Urgent! Lead Generative AI Engineer - Player Coach Job Opening In New Delhi – Now Hiring AcquireX
Location:
Viman Nagar, Pune
About AcquireX
Be part of the AcquireX team that unleashes the power of leading-edge technologies to help improve e-commerce processes in the e-commerce world.
Purpose
Own our Generative AI technical vision.
You will rapidly prototype and lead a dedicated team of two engineers to launch our company's first intelligent search and content automation systems.
Role Summary
We're looking for a hands-on Gen AI pioneer who can architect, code, and mentor.
This is a player-coach role where you'll be building foundational systems while guiding your team.
You will partner daily with product and engineering leadership to transform business goals into cutting-edge, shippable LLM-powered solutions.
Key Responsibilities
Architect & Build RAG Systems: Design, develop, and deploy sophisticated Retrieval-Augmented Generation (RAG) systems to power our next-generation search and discovery experience.
Develop & Fine-Tune LLMs: Lead the development of advanced generative models for nuanced tasks like automated content creation, summarization, and metadata enrichment.
Own the Gen AI Stack: Select, provision, and optimize our stack, leveraging managed services like Azure OpenAI or AWS Bedrock, or self-hosting models on GPU infrastructure.
You will establish best practices for repo structure, CI/CD, and model/prompt versioning.
Implement LLMOps: Embed robust observability using tools like OpenTelemetry and Prometheus.
This includes tracking standard metrics (latency, cost, accuracy) and specialized monitoring for hallucination, toxicity, and data drift.
Lead & Mentor: Hire, coach, and develop ML talent.
Set the standard for high-quality code, rigorous experimentation, and rapid iteration within the Gen AI domain.
Must-Have Skills
Production LLM Experience: 5+ years in Python with demonstrable success in productionizing LLM applications using modern frameworks like DSPY, LangChain, LlamaIndex, or Hugging Face Transformers.
RAG Expertise: Deep, practical knowledge of RAG architecture, including advanced prompt engineering, chunking strategies, and proficiency with vector databases (e.g., Pinecone, Weaviate, Milvus).
Cloud Proficiency: Expertise with managed LLM services (Azure OpenAI Service or AWS Bedrock).
Strong foundational cloud skills in either Azure or AWS for compute orchestration (AKS/EKS), serverless functions, and storage.
MLOps Acumen: Solid experience with Docker, CI/CD pipelines (e.g., GitHub Actions, Argo), and model registries.
Leadership & Communication: Proven ability to lead small, highly technical teams and clearly communicate complex concepts to stakeholders.
Nice-to-Have Skills
Experience with agentic workflows (e.g., AutoGen, CrewAI).
Familiarity with multi-modal models (text, image, etc.).
Knowledge of advanced LLM fine-tuning techniques (e.g., LoRA, QLoRA).
Strong SQL skills (especially with ClickHouse) and a keen eye for inference cost optimization.
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Unlock Your Lead Generative Potential: Insight & Career Growth Guide
Real-time Lead Generative Jobs Trends in New Delhi, India (Graphical Representation)
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Great news! AcquireX is currently hiring and seeking a Lead Generative AI Engineer Player Coach to join their team. Feel free to download the job details.
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An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at AcquireX adheres to the cultural norms as outlined by Expertini.
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