About
An engineer-turned-executive who leads delivery, not just tracks it.
I run enterprise programs the way a P&L owner would — accountable for outcomes, not just RAG statuses.
Twelve-plus years in IT — the first seven hands-on in .NET engineering before moving into program and delivery leadership. That foundation means I read a status report and an architecture diagram with equal fluency, and use both to keep delivery plans honest.
Today I own multi-account portfolios worth ₹2Cr+, leading 20+ engineers as the single point of accountability for client sponsors on delivery health, risk and scope. I'm now applying that same discipline to AI-augmented delivery — using agentic tooling to compress planning, reporting and QA cycles without sacrificing governance.
Leadership
Own the plan, the risk register and the client relationship — with the technical depth to challenge estimates intelligently.
Positioning
AI-augmented delivery practitioner, LTIMindtree Certified Agile Practitioner, and one of the few leaders who can still read the code.
12+ Years in IT · Technical Project Management · Enterprise Delivery · Software Engineering Background
Currently: Applying agentic AI workflows to enterprise delivery reporting and risk forecasting.
Leadership
Delivery credibility, earned in code.
Most program managers manage the plan. I've also built the systems it describes — which changes every conversation with engineering and the boardroom.
Portfolio governance
Govern the portfolio.
Multi-account governance across L&T Group programs — steering committees, Agile-aligned risk controls, ISO-standard compliance, vendor and SLA management.
Client partnership
Own the client relationship.
The single point of accountability for delivery health with client sponsors — reading the room, surfacing risk early, and keeping stakeholder confidence green even when the plan isn't.
People leadership
Build & grow the team.
Coached engineers in Scrum and Kanban (+15% productivity), grew individual contributors into module owners, and structured teams to reduce key-person risk.
Commercial discipline
Steer the commercials.
Effort estimation, resource planning and vendor/SLA management that protect delivery margin — the commercial discipline behind every predictable, on-budget green status.
Technical depth
Speak the stack.
.NET, C#, SQL Server and Azure background means estimates get challenged intelligently, risks get spotted early, and technical teams get a leader who understands the work.
Transformation
Adopt what's next.
Formally upskilling in AI and applying it hands-on to delivery practice — reporting, planning and engineering workflows. Full credentials under AI Leadership.
Operating principles
How I run delivery.
"I build delivery organizations that turn enterprise transformation into predictable, measurable outcomes — through governance people trust, capability that outlasts me, and decisions driven by data, not decks."
Anyone can report a status. These are the operating principles I lead teams and accounts by — the difference between managing a plan and owning an outcome.
Principle 01
Green is earned, not reported.
Status reflects reality. I surface risk while it's still cheap to fix — a comfortable steering deck that hides slippage helps no one, least of all the client.
Principle 02
Estimate honestly, protect the margin.
On-budget isn't luck. Disciplined estimation, resource planning and scope control are how delivery stays profitable and commitments stay credible.
Principle 03
Build people, not just plans.
The strongest delivery org outlasts any one manager. I grow engineers into owners and reduce key-person risk, so capability compounds instead of walking out the door.
Principle 04
AI is a capability, not a slide.
I earn the right to govern GenAI initiatives by building them hands-on — so adoption decisions come from judgement, not vendor decks.
I don't just hold opinions — I publish them.
A public record of technical writing and community contribution — see Recognition for the award tally. The same instinct I bring to delivery leadership: think in the open, get the reasoning peer-reviewed.
Community contribution
795k developers reached, mostly on SQL Server.
Contributing since 2018 — 430 answers, 5,685 reputation, 92% of it on sql-server. These are the problems engineers hit at 2am when a report times out. Answering in public gets the reasoning peer-reviewed, which keeps a delivery leader honest about what is and isn't feasible.
GROUP BY vs OVER() decisions behind them.
View full contribution breakdown
Why it matters for delivery: engineers escalate database problems to me because I've debugged them, not because the org chart says to. That shortens the distance between a red status and a real fix.
How I work
One framework, every program.
The same nine-step discipline behind every account I run — from the first discovery call to the retrospective that feeds the next one.
01 · Discovery
Understand the business context, constraints and success criteria directly with stakeholders before a single line of a plan gets written.
02 · Planning
Translate scope into a realistic delivery plan — estimation, resourcing and a RAID log that starts before the risk does.
03 · Risk Assessment
Score and track risk continuously, not once at kickoff — the difference between a red status that's a surprise and one that's already being managed.
04 · Execution
Run sprints and phases alongside engineering — close enough to the stack to catch technical risk before it becomes a client escalation.
05 · Governance
Steering-committee cadence, ISO-standard compliance and SLA management that keep every account auditable end to end.
06 · Stakeholder Communication
Keep sponsors and delivery teams reading from the same status — surfacing risk early instead of managing it around a comfortable deck.
07 · Quality Assurance
Build QA gates into the plan itself, not bolt them on at the end — the same discipline that has held delivery success at 98%.
08 · Deployment
Sequence go-lives to protect production stability — zero critical go-live escalations across every account run this way.
