New Roles · Engineering AI Builders
AI Engineer. The role, the market signal, and how to build it in your org.
The most-hired AI Builder role in the market today. Builds, integrates, and ships AI features inside products and internal tools.
509 postings · 298 distinct titles · from 260,470 real job postings · see the live data →
What the market calls it
AI EngineerSr/Staff AI EngineerGenAI Engineer
Hiring this role in our corpus right now
Capitalone 108PwC 66Bosch 23Genpact 23Citi 18
What the postings ask this role to do
8,240 tasks extracted from real AI Engineer job descriptions, classified Automate / Augment / Human-only. Only 1.9% can be fully automated: companies are hiring this role for the judgment, not the keystrokes.
Automate
- Run large language model inference.
- Clean and tokenize datasets for model fine-tuning or high-quality context retrieval.
- Maintain code repositories.
- Maintain detailed records of code, testing techniques, and support activities.
- Perform day-to-day operations on vector databases (pinecone, milvus, etc.), including indexing, querying, and optimizing search retrieval.
Augment
- Leverage a broad stack of open source and saas ai technologies such as aws ultraclusters, huggingface, vectordbs, nemo guardrails, pytorch, and more.
- Design ai software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
- Develop ai software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
- Test ai software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
- Deploy ai software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Human-only
- Contribute to the technical vision and the long term roadmap of foundational ai systems at capital one.
- Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver ai-powered products that change how our associates work and how our customers interact with capital one.
- Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver ai-powered products.
- Invent and introduce state-of-the-art llm optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ai systems.
- Contribute to the technical vision for foundational ai systems.
How we build it in your org
From the market's version of this role to your version of it
1. Audit the work
Start Your Audit maps the tasks this role would own in your operation and classifies each one: what AI runs, what your people run with AI, what stays human.2. Define your version
Your team composes the job description for your org's variant of the role, grounded in the audited tasks rather than a copied template.3. Make people ready
A learning plan built from that job description, delivered in GenAI Sandboxes with Simulations and Competency Assessments. Readiness is demonstrated, not assumed.Build your own
Compose your org's AI Engineer job description
Start from the tasks real postings ask for, keep the ones that match your operation, add what is specific to you. The tasks carry their AI classification, so the JD you take away already says what AI runs and what stays with people.
Start with the work, not the org chart.
Run the audit on one operation and see what this role would own first.