ACTIVATE / ALIGN / RESTORE
Run the room, not just the ticket.
Establish command structure, decision cadence, ownership, and escalation paths across engineering, product, legal, security, account, and partner teams.
Executive crisis leadership · Production AI & backend engineering
Hi, I’m Nikita. I calm complex crises, build intelligent systems, and occasionally find time to finish my coffee.
I’m a mom navigating life somewhere between diapers, deadlines, deep research, and the daily rhythm of executive-level fire drills.
By day, I lead some of Microsoft’s highest-severity executive escalations for strategic S500 customers, stepping into the moments when the pressure is high, the path forward is unclear, and everyone needs calm, clarity, and action fast.
When the war room winds down, I usually end up swapping incident bridges for Python, LLMs, cloud architecture, and whatever AI idea has taken over my brain that week. I’m constantly learning, researching, experimenting, and building, especially around production-grade AI, intelligent agents, backend systems, and the messy, fascinating space where technology meets real human decision-making.
That intersection is really my thing: turning chaos into clarity, pressure into momentum, and lessons from real-world crises into smarter, more resilient systems.
And somewhere in between all of that, I’m probably looking for a missing bottle, reheating the same cup of coffee for the third time, or wondering how bedtime became its own high-severity incident.
2,000+executive escalations synthesized
S500strategic customers
Production AILLM and agentic systems
Multi-cloudAzure and AWS architecture
Dual-practice operating radar
Executive command meets engineering depth
My leadership and engineering practices reinforce each other: operational pressure sharpens system design, while technical depth improves decisions during critical events.
SIGNAL / DECISION / TRUST
Translate complexity into action.
Build executive updates that make the situation, impact, risk, decision, and next checkpoint clear, without forcing leaders to reconstruct the story.
LEARN / REDESIGN / VERIFY
Make every incident improve the system.
Turn post-incident evidence into prioritized corrective action, better playbooks, improved product decisions, and measurable operational learning.
ORCHESTRATE / VALIDATE / SCALE
Build AI systems, not isolated model demos.
Engineer LLM and agentic platforms with typed APIs, orchestration, guardrails, observability, retrieval, human review, and cloud-native deployment.
Original research / practitioner framework
Crisis Support Debt™
A hidden organizational vulnerability that accumulates when the support ecosystem around mission-critical technology deteriorates, even while the technology itself appears healthy.
THE CENTRAL QUESTION
What happens when the system still runs, but the organization’s ability to recover from its failure has quietly weakened?
Human expertise, institutional knowledge, documentation, supplier capability, operational process, and governance can erode gradually. The vulnerability may remain invisible during normal operations and surface only when a major disruption demands capabilities that no longer exist at the required depth or speed.
Crisis Leader
How leaders create shared reality, decision velocity, and trust under pressure.
Operational resilience
How invisible support-system decay changes an organization’s recovery capacity.
AI & human judgment
How intelligent systems can strengthen, not displace, accountable human decisions.
Experience timeline
From technical depth to enterprise command
A career built from cloud and regulated-infrastructure depth to the final escalation tier for Microsoft’s most strategic customers and senior executives.
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2018-Now
Microsoft · Seattle
Senior Escalation Manager & Executive Lead
Lead the highest-severity, executive-sponsored escalations for Microsoft’s Strategic 500 customers across Azure, Microsoft 365, identity, and other enterprise services. Healthcare & Life Sciences is one specialized vertical within this broader remit, bringing additional regulatory and reputational complexity.
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2016-2018
Microsoft · India & Costa Rica
Azure Support Engineer
Owned Azure commerce, subscription, quota, and deployment escalations. Built early pathways for Tier-2/3 incidents and translated customer signal into product and roadmap input.
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2011-2013
Hewlett Packard · India
Technical Solutions Engineer II
Provided first-line technical management and support for Product Data Management (PDM), Active Directory (AD), and SAP while supporting enterprise infrastructure and computer system validation in highly regulated environments.
