AI-Native Engineering
Led engineering teams building AI-powered customer support, knowledge retrieval, classification, routing, and agentic workflows.
32% support deflectionSenior Software Engineering Manager · Spring Health · Frisco, Texas
Gurusewak
Kalra
Senior Software Engineering Manager building AI-native products, high-impact teams, and modern engineering organizations.
I lead product engineering at the intersection of AI, enterprise SaaS, customer value, and growth. I help teams decide where AI creates meaningful leverage, build production-ready experiences, modernize how software is delivered, and develop engineers into broader technical leaders.
Leadership Impact
Engineering connected to customer and business outcomes.
$1.8M
Qualified expansion opportunities generated
$1.2M converted into closed opportunities
32%
Reduction in customer-support emails
Through AI-powered support experiences
28%
Increase in new monthly active users
Driven by product-led growth initiatives
$5M+
Operational savings generated
Through digital customer-support and engagement
19+
Countries reached
Expanding enterprise experiences globally
$20M
Enterprise contract influenced
Contributed to a landmark enterprise deal
5.5 → 7.8
Customer NPS improvement
Measurable customer experience lift
85% → 93%
Digital engagement increase
Across the customer platform
Product Strategy
Evolved Spring Insights into a customer-value platform with ROI analytics, clinical outcomes, and executive reporting.
$1.8M expansion pipelinePeople Leadership
Led up to 11 engineers across two teams. Built hiring pipelines, coached engineers toward ownership, and developed senior engineers into technical leaders.
11 engineers ledOrganizational Transformation
Helped lead Spring Health toward AI-native engineering: career ladders, interview design, AI fluency standards, and SDLC integration.
Company-wide impactAI-Native Engineering
Building AI capability across products, teams, and engineering systems.
Not experiments. Not features. A durable operating model where AI is embedded in how products are built, teams are evaluated, and engineering organizations grow.
Product Strategy
Evaluate whether AI creates meaningful leverage. Compare with deterministic software, workflow automation, and data pipelines before committing.
- Problem-first decision framework
- AI vs. deterministic trade-off analysis
- Value, cost, latency, and security assessment
- Long-term maintainability planning
AI Architecture
Build production-ready AI systems with proper retrieval, grounding, evaluation, and human oversight rather than prototype-grade integrations.
- RAG with semantic and keyword retrieval
- Agentic workflows with domain semantics
- MCP and structured tool definitions
- Observability and evaluation loops
Engineering Workflow
Integrate AI across the full SDLC, from discovery and design through implementation, testing, review, and measurement.
- AI-assisted discovery and specification
- Accelerated implementation and code review
- AI-supported testing and quality gates
- Measuring delivery and quality outcomes
Talent Systems
Update career ladders, establish AI fluency expectations, and redesign the interview process so AI capability becomes a hiring and growth criterion.
- IC and manager career ladder updates
- AI fluency expectations at every level
- AI-native interview design
- Connecting AI capability to career growth
Organizational Adoption
Help the organization move from isolated AI experiments to durable, measured AI capability embedded in product thinking and engineering execution.
- Coordinating cross-team AI pilots
- Representing product-engineering concerns
- Influencing reusable AI architecture
- Measuring adoption through outcomes
Organizational Transformation · Spring Health
Before
AI as an optional productivity tool
- AI used ad-hoc by individual engineers
- No standards for AI in interviews or hiring
- Career ladders silent on AI expectations
- Architecture and tooling fragmented
- No measurement of AI adoption or impact
After
AI as an intentional capability embedded in product thinking and engineering execution
- AI fluency expected at every engineering level
- Interview process assesses AI judgment
- Career ladders updated with AI expectations
- Reusable AI architecture and shared tooling
- Adoption tracked through delivery and quality outcomes
Helped lead Spring Health's transition toward AI-native engineering as one contributor among a broader organization.
People & Organizational Leadership
Technology scales through people.
Led up to 11 engineers across two product teams. Hiring, performance management, career planning, coaching, and developing engineers into technical leaders.
Engineer Development Model
Stage: Executor
The engineer delivers well-scoped tasks on time with good quality. They do what's asked and do it well.
Coaching approach
- Give clear scope and explicit success criteria
- Pair on ambiguous problems to build confidence
- Provide direct feedback on quality and pace
- Build trust through consistent follow-through
Leadership Philosophy
Give engineers clarity, context, ownership, and direct feedback.
Help strong executors become owners, owners become technical leaders, and technical leaders become organizational multipliers.
Protect team focus during ambiguity and staffing pressure.
Manage underperformance directly and fairly, for the team's benefit.
Build psychologically safe but accountable environments.
Lead through cross-functional influence rather than authority alone.
