Aravindhan Mani
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M:- Woodvale St, Clermont, FL 34711
https://www.linkedin.com/in/aravindhanmani
PROFESSIONAL SUMMARY
Technical leader with 20+ years of experience in Data Engineering + AI / ML, driving innovation in
enterprise-scale data platforms in banking, automotive autonomous systems and Aerospace. Proven expertise
in leading cross-functional teams, architecting patented AI solutions, and delivering high-performance systems
for Fortune 500 clients (US Bank, GM, ZF, Boeing). Combines hands-on technical mastery (Python, Spark, GCP,
Azure, Java, C++) with strategic leadership to align AI initiatives with business outcomes.
PROFESSIONAL SYNOPSIS
Technical Leadership & AI/ML Expertise
● 20+ years leading full software/system lifecycle (research to deployment) and cross-functional technical
teams (onshore/offshore), driving innovation in AI/ML, data engineering, and autonomous systems across
Banking, Automotive, and Aerospace domains.
● 5+ years proficient in architecting and ramping ELT/ETL platforms and data models to empower robust
business intelligence and analytics hosted in GCP and Azure environments leveraging Python, Spark,
Java/Spring, BigQuery, Kafka, GCP PubSub, and Airflow significantly enhancing pipeline workflows, strategic
AI/ML implementation aligned with business goals, specializing in GenAI environments, NLP, LLM,
reinforcement learning, and scaling AI-powered features with quality/cost tradeoffs
● 7+ years architected perception systems (Lidar/Radar) for traffic/pedestrian detection, with patented AI/ML
algorithms for map-building, sensor fusion and computer vision using Java, C++, Python predominantly.
● 8+ years extensive experience in leading teams and developing embedded software in the automotive and
aerospace industries, which includes developing CAN and diagnostic layers, battery system software, and
fan motor controller software, with a focus on C, C++, and embedded systems programming. Also led the
integration of various protocols, designed test software and automated test scripts, and ensured
compliance with industry standards
● Standardized CI/CD pipelines, containerization strategies, model deployment methodologies meeting
security/compliance requirements, performance-optimized code, feature engineering, and multi-stage
testing (unit/UAT/model validation/fault injection).
Leadership & Project management
● Guided a team of 25+ engineers based across 5 continents, focusing on meeting KPIs, maximizing
productivity and efficiency and nurturing a collaborative and continuously learning environment.
● Involved in both triumphs and failures, ability to turn minor setbacks into memorable learning experiences.
Strong team player, excellent communication, collaboration, and problem-solving skills with positive
attitude. Proven ability to manage projects effectively in a multidisciplinary team and deliver high-quality
solutions that improve scalability and performance.
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TECHNICAL SKILLS
Big Data & Cloud Platforms
● GCP (Vertex AI, BigQuery), GCP Pub/Sub, Azure, Airflow, Spark, PySpark, Databricks, Hadoop, Delta Lake,
Kafka, Hive
● Agile, Scrum, ETL/ELT Pipelines, Data governance, Medallion Architecture, Data Lakehouse Architecture
Software Engineering
● Code: Scala, Python, C, C++, Java, Rust, R, SQL, JavaScript, MATLAB, Bash, VB.NET, C#.NET
● Tools: Git, Jira, Confluence, SVN, CM Synergy, Protobuf, DOORS
● Visualization: Matplotlib, pyplot, plotly, Tableau/Power BI, Looker
● DB: Cassandra, PostgreSQL, MySQL, Oracle, Teradata, NoSQL, TigerGraph
AI/ML Tools & Frameworks
● Machine Learning: Scikit-learn, TensorFlow, PyTorch, Apache MLlib (Spark), Dlib, CUDA, XGBoost
● Deep Learning & NLP: BERT, Hugging Face Transformers, NLTK, LangChain, LangGraph
● GenAI & LLMs: Gemini AI Studio, Vertex AI, OpenAI GPT, RAG pipelines, Vector database
● MLOps: MLflow, Kubeflow, model monitoring (Evidently AI), feature stores (Feast)
● Computer Vision: OpenCV, YOLO, SLAM, Kalman filters, ROS (Robot Operating System)
Web & DevOps
● Backend: HTTP REST APIs, Spring Framework, Flask/Django, Json
● Frontend: HTML, CSS, JavaScript, React, Angular
● DevOps: Kubernetes, Docker, Jenkins, Terraform, GitHub Actions
● Testing: Pytest, Selenium, A/B testing, unit/integration testing
Embedded Systems & IoT
● Protocols: CAN, SPI, I2C, TCP/IP, UDP, Bluetooth, MQTT
● Tools: QNX RTOS, LabVIEW, ROS, GIS, AUTOSAR, DO-178B/C compliance
PATENTS
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Methods and systems for interpretating and negotiating traffic signals (11,205,343 · 2021)
Combining heterogeneous types of maps - · 2022)
Systems and methods for detecting traffic objects - · 2023)
System to derive an autonomous vehicle enabling drivable map - · 2020)
EDUCATION
● Bachelor of Engineering in Computer Science
● University of Madras, India | Sep 2000 - Apr 2004 | GPA: 3.3
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EXPERIENCE HIGHLIGHTS
Principal Data Engineer AI ML
TechGIRD | 06/2023-Present | Remote
Data Platform for Marketing Analytics - Client: US Bank
● Led/collaborated with a team of 10+ data engineers to design and implement a high-performance ELT platform
for marketing analytics using GCP, Azure, Java, SQL and Delta Lake, employing a medallion architecture to
process and analyze raw data from Salesforce and Marketo, including over 1M records of potential leads.
