GenAI Engineer Resume: Feedback Request

A GenAI engineer with 3.6 years of experience building production AI systems is seeking resume feedback to better frame achievements for LLM-centric roles, targeting positions in India or remote UAE jobs. The engineer wants to emphasize deployment and scalability over prompting, and avoid being seen as an 'AI wrapper' in a saturated market.

GenAI Engineer Resume: Feedback Request 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. Next Replication Lag → /en/threads/3314/ All Replies （4） Z Are you using RAG or fine-tuning for the production systems you mentioned? 0 A Had to rewrite my bullet points to focus on latency and costs to actually get interviews. 0 R That's a huge point. Most people just list tools, but showing you can actually optimize for production is key. 0 J try adding specific tokens/sec or cost savings numbers, that usually catches a recruiters eye. 0