Senior AI Engineer

AcquireX; Pune District; On-site; INR 2,000,000 - 3,000,000; Full time

Job summary

AcquireX is looking for a Gen AI pioneer based in Pune District, India, to lead the development of cutting-edge LLM-powered solutions and architect Retrieval-Augmented Generation (RAG) systems. The ideal candidate will have over 5 years of experience in production LLM applications using modern frameworks, strong cloud proficiency, and the ability to mentor a small team of engineers. This role requires hands-on leadership, innovation, and solid technical skills to advance our AI vision.

Qualifications

• 5+ years in Python with experience in productionizing LLM applications.
• Deep knowledge of RAG architecture, including advanced prompt engineering.
• Expertise with managed LLM services like Azure or AWS.

Responsibilities

• Architect and build Retrieval-Augmented Generation systems.
• Develop and fine-tune generative models for content tasks.
• Lead and mentor a team of engineers for high-quality output.

Skills

Production LLM Experience

RAG Expertise

Cloud Proficiency

MLOps Acumen

Leadership & Communication

Tools

DSPY

LangChain

LlamaIndex

Hugging Face Transformers

Azure OpenAI Service

AWS Bedrock

Docker

Job description

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.