Role

Forward-deployed AI Engineer

Ships AI features inside a customer's own codebase, working closely alongside their team.

13 chaptersAbout 5–6 months15–30 min a day14 skills2 projects
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Day 1 on the Forward-deployed AI Engineer path.

What a Forward-deployed AI Engineer does

Embeds with a customer to scope their problem, prototype fast, and build an AI feature directly into their software. Blends strong coding with clear, friendly talk so the customer trusts the result.

  • Meet a customer to understand their problem and what success looks like
  • Prototype an AI feature quickly to show what is possible
  • Build the feature into the customer's own codebase and tools
  • Connect a large language model (the AI behind chat tools) to real data
  • Test the feature with the customer and fix what breaks
  • Iterate on-site as the customer uses it and gives feedback
  • Hand off clean code and notes so the customer's team can keep it running

A day in the life

  1. Join a call with the customer to clarify the problem and goals
  2. Read the customer's codebase to learn how it fits together
  3. Prototype a feature with an AI model, then demo it live
  4. Debug a broken integration using logs and the customer's data
  5. Gather feedback on-site and reshape the plan for tomorrow
  6. Write a short update and a clear handoff for the customer's team

Tools you will use

Languages: Python, TypeScript, JavaScriptAI models and APIs: OpenAI, Anthropic, open-source modelsAI app frameworks: LangChain, LlamaIndex (tools that wire models into apps)Vector databases: Pinecone, pgvector (stores that find similar text)Version control: Git, GitHubCloud platforms: AWS, Azure, Google CloudContainers: DockerNotebooks and demos: Jupyter, Streamlit

Your plan

Chapter by chapter.

1~2 wks

See the work of a Forward-deployed AI engineer

StartFree
2~2 wks

Customer engagement and delivery

Skills
3~2 wks

Architecture write-up: explain a system you built

Proof
4~2 wks

Adapting under pressure

Skills
51–2 wks

Meet people doing the work

People
6~2 wks

LLM and AI engineering skills

Skills
7~2 wks

Checking AI output quality

Skills
8~2 wks

Coding and debugging craft

Skills
9~2 wks

Working with APIs

Skills
10~2 wks

Build an AI feature: a RAG app, an LLM gateway, or a guardrail layer

Proof
111–2 wks

Prepare for Forward-deployed AI engineer interviews

Interview
121–2 wks

Choose your route into Forward-deployed AI engineer work

Decide
13on your timeline

Apply for Forward-deployed AI engineer roles

Apply

By the last chapter

This is what you can show.

Things you've made

Architecture write-up: explain a system you built and Build an AI feature: a RAG app, an LLM gateway, or a guardrail layer

Skills you can prove

14 skills, each rated on work you actually did.

People you've talked to

3 people who do the job, with a message ready for each.

Questions you can answer

17 interview questions and a mock interview, with feedback.

Credentials

8 credentials compared, so you can pick one, or decide you don't need one. None is required.

Ways in

There is more than one route.

Ways to study

  • Bachelor degree in computer science, software engineering, or related field
  • Coding bootcamp focused on software development or applied AI
  • Diploma or certificate in programming with strong project work
  • Self-taught path with online AI courses plus a deployed portfolio

How people get their first job

  • Build 2 to 4 small AI apps that solve a real problem, with clear README files
  • Apply for engineering internships at AI-native startups
  • Start as a software engineer and take on customer-facing project work
  • Contribute to open-source AI tooling to learn how models plug into apps
  • Join a hackathon and ship a working AI demo in a weekend

Life skills on this path: Networking · Job interviews · Job search

How the work is changing

What AI is doing to this role

How AI is changing this role · one of 6 tasks we track

Learn the customer's codebase fast

Sped up a lot

What AI does

Cursor and Claude Code explain unfamiliar code and map it in minutes.

Still yours

Spotting the risky assumptions hiding in their system stays with you.

Reviewed September 2026

In the app · Premium

The rest is in the app

  • How AI affects the other 5 tasks
  • Whether this job is growing or shrinking
  • How hard the first job is to get
  • Similar roles that are easier to get into
  • Updated every month, with sources
See it in the app →

How we rate a job →

Already working

Already a Forward-deployed AI Engineer?

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Questions

Questions about this path

How long does it take to become a forward-deployed ai engineer with Welica?

The path is 13 chapters, 5–6 months at 15 to 30 minutes a day. You can go faster or slower; the plan moves with you.

Do I need a degree?

Not always. Common routes are bachelor degree in computer science, software engineering, or related field, coding bootcamp focused on software development or applied AI, diploma or certificate in programming with strong project work, or self-taught path with online AI courses plus a deployed portfolio.

What is free?

Chapter 1, See the work of a Forward-deployed AI engineer, is free for good. Premium unlocks the rest of the path.

Start the Forward-deployed AI Engineer path.

Chapter 1 free. About 15 to 30 minutes a day.

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