09 · Continuous Improvement
Close every phase with a retrospective and feed it back into the next one's plan — capability that compounds instead of resetting each time.
Success stories
Enterprise programs, measured in business outcomes.
Framed by business outcomes, not feature lists. Each shows how I lead delivery across stakeholders, governance and execution — all for L&T Group companies at LTIMindtree.
Narada — SEBI Compliance Reporting Platform
Business challenge
Group companies needed an auditable process for SEBI regulatory disclosures — a regime where misses carry real consequences — and filings were fragmented across manual, ad hoc processes with no single system of record.
Technologies · .NET Core · SQL Server · Azure
Read full case study
Business context
SEBI compliance sits above any single business unit — a missed or late disclosure exposes the whole group to regulatory scrutiny, not just the filing team, which is what elevated this from an IT ticket to a governance priority.
My role
Sat as the single point of accountability between engineering, the client sponsor and compliance stakeholders — validating scope trade-offs before they became rework, and running steering-committee reporting on schedule and audit readiness.
Team composition
A cross-functional team of developers, QA and a dedicated compliance/corporate-secretarial stakeholder group — no external vendor, so accountability for delivery and correctness sat entirely with this team.
Strategy
Defined requirements directly with the corporate-secretarial team and built the platform incrementally against ISO-aligned governance checkpoints, rather than a single big-bang release.
Risks managed
The core risk was a submission slipping past a regulatory deadline — mitigated with a RAID log reviewed at every steering committee, not just at milestones, so a slipping date surfaced while there was still time to act.
Key decisions
Chose to build the audit trail into the platform from day one rather than add it later — cost more up front, but avoided a much costlier retrofit once the platform was live and in regulatory use.
Lessons learned
Regulatory platforms live or die on auditability, not features — building the submission trail in from day one avoided a costly retrofit later.
CDP — Common Digital Platform, L&T Construction
Business challenge
Road-construction operations sat across disconnected processes and reporting silos, limiting visibility across sites and slowing decisions that depended on site-level data.
Technologies · .NET · Angular · SQL Server · Azure DevOps
Read full case study
Business context
Construction programs run on site-level realities changing week to week — without shared visibility, decisions at the program level were being made on stale or incomplete data, turning a reporting gap into a real delivery risk.
My role
Owned the delivery plan and stakeholder relationship across construction operations and the technical team, translating field realities into a build the engineers could actually deliver.
Team composition
Coordinated between construction operations leads at each site, the internal engineering team, and Azure DevOps-based delivery tooling — no single site owner had visibility into the others before this platform existed.
Strategy
Led end-to-end delivery of the digitization platform, sequencing rollout site-by-site so operational teams could adopt without disrupting live construction schedules.
Risks managed
The main risk was adoption resistance from site teams used to their own processes — managed by rolling out one site at a time and treating early-site feedback as input to later rollouts, not just a rollout order.
Key decisions
Chose phased, site-by-site rollout over a single group-wide launch — slower on paper, but it meant a failure at one site never became a group-wide failure.
Lessons learned
Adoption in field operations depends more on rollout sequencing than on feature completeness — phased site onboarding avoided the resistance a big-bang launch would have triggered.
Easy Skills — Competency Management System
Business challenge
L&T Construction needed a better way to track workforce capability and deploy people against the right project needs, with capability data scattered across spreadsheets and manual records.
Technologies · .NET MVC · SQL Server · Power BI
Read full case study
Business context
Staffing decisions were being made from out-of-date spreadsheets maintained by individual managers — a capability gap could stay invisible at the program level until a project was already short-staffed.
My role
Bridged HR and engineering priorities directly, keeping the delivery plan realistic against a competing set of HR reporting deadlines.
Team composition
A small engineering team paired directly with the HR stakeholders who owned the underlying staffing process — deliberately kept lean, since the harder problem was data-model alignment, not build capacity.
Strategy
Led delivery across technical and HR stakeholders, aligning the data model to how HR actually made staffing decisions rather than how the system happened to store records.
Risks managed
The risk that mattered most was HR not trusting the new system enough to retire their spreadsheets — addressed by validating the data model against real staffing decisions before rollout, not after.
Key decisions
Prioritized matching HR's existing decision process over a technically cleaner data model — the less elegant choice, but the one that got the system actually adopted instead of running in parallel with the old spreadsheets.
Lessons learned
A system HR stakeholders trust for staffing decisions needs to match their existing decision process, not just digitize the old spreadsheet.
HRMS Digitalization
Digitized hiring, promotions, resignations, interviews and reviews — reducing manual effort and turnaround by 25%.
Bid Advisory & Commodity Hedge Management
Gave the finance function real-time visibility into bid advisory requests, replacing status updates chased over email with a single source of truth — tightening operational control over commodity hedge decisions.
eClaim — Expense Management
Replaced manual expense scrutiny with an automated submission-to-approval workflow — cutting processing time across operations and freeing finance staff from line-by-line manual review.
