3.6 years of industry experience building production AI systems is a solid foundation, but the jump to a dedicated AI Engineer role often requires a very specific way of framing achievements. I'm currently polishing my own profile and looking for a critical eye on how to present GenAI work without sounding like I'm just "using an API."
If anyone has experience reviewing resumes for LLM-centric roles, I'd appreciate a look. I'm trying to move away from generic descriptions and toward a more real-world, impact-driven narrative. My background is a B.Tech in Computer Science, and I'm targeting roles in India or remote positions in the UAE. Since the market is getting saturated with "AI wrappers," I want to make sure my production experience actually stands out to hiring managers.
I'm specifically looking for a deep dive into a few areas:
Technical Framing: Am I highlighting the right parts of the AI workflow? I want to emphasize deployment and scalability over just "prompting."Red Flags: Are there gaps in my stack or phrasing that make me look like a beginner despite the years of experience?Job Hunting: Any specific strategies for finding high-quality LLM agent or GenAI roles that aren't just flooded with 1,000+ applicants on LinkedIn?
If anyone has experience reviewing resumes for LLM-centric roles, I'd appreciate a look. I'm trying to move away from generic descriptions and toward a more real-world, impact-driven narrative.
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All Replies （4） #
Z
Are you using RAG or fine-tuning for the production systems you mentioned?
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A
Had to rewrite my bullet points to focus on latency and costs to actually get interviews.
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R
That's a huge point. Most people just list tools, but showing you can actually optimize for production is key.
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J
try adding specific tokens/sec or cost savings numbers, that usually catches a recruiters eye. 0