MSc, Engineering Project Management
The University of Manchester
Systems thinking across technology, people, risk and strategic delivery.
Technical Programme Leadership · Complex Systems · Applied AI Thinking
Technical Programme Manager · UK
HasithReddy
£5.5M+Programme value
25+Global client engagements
09Years
VR & XRHealth TechAutonomous RoboticsMedical DiagnosticsEnterprise Software
I lead complex technical programmes with product judgement, in industries where reliability, safety and good decisions matter.
01 — Experience
My career didn't move across industries by chance. Each role exposed me to more complex products, greater technical ambiguity and higher-stakes decisions. From enterprise software to biotechnology, autonomous robotics and immersive healthcare, every step expanded how I think about building products, aligning teams and delivering outcomes.
02 — Capabilities
The operating range behind nine years of complex product and programme delivery.
Tools
- Figma
- GitHub
Tools
- Jira
- Confluence
- MS Project
- ProofHub
Tools
- AWS
- SQL
- Power BI
- Tableau
- ChatGPT
- Claude
- Codex
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Tools
- Figma
- GitHub
03 — How I Work
Five principles that guide how I turn ambiguity into decisions, products and measurable outcomes.
Before building anything, I define the decision that needs to be made, who owns it, and the constraints that shape it. Clear decisions produce better products than premature solutions.
Before building anything, I define the decision that needs to be made, who owns it, and the constraints that shape it. Clear decisions produce better products than premature solutions.
Technology never exists in isolation. Regulation, user behaviour, commercial reality and organisational incentives shape every successful product as much as engineering does.
I work across customer needs, commercial priorities, technical teams and operations—turning different perspectives into clear decisions and coordinated delivery.
Execution is a system that can be designed, measured and continuously improved. Better planning, feedback loops and visibility reduce friction long before deadlines become problems.
Frameworks are useful only when they improve outcomes. I keep the practices that create measurable value and discard those that exist for process alone.
Read the full principlesLong-form thinking, examples and the reasoning behind each approach.
04 — Applied AI Thinking
Four self-directed studies in how AI should behave when real organisations depend on it.
Each works a problem end to end: where the system earns trust, where a person stays in the loop, and what it must refuse to do. Studies rather than shipped products — the reasoning is the artefact.
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05 — Education & Credentials
Education
BTech, Mechanical Engineering
JNTU, Anantapur
Ideal Student of Talent and Excellence.
ISTE Recognition · 2016Credentials
- IBM AI Product ManagementIBM · 2025
- Lean Six Sigma Black BeltSix Sigma Academy · 2024
- AWS Certified Cloud PractitionerAmazon Web Services · 2024
- Project Management Professional (PMP®)Project Management Institute · 2022
- Professional Scrum Master™ I (PSM I)Scrum.org · 2022
IBM AI Product ManagementIBM · 2025
Lean Six Sigma Black BeltSix Sigma Academy · 2024
AWS Certified Cloud PractitionerAmazon Web Services · 2024
Project Management Professional (PMP®)Project Management Institute · 2022
Professional Scrum Master™ I (PSM I)Scrum.org · 2022
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