Headline

Working as a Al Engineer on production Al systems for enterprise clients.

About

I build GenAl systems that go to production - not just prototypes. Over the last 2+ years at Cognizant, I've moved from data engineering into full agentic Al development. Today I work on systems that process real customer requests, automate supply chain decisions, and connect LLMs to live enterprise data. What I've shipped: 1. Agentic Salesforce automation using Google ADK - live in production, handling real support tickets 2. Multi-agent supply chain assistant (CrewAl + Neo4j) cut reconciliation time from 3 hours to 25 minutes 3. RAG pipelines with dynamic prompt strategies for context-aware LLM responses I started in data engineering - pipelines, SQL, ETL - which means I understand the data layer that most Al engineers skip. That foundation makes a real difference when building reliable Al in production. Stack: Python GCP Google ADK CrewAI RAG LangChain Fast API Neo4j. Azure SQL Currently exploring roles at product and startup companies where I can own Al features end to end. Open to: Full-time | Hyderabad / Remote

Location

Hyderabad

Work experience

Associate at Cognizant, Sep 2024 - Present · 1 yr 9 mos, Al-Powered Salesforce Automation 1. Built an agentic Al system using Google ADK integrated with Salesforce APIs to auto-classify, prioritize, and resolve customer support tickets - currently live in production. 2. Designed RAG pipelines and dynamic prompt strategies for real-time, context-aware responses. 3. Reduced manual effort in ticket resolution and improved accuracy through automated verification. GenAl Supply Chain Optimization 1. Built a multi-agent system using CrewAl and Neo4j for demand forecasting and purchase order automation. 2. Led a 4-member cross-functional team to integrate Al outputs into ERP systems. 3. Reduced reconciliation time from 1 hours to 25 minutes.

Program Analyst Trainee at Cognizant, Sep 2023 - Sep 2024 · 1 yr 1 mo, Built data infrastructure that now underpins production Al systems. 1. Developed ETL pipelines and data transformation logic across internal projects. 2. Processed and analyzed large datasets using SQL and Python, improving reporting access efficiency. 3. Implemented validation checks that improved data accuracy and reduced downstream errors. 4. Built scalable data warehousing solutions on Azure Synapse, Microsoft Fabric, and Power BI Stack: Python SQL Azure Synapse Microsoft Fabric Power BI

Intern at Cognizant, Mar 2023 - Jun 2023 · 4 mos, Hyderabad, Telangana, India, 1. Built and optimized ETL pipelines using IBM DataStage, reducing manual effort and latency. 2. Wrote SQL scripts to ensure data integrity and quality across platforms. 3. Developed automation scripts in Python for data extraction and transformation tasks. 4. Participated in team discussions on improving data integration workflows.

Education

Bachelor of Technology - BTech, Anurag group of institutions