Sr. AI/ML Engineer
Resume:
SRIKANTH AAKULA
************@*****.***
Professional Summary:
AWS and Azure certified AI/ML Engineering Leader and Data Scientist with 15+ years of experience designing, building, and deploying enterprise-grade GenAI, LLM, NLP, and ML solutions in regulated financial services environments. Hands-on expertise across the full ML lifecycle—from data preparation, feature engineering, and model training through CI/CD deployment, monitoring, drift detection, and retraining—using Python, LangChain, LangGraph, PyTorch, scikit-learn, TensorFlow, and MLflow. Proven experience delivering production RAG pipelines, agentic AI systems, Google CCAI-powered conversational AI, and propensity models integrated into enterprise platforms, including Salesforce. Equally strong as a people manager leading onshore/offshore AI/ML teams and as a hands-on engineer writing and reviewing production code.
KEYSKILLS & COMPETENCIES:
•GenAI & LLM Engineering:
LLMs (GPT-4, Claude, Gemini), RAG pipelines, Lang Chain, Lang Graph, CrewAI, Google ADK, prompt engineering, vector databases, Hugging Face, agentic AI, Google CCAI / Dialogflow
•ML Engineering:
Python (Pandas, NumPy, scikit-learn, PyTorch, Tensor Flow), NLP & text analytics, propensity modeling, churn prediction, customer segmentation, feature engineering, model evaluation & tuning
•MLOps & Deployment:
MLflow, CI/CD for ML, model versioning & registry, drift detection, monitoring & retraining, Databricks (Spark, MLflow, Unity Catalog), Snowpark, Docker, Kubernetes, feature stores
•Cloud & Integration:
Azure (Certified), AWS (Certified), GCP / BigQuery, Snowflake, SQL, Java (Spring, J2EE), RESTful APIs, microservices, Sales force CRM, RPA
•Governance & Leadership
ResponsibleAI AIGuardrails DataGovernance Compliance PeopleManagement Onshore/OffshoreTeams Agile/ Scrum Sprint Planning Executive Communication
PROFESSIONAL EXPERIENCE:
Discover Financial Services – Capital One, Atlanta, GA
Manager, Data Science & AI/ML Engineering Jan2022–Present
Hands-on AI/ML engineering manager delivering production GenAI, LLM, NLP, and ML solutions in a regulated financial services environment. Led end-to-end ML lifecycle—from data ingestion and feature engineering through model training, CI/CD deployment, monitoring, and retraining—while managing onshore and offshore engineering teams. Integrated AI capabilities into enterprise platforms, including Salesforce and Google CCAI, ensuring responsible AI governance, security, and compliance alignment throughout.
•Led research-to-production delivery of an enterprise GenAI customer intelligence platform—engineered end-to-end ML pipelines (data prep feature engineering model training deployment monitoring) using Python, LangChain, and BigQuery; implemented RAG pipelines, LLM-generated segment summaries, and campaign lift simulation integrated with Salesforce for targeted execution.
•Developed propensity scoring models and customer segmentation using scikit-learn and Python across millions of customers—enabling data-driven product adoption targeting and merchant strategy optimization.
•Implemented MLOps best practices across all AI/ML deliverables—CI/CD for ML pipelines, model versioning and registry management, real-time monitoring, drift detection, and automated retraining workflows using MLflow and Databricks.
•Implemented Databricks Unity Catalog for enterprise ML governance—enabling data lineage tracking, dataset versioning, access governance, audit trails, and compliance controls across all AI/ML deliverables in a regulated environment.
•Applied responsible AI principles throughout—LLM guardrails, explainability requirements, fairness checks, privacy-by-design, and compliance-aligned governance for all production GenAI and ML systems.
•Managed and mentored onshore and offshore AI/ML engineering teams—supporting sprint planning, backlog prioritization, delivery commitments, performance coaching, and technical skill development across Agile cycles.
•Implemented data pipeline security controls, including encryption, data masking, role-based access controls, and row-level security—ensuring data protection and compliance alignment across regulated analytics environments.
•Built a daily acceptance monitoring pipeline with outlet-level SQL and Python analysis by customer, issuer, and product—enabling granular KPI tracking, anomaly detection, and early risk detection.
