Puneet Goyal

Business-led technology transformation executive with 22+ years of technology leadership, including 15+ years engineering high-governance platforms within regulated financial-services environments.

Production Agentic AI Pioneer: Head of Engineering at Capital One, leading the architectural evolution of production-grade Agentic AI platforms, Model Context Protocol (MCP) implementations, LLM orchestration, and developer self-service ecosystems.

Core Value Proposition: Expert at turning highly fragmented, manual enterprise workflows into automated, production-grade platforms. Solved the enterprise cyber-remediation bottleneck by unifying high-fidelity vulnerability telemetry and application provenance with MCP-enabled AI agents to autonomously resolve code defects, handle build failures, and execute self-healing deployment pipelines.

Scalable Data & Governance Patterns: Extends this exact AI-and-platform operating model to knowledge discovery and data engineering—establishing trusted context retrieval, canonical data products, and event-driven architectures that make AI operationally reliable and cost-effective at enterprise scale.

Executive Leadership: Operates with an "own-your-CEO" mindset across technology strategy, architecture choice, hybrid build-vs-buy investments, cross-functional organization design, and measurable business outcomes.

Director, Software Engineering | Enterprise Engineering Transformation - Capital One - Bangalore, India

(2012-05)

Execute multi-year, high-scale enterprise platform transformation strategies. Responsible for converting fragmented security, data, cloud, and engineering workflows into governed, product-led platforms. Manage full operational budget, team topologies, OKRs, and executive communications across the transformation portfolio.

• Cybersecurity Automation, Production Agentic AI & Vulnerability Remediation
• The Systemic Problem: Redefined enterprise vulnerability remediation from an administrative, ticket-driven follow-up exercise into a closed-loop engineering system across SAST, SCA, container security, and end-of-life (EOL) dependencies.
• MCP & Agent Architecture: Productionized an autonomous multi-agent cyber remediation workflow utilizing Model Context Protocol (MCP) to grant LLM agents secure, contextual access to tools, code repositories, Jira tracking, and Jenkins validation pipelines.
• Self-Healing Orchestration: Combined deterministic automation (Mend Renovate, OpenRewrite-style recipes) for standard updates with Agentic AI reasoning loops to dynamically diagnose and self-heal build failures, compile-time errors, and complex dependency conflicts.
• Governed Execution: Engineered the end-to-end automated guardrails ensuring every AI-generated Pull Request underwent rigorous automated scan confirmation, audit evidence collection, and human-in-the-loop validation before production release.
• Converged an ecosystem of 50-60 disjointed engineering tools and siloed micro-platforms into a unified internal developer platform leveraging Backstage plugins.
• Formulated the architecture and build-vs-buy strategy for a $50M platform investment, prioritizing open-source API extensibility, identity integration, and low long-term operating costs.
• Positioned the IDE and Internal Developer Platform as the core developer interaction layers, successfully driving frictionless onboarding, standardized microservice templates, and unified release workflows.
• Shifted cloud governance from reactive, post-deployment compliance to proactive, pipeline-embedded guardrails by injection of 400+ automated cloud controls directly into CI/CD templates.
• Linked infrastructure compliance failures directly to application metadata and IAM/access contexts, eliminating team ownership ambiguity and accelerating risk closure.
• Established enterprise blueprints for cloud-native distributed systems, microservices, observability frameworks, resilience testing, and cost-optimized AWS architectures (EC2, ECS, EKS, Lambda).
• Mitigated fragmentation across producer/consumer pipelines by establishing strict schema contracts, metadata lineage, and data profiling patterns.
• Transitioned data architecture away from brittle point-to-point ETL builds toward real-time, Kafka-driven event streaming and governed canonical data entities.
• Implemented source-level data quality remediation workflows, embedding automated data-validation gates to protect downstream risk, control, and real-time analytics platforms.
• Achieved 100% Continuous Deployment adoption across target portfolios by transforming CI/CD pipelines into automated maturity models featuring mandatory regression confidence gates, canary releases, feature flags, and rapid rollbacks.
• Replaced fragmented wiki environments with an automated docs-as-code publishing pipeline, using Agentic AI context-retrieval patterns to surface high-fidelity technical answers directly inside developer operational workflows.

Software Engineering & Technology Roles - HSBC - Bangalore, India

(2008-06 - 2012-05)

Acquired foundational hands-on experience in financial technology, enterprise software engineering, distributed systems architecture, and application delivery within high-availability environments.

Software Engineer - Earlier Software Engineering Roles

(2005-05 - 2008-05)

Acquired foundational hands-on experience in financial technology, enterprise software engineering, distributed systems architecture, and application delivery within high-availability environments.

LEAD Program - Leadership Development - Stanford University (2025)

Post-Graduation - Strategic Thinking and Leadership - IIM Ahmedabad (2021)

Post-Graduation - Information Technology & Data Analytics - IIM Kozhikode (2021)

Post-Graduation - Cloud Computing - Great Learning

Master of Computer Applications (MCA) - Computer Applications - Indira Gandhi University, Delhi (2005)