AI Engineer
On-siteBengaluru, Karnataka, India
Job Summary
Design, build, and deploy AI-powered applications using Large Language Models, multimodal models, and intelligent agents to automate enterprise workflows. Develop advanced prompt engineering strategies, Retrieval-Augmented Generation pipelines, and multi-agent systems capable of reasoning and executing complex tasks. Integrate scalable inference pipelines with enterprise systems, databases, and third-party platforms while implementing robust evaluation frameworks to measure AI quality. Optimize applications for latency, accuracy, and operational efficiency through observability, monitoring, and continuous experimentation. Collaborate closely with Product, Platform, and Customer Success teams to deliver production-ready solutions that solve meaningful business problems.
Required Qualifications
- 3+ years of experience building AI, machine learning, or backend software applications
- Strong proficiency in Python with experience building production-grade applications
- Hands-on experience with Large Language Models, prompt engineering, Retrieval-Augmented Generation (RAG), and AI agent frameworks
- Experience using frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, LangGraph, or similar
- Familiarity with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or PGVector
- Experience integrating AI applications with REST APIs, databases, and cloud services
- Understanding of model evaluation, prompt optimization, hallucination mitigation, and AI quality measurement
- Experience with Docker, Kubernetes, and cloud platforms such as AWS, Azure, or GCP
- Familiarity with Git, CI/CD pipelines, and software engineering best practices
- Understanding of distributed systems, scalable APIs, and enterprise application development
Desired Qualifications
- Exposure to fine-tuning, model serving, MLOps, or inference infrastructure is highly desirable
- Experience building enterprise applications using GPT, Claude, Gemini, Llama, Mistral, or other foundation models
- Experience with vLLM, TensorRT-LLM, TGI, model deployment, GPU optimization, or inference platforms
- Experience with supervised learning, deep learning, model training, evaluation pipelines, and ML frameworks such as PyTorch or TensorFlow
- Experience integrating AI solutions with CRMs, ERPs, productivity tools, cloud platforms, and enterprise workflows
- Experience building SDKs, APIs, developer tools, or AI platform capabilities for external developers
- Founder-level ownership and bias for action
- Strong strategic thinking and ability to connect technical decisions to business impact
- Excellent communication and mentoring skills
- Thrives in ambiguity, fast-paced environments, and early-stage startup culture
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