Urgent! Lead Generative AI Engineer - Player Coach Job Opening In Pune – 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
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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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