AI leadership
AI-augmented delivery, built on real foundations.
A deliberate bet on where enterprise delivery is heading — not AI hype. I'm formally trained, building hands-on, and positioning my delivery org to lead the shift instead of reacting to it.
Where AI meets program management
How I'm applying — and preparing to lead — AI in enterprise delivery:
- Delivery intelligence — AI-assisted status reporting, risk summarization and planning support across program artifacts.
- Engineering acceleration — governing teams that use AI coding tools responsibly: productivity with review discipline.
- Agentic workflows — studying multi-agent systems and RAG pipelines hands-on, to scope and govern GenAI initiatives credibly rather than from slideware.
- Adoption & change — the same change-management discipline that drove delivery adoption (see Steering Snapshot) now applied to AI rollout, where adoption is the whole battle.
Expertise
Seven years of building before leading.
2014–2021: enterprise applications across real estate, CRM, HR, MIS and regulated healthcare — the years that keep my delivery plans technically honest.
Enterprise application delivery
.NET Core, MVC, SQL Server systems across full lifecycles — including regulatory-compliant builds for B. Braun Medical India that cut audit preparation time by 20%.
Data & performance
HR and MIS reporting solutions with a 45% reporting-performance improvement — I know what slow queries cost a business, and what fixing them takes.
Cloud-era delivery
Azure and Azure DevOps pipelines across current programs; architecture and IT-governance forums contributor since my developer years (+25% team efficiency).
Leadership
Program & Delivery MgmtPMO & GovernanceAgile · Scrum · KanbanStakeholder MgmtRisk & RAIDVendor & SLAEstimation & MarginAI & GenAI
RAG PipelinesLangGraphAgentic WorkflowsPrompt EngineeringOpenAI APIsCloud & DevOps
AzureAzure DevOpsCI/CD PipelinesGit / TFSJiraEngineering
C# / .NET CoreSQL ServerAngularReactPythonPower BIExperience
Twelve years, one trajectory.
Engineer → mentor → program leader. Every phase compounds into the next.
NEXT PHASE · TARGET → VISION
Delivery Manager → Program Director
The trajectory this record points to
Near term: Delivery Manager / Senior Program Manager owning multi-account portfolios, client P&L conversations and AI-augmented delivery. The 3–5 year vision: Program Director — building delivery organizations, not just running programs.
JUN 2021 → JUN 2026 · LEADERSHIP PHASE
Manager — Program & Project Management
LTIMindtree · Mumbai
₹2Cr+ multi-account portfolio, 20+ engineers across .NET, Java, SQL Server and cloud (full delivery metrics under Steering Snapshot, above). Own client-sponsor relationships and steering committees across L&T Group accounts; ISO-standard governance; effort estimation and SLA management that protect delivery margin; grew engineers into module owners; HR automation cutting turnaround by 25%.
DEC 2017 → JUN 2021 · ENGINEERING PHASE
Software Developer
Innovsource Services · Mumbai
HR and MIS reporting solutions — +45% reporting performance. Mentored junior developers; contributed to enterprise architecture and IT governance forums (+25% team efficiency).
MAY 2016 → DEC 2017 · ENGINEERING PHASE
Software Engineer
SA-Techno Consulting Services · Pune
Regulatory-compliant applications for B. Braun Medical India — −20% audit preparation time; improved SLA compliance in service delivery.
APR 2014 → MAY 2016 · ENGINEERING PHASE
Software Developer
Intellect Software Solutions · Mumbai
Enterprise .NET applications for real estate, CRM, sales and marketing — the foundation of everything since.
Recognition
Certified, recognized, still learning.
Education
Certifications
All certifications are independently verifiable on my LinkedIn profile.
Awards & recognition
Insights
What I'm thinking about, in public.
A working point of view on delivery leadership, engineering depth, and AI-augmented execution — published, not just practiced.
More articles on C# Corner and answers on Stack Overflow.
Recommendations
Trusted by the teams and clients I've delivered for.
From the leaders I report to, the teams I lead, and the clients I deliver for.
What colleagues say
"He combines strong program and project management expertise with enough technical depth to support sound architectural decisions, while leading with calm and maintaining stakeholder confidence under pressure."
Leadership style
"He brings clarity, structure, and steady ownership to difficult situations, keeps teams aligned without micromanagement, and creates trust through proactive leadership."
Full recommendations available on my LinkedIn profile.
Contact
Open to delivery and program leadership opportunities.
Open to Delivery Manager, Senior Program Manager and Technical Program Manager roles — especially enterprise transformation, delivery governance and AI-enabled execution.
Reach me directly
Mumbai, India · Open to relocation — India and GCC
Next step
Send a message about a delivery leadership role, or take the résumé with you. I reply within one business day.
Prefer email? Write directly to surajkumar.navodya@gmail.com.
Prefer LinkedIn? Connect with me there.
- Open to Delivery Manager, Senior Program Manager and Technical Program Manager roles.
- Strong fit for enterprise transformation, PMO and governance, client-facing delivery, and AI-enabled execution.