Job DescriptionWe're seeking an exceptional AI Software Engineer to build and scale enterprise AI applications end to end from database to UI. In this role, you'll work with cutting-edge LLM technology, RAG systems, and production ML infrastructure, combining full-stack development expertise with hands-on AI/ML engineering to ship intelligent systems that deliver real business value at scale. You'll be a key technical contributor, shipping production-ready AI features that users love while ensuring reliability, performance, and cost-effectiveness.
Key Responsibilities:- Design and implement end-to-end RAG (Retrieval-Augmented Generation) pipelines for intelligent document search and question-answering across enterprise knowledge bases.
- Build production-ready integrations with leading LLMs (GPT-4, Claude, Gemini) for accurate, contextual responses to user queries.
- Develop prompt engineering strategies and evaluation frameworks to ensure consistent, high-quality AI outputs.
- Create agent systems with tool integration capabilities that can autonomously complete complex tasks.
- Implement vector search solutions using Pinecone, Weaviate, or similar technologies for semantic similarity and knowledge retrieval.
- Build scalable backend services using Python/FastAPI with type-safe APIs, authentication, and robust error handling.
- Develop responsive, performant frontend applications using React/Next.js with real-time streaming for LLM responses.
- Design and optimize database schemas across PostgreSQL, MongoDB, and Redis to support high-throughput AI workloads.
- Implement WebSocket servers and event-driven architectures for real-time user experiences.
- Create comprehensive testing strategies covering unit, integration, and end-to-end tests.
- Deploy and manage ML/AI services using Docker containers and Kubernetes orchestration.
- Build and maintain CI/CD pipelines for rapid, safe deployment of AI features.
- Implement infrastructure as code using Terraform to manage cloud resources (AWS, Azure, or GCP).
- Set up monitoring and observability using Datadog, Prometheus/Grafana, and LLM-specific tools (LangSmith, Weights & Biases).
- Optimize costs through intelligent caching, batching strategies, and model selection algorithms.
- Ensure enterprise-grade security through authentication, authorization, secrets management, and compliance measures.
Qualifications- Expert-level proficiency in Python with modern frameworks (FastAPI, Flask).
- Strong TypeScript/JavaScript skills with deep React and Next.js experience; proven track record designing and building RESTful and GraphQL APIs.
- Solid understanding of relational (PostgreSQL, MySQL) and NoSQL (MongoDB) databases.
- Experience with authentication systems (OAuth2, JWT, SSO) and security best practices.
- Proven track record of shipping high-quality, scalable software to production.
- Hands-on experience building and deploying AI/ML applications in production environments.
- Deep understanding of LLM integration, prompt engineering, and context managemen.
- Proven expertise with RAG systems, including document processing, chunking, embedding, retrieval, and generation.
- Experience working with vector databases (Pinecone, Weaviate, Chroma, FAISS, or Qdrant).
- Strong grasp of semantic search, similarity algorithms, and hybrid search techniques.
- Knowledge of evaluation frameworks for assessing AI system quality and performance.
- Production experience with Docker containerization and Kubernetes orchestration.
- Strong knowledge of at least one major cloud platform (AWS, Azure, or GCP) and its AI services.
- Experience building CI/CD pipelines for ML/AI application.
- Proficiency with infrastructure as code tools (Terraform, CloudFormation, Pulumi).
- Understanding of monitoring, logging, and alerting best practices; cost optimization experience for cloud and AI workloads.
- Strong computer science fundamentals and algorithmic thinking.
- Proficiency with Git workflows, code review practices, and collaborative development.
- Excellent debugging and problem-solving skills.
- Clear technical communication and documentation abilities.
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