Selected Leadership Stories
Where leadership met product, AI, and people.
Making Engineering AI-Native
Helped lead Spring Health's transition from AI as an optional tool to AI as an intentional capability embedded across career ladders, hiring, product development, and the full SDLC.
Career LaddersAI FluencyInterview DesignSDLC IntegrationAdoption Measurement
Company-wide engineering transformation
Evolving Spring Insights into a Customer-Value Platform
Led the engineering team that transformed an analytics feature into a customer-value platform with ROI measurement, clinical outcome tracking, executive reporting, and AI-powered engagement.
ROI AnalyticsClinical OutcomesExecutive ReportingAI SupportCustomer Retention
$1.8M expansion pipeline generated
AI-Powered Customer Support
Built an AI-powered support experience with knowledge retrieval, intent classification, ticket routing, deterministic guardrails, and human escalation paths.
Knowledge RetrievalClassificationRoutingGuardrailsObservability
32% reduction in support emails
Global Knowledge and Support Automation
Led the architecture and delivery of a global knowledge and support platform across 70+ sites, 9 languages, and 17 products with automated publishing and AI-assisted personalization.
70+ Sites9 Languages17 ProductsAutomated PublishingPersonalization
$5M+ operational savings
Scaling Product Experiences Globally
Expanded enterprise product experiences to more than 19 countries, coordinating across engineering, localization, design, and legal teams to build scalable, accessible international architecture.
19+ CountriesAccessibilityArchitectureCross-Team Coordination
$20M enterprise contract influenced
Career Journey
From engineer to organizational leader.
CodeSystemsProductsTeamsLeadersOrganizations
2022 – Present
Teams → Organizations
Senior Software Engineering Manager
Spring Health
Lead up to two product engineering teams (11 engineers). Built AI-native customer support, analytics, and insights platforms. Helped lead organizational AI transformation: career ladders, interview design, and AI fluency standards.
AI EngineeringPeople LeadershipProduct StrategyOrg Transformation
2021 – 2022
Products → Teams
Software Engineering Manager
Spring Health
Managed engineering team delivering customer-facing product experiences. Established engineering practices, hiring processes, and product-engineering collaboration frameworks.
Engineering ManagementHiringProduct Engineering
2019 – 2021
Systems → Products
Staff Software Engineer
LogMeIn
Technical leadership across global customer support and knowledge platforms. Led architecture for 70+ sites, 9 languages, 17 products. Contributed to $20M enterprise contract and $5M+ in operational savings.
Technical LeadershipGlobal PlatformsArchitectureEnterprise
2016 – 2019
Code → Systems
Technical Lead / Senior Engineer
LogMeIn
Led technical direction for customer experience products. Expanded platforms to 19+ countries. Improved sales demo satisfaction from 2.6 to 4.6.
Technical LeadInternational ExpansionCustomer Experience
2014 – 2016
Components → Features
Senior Software Engineer
Citrix
Delivered complex product features across enterprise SaaS products. Deep technical execution in large-scale systems.
Enterprise SaaSFull-StackScale
2012 – 2014
Individual Contributor
Software Developer
Egen Solutions
Started career building customer-facing web applications. First engineering role establishing foundations in product thinking and technical craft.
Web DevelopmentProduct Engineering
Personal
The same curiosity that builds systems also explores the world.
Engineering leadership is not just a professional identity. The way I approach exploration, learning, and ambiguity outside work is the same way I approach it inside.
33 States and Counting
Goal: all 50Exploring the United States one state at a time, with a goal to visit all 50. Every trip is an exercise in curiosity.
Flying Lessons
Systems thinking from 2,000 ftTook flying lessons and seriously considered becoming a pilot. Understanding systems from the cockpit changed how I think about complex technical decisions.
Titanic's Final Dinner
April 14, 1912 menuRecreated the Titanic's final first-class dinner menu for friends, a research project disguised as a dinner party.
International Cultures
9 languages shippedStrong interest in international cultures, languages, and global experiences. Nine languages in the support platforms I've helped build.
Cooking and Cuisine
Always experimentingCooking new cuisines as a form of exploration. Trying restaurants nobody has heard of. Finding signal in unexpected places.
Continuous Learning
Never stop buildingFrom hands-on developer to engineering manager, each stage required unlearning as much as learning. Curiosity is the constant.
“Moving from a hands-on developer into engineering leadership was not about giving up the craft. It was about finding a bigger way to build.”
Contact
Let's build what comes next.
I'm interested in opportunities where I can lead AI-native product engineering, develop strong technical leaders, and connect engineering strategy with meaningful customer and business outcomes.
Frisco, Texas · Open to remote
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