - Oct 2018 · 1 yr 10 mos, Hyderabad Area, India, My work here involves structure user data ,organise them according to the requirement of the project . For extracting raw data we use mongo db query , python(pandas,numpy) is vastly used for data munging manipulation in data frames , dictionaries and lists objects . We vastly use Elastic Search for storing analysed data , for fast query and analysis. I was involved in developing dashboards using R-shiny and plotly visualisation . I was actively involve in developing web based reporting system in Flask and mongo db . Recently involve in developing chatbot for our organisation , in which applying NLP and machine learning models like naive Bayes , random Forest , logistic regression , deep learning models like word2vec and doc2vec models .

Data Scientist at Predictive research, Nov 2013 - Oct 2016 · 2 y 11 mo, Bangalore

Education

Btech in Information Technology., Information Technology, GIET University Gunupur

Bachelor of Technology, Information Technology, Gandhi Institute of Management & Technology