•Automated Salesforce metrics integration using RPA and Python pipelines, reducing manual effort by 99% and enabling event-driven automated alerts for sales follow-up.
•Implemented unit, integration, and performance testing across ML models, pipelines, APIs, and financial systems—ensuring quality, accuracy, and stability of all deployed solutions.
•Co-led the Counterparty Restitution Program—partnering across strategy, settlement, and data management to define KPI tracking and implement Salesforce-based case management.
THECOCA-COLACOMPANY Atlanta,GA
Financial Systems & Cloud Data Engineering Manager 2018–Jan2022
Led onshore and offshore engineering teams delivering enterprise Java applications, ETL pipelines, financial systems, and ML- powered analytics at scale. Built and maintained Spring/J2EE backend services and standalone ETL utilities across SAP HANA, Teradata, Oracle, SQL Server, Snowflake, and Azure, collaborating with international offshore teams across multiple time zones.
•Designed and developed Java-based (Spring, J2EE) web applications, backend services, and standalone ETL utilities—delivering enterprise financial systems and analytics platforms with security integration and scalable architecture across the Coca-Cola technology portfolio.
•Served as SME for business-critical platforms, including P&L systems supporting $7.4B GR / $3.6B NR, Salesforce, food service systems, Volume Performance Intelligence Application, and $3.8B allowance allocation—bringing deep SAP HANA and ERP integration expertise.
•Implemented CDC pipelines using Azure Data Factory—capturing real-time changes from source systems and enabling reliable, low-latency data integration across financial platforms.
•Designed and architected data, visualization, and analytics tools—reducing manual intervention by 90% and enabling leadership to access insights 2 days earlier than previously possible.
•Implemented row-level security and RBAC at the database level across SAP HANA, SQL Server, and Oracle—enforcing data access controls and protecting sensitive financial data.
•Eliminated manual processes, freeing 600+ hours annually at HQ and 5,000+ enterprise hours post-rollout (Top 10, Global Analytics Challenge 2020).
•Eliminated manual reporting across finance, generating approximately $300K in annual savings (Top 11, Global Analytics Challenge 2019).
•Implemented automated data validations and controls—enabling $200K in savings while strengthening governance.
•Collaborated with international offshore teams across time zones on the design, development, testing, and delivery of mission-critical engineering projects.
Technology Development Manager II 2016 – 2018
•Led delivery of 12 projects ($100K–$2M budgets), improving project success rates by 40% through on-time, within-budget execution across Agile and Waterfall methodologies.
•Built Java-based web applications and backend services with security integration, enabling scalable web reporting and enterprise-wide access.
•Designed and built customer agreement tracking and planning tools with expiration forecasting using business rules—hands-on SQL Server and ETL development using SSIS.
•Designed and implemented ETL pipelines using SSIS and SQL, integrating data from disparate sources to support analytics and decision-making.
•Implemented unit, integration, and performance testing across pipelines, applications, and financial systems to ensure quality and reliability.
SeniorEngineer 2015–2016
•Led end-to-end SDLC delivery within the Performance & Analytics Center of Excellence, translating business requirements into scalable analytics applications and reporting solutions.
•Architected and delivered data pipelines and performance dashboards to enable faster, insight-driven decision-making.
•Served as Project Manager and Technical Architect for automation and analytics initiatives, improving visibility and operational efficiency.
SQL Programmer I 2013–2015
•Led ETL and BI development supporting enterprise performance measurement and analytics.
•Delivered dashboards and analytics used by executive leadership for portfolio optimization and marketing investment decisions.
•Mentored junior developers and analysts while serving as technical lead on automation initiatives.
CCRI Inc. Moorhead,MN
Technology Developer 2009 – 2013
•Developed and maintained enterprise web applications and data solutions.
•Implemented monitoring, alerts, and notifications to improve system reliability and security.
EDUCATION:
•Master of Business Administration, Louisiana State University
•Master of Sciencein Computer Science, North Dakota State University
CERTIFICATIONS:
•AWS Certified
•Microsoft Azure Certified
CONTINUOUS LEARNING:
AgenticAI(LangChain,LangGraph,CrewAI,GoogleADK) LLM&RAGArchitecture NLP &TextAnalytics MLOps/LLMOps
Responsible AI AI Governance Guardrails MCP A2A Google CCAI Databricks Unity Catalog
Contact this candidate