Selected work
Operational systems and AI engineering
Representative work across crisis operations, production AI, backend reliability, and evidence-driven problem solving.
Operations02
Program system
Internal postmortem program
Helped establish and lead a repeatable review system that converted incident evidence into root causes, corrective actions, and organizational learning.
- 2,000+ escalations synthesized
- Kepner-Tregoe methodology
- Executive-grade review governance
Operating model
Executive escalation playbook
Standardized high-stakes escalation execution for executive-sponsored customer situations with severity criteria, war-room checklists, escalation trees, communication templates, and role clarity.
- Reusable incident structure
- Cross-functional accountability
- Readiness and IC enablement
Applied AI & engineering07
Production AI platform
LLM orchestration & conversation service
Production conversation backend designed for burst traffic, concurrent workloads, conversation state, latency control, and reliable Kubernetes deployment.
100s–1,000srequests per minute design range
Python · FastAPI · LLM APIs · Kubernetes · Docker
Agentic AI
Workflow assistant
End-to-end assistant for tool calling, structured output, validation, intelligent task routing, API integration, and workflow automation.
Python · FastAPI · LLMs · REST APIs
Responsible AI operations
Production guardrails framework
Controls for validation, fallback behavior, human review, audit logging, observability, model drift monitoring, and operational governance.
Python · MLOps · Monitoring · APIs · LLM systems
Performance engineering
Python memory & latency optimization
Diagnosed memory retention in asynchronous workloads through heap, reference, task, and object-lifecycle analysis; refactored background execution for stability.
Python · Async · Memory profiling · Debugging
Database performance
PostgreSQL query optimization
Used query-plan analysis, indexing, query rewriting, and data-access optimization to remove a production bottleneck.
~1.2s → ~15msquery latency
PostgreSQL · SQL · Indexing · Performance tuning
Cloud architecture
Cloud-native AI platform
Backend and AI services designed across AWS and Azure with containers, orchestration, deployment automation, observability, and infrastructure as code.
AWS · Azure · Kubernetes · Docker · Terraform · CI/CD
Graduate analytics project
Hospital length-of-stay prediction
An end-to-end study of patient and resource factors associated with extended hospital stays, combining statistical analysis, feature engineering, model evaluation, and executive recommendations.
- Domain
- Healthcare operations
- Methods
- EDA · statistics · ML
- Outcome
- Decision-focused analysis
Beyond the model
How I think about production AI systems
A model is one component. Reliability comes from the operating system around it: orchestration, validation, observability, human judgment, and resilient infrastructure.
Reasoning core
LLM / Agent
Select a system component to inspect its role in production reliability.
Technical capability map
From model behavior to production reliability
A multi-disciplinary engineering toolkit spanning AI, backend systems, infrastructure, data, full-stack development, and production troubleshooting.
AI / MACHINE LEARNING
Intelligent systems
BACKEND ENGINEERING
APIs & distributed services
CLOUD / INFRASTRUCTURE
Portable production platforms
DATA / DATABASES
Fast, governed data paths
LANGUAGES / FULL STACK
End-to-end implementation
RELIABILITY / OPERATIONS
Engineering under real conditions
Select an interactive skill to filter the related project portfolio.
Credentials
Methods behind the judgment
PROCESS / BLACK BELT
Lean Six Sigma
Systematic improvement, measurement, and durable process redesign.
DELIVERY / PRACTITIONER
PRINCE2
Structured governance, delivery controls, risk, and stakeholder alignment.
SERVICE / FOUNDATION
ITIL
Service management, incident discipline, and continual improvement.
ANALYSIS / PRACTITIONER
Kepner-Tregoe
Evidence-based problem analysis and root-cause isolation.
CLOUD / MICROSOFT
Azure · Security · AI
AZ-900, SC-900, MS-900, AI-900, and Power Platform Fundamentals.
EDUCATION / IN PROGRESS
PhD Candidate
Artificial Intelligence research; MS in Applied AI at the University of San Diego, Shiley-Marcos School of Engineering.
Open channel