Nagesh Muniraja

Product Manager

Bengaluru, Karnataka, India7 yrs 6 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

9+ years of experience in AI solutions.
Expertise in Generative AI and LLMOps.
Proven track record in building scalable data pipelines.

Stackforce AI infers this person is a Senior AI Engineer specializing in Generative AI and Data Engineering for Healthcare and Finance.

Contact

nagesh.muniraja@alegeus.com +919483725114 LinkedIn

Skills

Core Skills

Data EngineeringGenerative AiCloud Services

Other Skills

AWS GlueAWS LambdaAWS SageMakerAirflowAmazon AthenaAmazon Web Services (AWS)Apache KafkaApache SparkApache Spark StreamingAzure DatabricksBig Data AnalyticsDatabricksDeep LearningDelta LakeHadoop

About

I'm a Senior AI Engineer with 9+ years of experience building intelligent, production-grade AI solutions across healthcare, finance, and enterprise automation. My core focus lies in Generative AI, Agentic AI, and LLMOps, where I design and deploy advanced applications using cutting-edge tools like OpenAI GPT, LangChain, Hugging Face, and Azure OpenAI Studio. With hands-on experience in building autonomous AI agents, LLM-powered search systems, and dynamic report generation, I specialize in delivering scalable end-to-end AI products—from data pipelines to intelligent user interfaces. My recent work includes developing a GenAI platform for a major healthcare client, where I architected agentic workflows, secure role-based dashboards, and real-time analytics pipelines leveraging Snowflake, Power BI, and multi-cloud infrastructures (AWS & Azure). I am also deeply involved in MLOps and LLMOps practices, focusing on model fine-tuning, evaluation, versioning, and monitoring using tools like MLflow, Airflow, and CI/CD pipelines. My strength lies in blending cloud-native architectures with intelligent orchestration to solve complex business challenges through automation and conversational AI. 💡 I’m passionate about pushing the boundaries of applied AI—whether it's automating decision-making, improving human-AI collaboration, or enabling self-directed agentic workflows. Let’s connect if you’re building in the future of AI-first products, LLM-powered systems, or enterprise-grade GenAI platforms.

Experience

Alegeus

Senior Engineer ll

Mar 2023 – Present · 3 yrs · Bengaluru, Karnataka, India · Hybrid

I am leveraging cutting-edge technologies like Databricks, Delta Lake, and Snowflake to build high-performance data pipelines that power real-time insights and drive business decisions. My work involves crafting scalable, efficient solutions that integrate seamlessly with advanced data platforms, ensuring seamless data flow and availability for analysis.
Key contributions include:
Building Scalable Pipelines: Architecting and developing data pipelines using Databricks and Delta Lake to handle large-scale data transformation, ensuring reliability and efficiency in processing.
Complex Data Transformations: Applying advanced data transformations to curate and prepare datasets for analysis, enabling the creation of powerful business intelligence dashboards.
Snowflake Integration: Integrating Snowflake as a central data warehouse, optimizing storage and query performance for fast data retrieval and reporting.
Generative AI Integration: Exploring and applying Generative AI technologies to enhance data processing workflows, improve decision-making, and drive innovative AI-powered analytics.
Dashboard Development: Working closely with business teams to design and build dynamic, user-friendly dashboards that provide actionable insights across various departments.
With a focus on leveraging both traditional and AI-driven technologies, I strive to push the boundaries of data engineering, enabling more intelligent, automated, and scalable solutions for the organization.

DatabricksDelta LakeSnowflakeGenerative AIData Engineering

Kpi partners

Senior Data Engineer II

Jul 2021 – Mar 2023 · 1 yr 8 mos · Remote

I played a key role in building robust data pipelines for Rivian Automobile, utilizing advanced technologies such as PySpark, Python, and AWS cloud services. I was responsible for designing and implementing end-to-end data processing solutions that supported data-driven insights for the organization.
Key contributions include:
Building Data Pipelines: Developed and optimized scalable data pipelines using AWS Glue to process and transform large datasets.
Spark SQL Transformations: Wrote and optimized Spark SQL queries for complex data transformations, enabling efficient data processing at scale.
Airflow DAGs: Created and managed Airflow Directed Acyclic Graphs (DAGs) to automate and schedule data pipeline executions, ensuring reliable and timely delivery of data.
AWS Services Integration: Leveraged a variety of AWS services (such as AWS S3, AWS Lambda, and AWS Glue) to streamline data workflows and enhance scalability and performance.

PySparkPythonAWS GlueAirflowData EngineeringCloud Services