● Utilized Dataform and Delta Lake in GCP to transform denormalized data into Star schemas, enhancing a
scalable data mart at the gold layer for real-time analytics and historical comparisons for strategic insights.
● Key Acheivements: Leveraged ML models to predict customer behavior and lead conversion rates using
historical data along with reduced data ingestion to visualization time by 60%, enhancing operational reliability
and decision-making speed for marketing teams.
Scalable Spark-Based ETL Platform - Client: US Bank
● Spearheaded deployment of a versatile, Spark-based ETL platform with extensive configurability to address
diverse customer needs, utilizing GCP, Azure, Java, Cassandra, Kafka, GCP PubSub, SQL, BigQuery, Databricks,
ADLS, AFS, and file-based systems, with orchestration managed by Airflow.
● Implemented a data lakehouse architecture enhanced by Snowflake dimension modeling, enabling seamless
integration of various data sources and targets, and supporting the processing of millions of records daily with
high efficiency and scalability while adhering to data governance principles and compliance.
● Developed a GenAI chatbot on GCP using RAG with LLM chains and BERT for NLP. Integrated Jira/ServiceNow
tickets via Vertex AI, data in BigQuery/Cloud Storage & native vector db. This solution, powered by the Gemini
API, reduced production issue resolution time by 50% through automated analysis and recommendations.
● Achieved an 80% reduction in codebase size through automated configurations, significantly lowering
maintenance efforts, accelerating consumer onboarding by 70%, and simplifying pipeline management.
● Spearheaded agile and automated integrated testing procedures, CI/CD pipelines, re-architected configuration
parameters to enhance Spark application performance, and incorporated data and dimensional modeling
techniques, and optimized query performance
Research Software Engineer
Alten | 10/2015-06/2023 | Warren, MI
Autonomous research projects – Client: General Motors
● Spearheaded the development of autonomous driving systems, including collision avoidance algorithms and
HD map construction, by leading a team of 15+ engineers and researchers. Leveraged AI/ML, using GCP's
TensorFlow for model training and BigQuery ML for predictive analytics, alongside Lidar, Radar to enable cross
traffic detection and maneuvering, core algo in Java, C++ & Python. Utilized GCP Pub/Sub for real-time data
streaming from sensors to cloud for shared responsiveness of our autonomous systems.
● Researched and developed an systematized for building and smoothing maps for autonomous driving, using
multiple data sources. Designed application to merge map data collected from various vehicles in GCP,
employing a Snowflake schema for lane organization, efficient data storage and retrieval
● Designed and developed software systems to negotiate traffic signal phase association to lanes, predict and
infer sensed intersections using computer vision and machine learning algorithms. Incorporated Google's
AutoML for rapid model development and Cloud AI Platform for scalable model training and deployment.
● Established an environment to benchmark and evaluate performance measurement for different driving
behavioral (adversarial) agents under various traffic situations.
● Utilized geospatial libraries to integrate OpenStreetMap GIS layers with ROS for validating HD map
construction. Merged multi-vehicle LiDAR and camera data into unified lane-level maps.-
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Radar projects – Client: ZF
● Conducted advanced research on imminent crash prediction for ADAS (Advanced Driver Assistance Systems),
leveraging radar systems and a C++ development environment with extensive use of templates, STL data
structures, and multithreading for real-time performance optimization.
● Architected, developed, and debugged radar functions for object classification and relative behavior
integrating machine learning models using Java, C++
Senior software engineer
Capgemini | 07/2012-09/2015 | Milford, MI & India
Audio Head Unit (AHU) Infotainment - Client: Panasonic (Ford)
● Spearheaded a team of 10+ engineers in developing CAN and diagnostics layers integrated with Ford Network
OS, utilizing C++, Vector CANoe/CANalyzer tools, and embedded systems programming for robust automotive
network performance.
● Developed a security service diagnostic feature, redesigned the Diagnostics Trouble Code functions and
automated CAN testing.
Battery System Software - Client: General motors
● Developed GMLAN CAN middleware layer and seamlessly integrated with the application layer, leveraging C,
C++, CAN protocols, and AUTOSAR compliance.
● Integrated Board Support Package (BSP) with GM application layer using embedded C and RTOS, and executed
comprehensive vehicle testing reliability with diagnostic tools like Vector CANalyzer.
● Developed and integrated SPI driver for Cell sensing boards utilizing C, ARM architecture.
Software Team Leader
Rotork Controls | 04/2011-06/2012 | UK & India
Control Valve Actuator software
● Lead a team to integrate the CAN and Bluetooth protocol layer with the main actuator control software.
● Interfaced status, configuration, and calibration parameters with the communication protocols.
● Designed and developed an application that communicated via a National Instruments CAN card and
Bluetooth to test the embedded software.
● Conceptualized and designed an automated actuator test bench.
Software Technical Lead
HCL Technologies | 08/2004-03/2011 | San Diego, CA & India
Fan Motor Controller software - Client: Rockwell Collins
● Collaborated with clients (Boeing & Airbus) to consolidate traceability matrix, tracking requirements through
code and test cases.
● Led the development of core fan motor controller software from driver to application layers, ensuring DO-178B
compliance and achieving certification.
● Designed a configurable common core motor controller software adaptable for different programs
● Developed CAN test software and automated test scripts for efficient testing and integration.
● Automated test scripts for functional and unit testing of embedded software, focusing on Auxiliary Power
System (APS) and RPDS.
● Architected and developed multi-language support for universal display firmware.
● Improved Functional Verification Testing platform and automated Hardware Software Integration Testing.
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