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:\-**

• *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.