Lesson 14 — IT Roles & Open Source

Who does what; the open-source ecosystem; how to enter; which course to take next.

IT Landscape Module 5 Course Finale

Roles are clouds, not boxes

• Same person, different title depending on company size and culture.
• Hold the titles loosely — use them to know what to search for, not to box yourself in.

The engineering job-family map

As of 2026 — titles drift; the work is what matters.

The data and AI job-family map (as of 2026)

• Data Engineer — pipes data around (Airflow, dbt, Spark, Kafka).
• Data Analyst — asks questions of data (SQL, dashboards).
• Data Scientist — builds statistical / ML models in notebooks.
• ML Engineer — puts models into production.
• AI Engineer — new — builds with LLMs, RAG, and agents.
• Research Scientist — academia-adjacent.

The “around engineering” roles

• Product Manager — what to build, for whom, why.
• Designer — UX, UI, research.
• Engineering Manager — people + delivery.
• Tech Lead — people-light, technical-direction-heavy.
• Solutions / Sales Engineer — technical, customer-facing.
• Developer Advocate — community-and-content-facing.
• Technical Writer · QA / Test Engineer.

Security as its own world

• Defensive (Blue Team) — SOC analyst, threat hunter, incident responder.
• Offensive (Red Team) — penetration tester, security researcher.
• Governance, Risk & Compliance (GRC) — risk, compliance, audit.
• AppSec / Cloud Security / OT Security — specializations.

Increasingly its own career ladder, not a stop on the engineering one.

Open source — what it actually is

• Most of the software you use is built on it.
• Every cloud, every browser, every database you’ve met in this course sits on a tower of open-source pieces.

Why open source exists (and why it works)

• Dogfooding — maintainers volunteer because they need the tool too.
• Corporate backing — many are paid by their employers to work on tools their employers use: Linux, Kubernetes, Postgres, Python, the LLVM compiler — all overwhelmingly maintained by paid engineers at large companies.
• Foundations — Linux Foundation, Apache, CNCF, Python Software Foundation, Mozilla.

Money + identity + meritocracy + accumulated trust.

Open-source licenses (the 30-second version)

• MIT / Apache — very permissive; use however you want, even closed-source.
• GPL — you must share changes back if you redistribute.
• AGPL — same, even if you only use it as a network service.
• BSL / SSPL — newer “source-available”; not strictly open source; vendor protection.

How to “enter” IT without a CS degree

1. Pick one role from slides 3–6 that looks interesting.
2. Read its job-ad language until it stops feeling foreign.
3. Ship something tiny in public — a GitHub project, a blog, a tool, a Substack.
4. Contribute a one-line fix to a small open-source project.

Which course on this platform next?

The course, in three bullets

• You now have a map of IT (L01) — frontend / backend / data / infra / security all on one page in your head.
• You’ve seen what the tools actually look like (L05) — IDEs, GitHub, AI assistants — and know the words on a job description aren’t magic.
• You’ve watched AI become a real seat at the table (L11) — and you know which sibling course to take to actually build with it.

The end — and the start.