Senior AI Engineer

Job Title

Senior AI Engineer

Location

- Viman Nagar, Pune

Experience- 6+ Years

Timings

-11 am to 8 pm

Mode

- Hybrid Model

Be part of the AcquireX team that unleashes the power of leading-edge technologies to help improve e-commerce processes in the hardware world.

Job Description

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Key Responsibilities

Work on the Full GenAI Stack

Build and optimize full-stack applications using spec- driven development, Next.js, TypeScript, Python, Node.js, .NET, and managed services such as Azure OpenAI.

Develop AI Systems

Design, develop, and deploy sophisticated AI systems, including Retrieval-Augmented Generation (RAG), to power next-generation search and discovery experiences.

Develop and Fine-Tune LLMs

Build and optimize generative AI models for automated content creation, summarization, and metadata enrichment.

Implement LLMOps

Establish robust observability using tools such as OpenTelemetry and Prometheus, tracking latency, cost, accuracy, hallucinations, toxicity, and data drift.

Backend Development

Develop scalable backend services, REST APIs, and integrations using Python, Node.js, and .NET to support AI-powered applications.

Database Management

Design, integrate, and optimize databases for efficient data storage, retrieval, and processing across AI and full-stack applications.

Must-Have Skills

Programming Languages

Strong proficiency in Python for AI/ML development, LLM integration, automation, and backend development.

Backend Technologies

Experience with Node.js and .NET for developing scalable backend services, REST APIs, and enterprise application integrations.

Full-Stack Development

Hands-on experience with Next.js, TypeScript, and modern web application development.

Production LLM Experience

Experience in full-stack development 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.

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.