AI Software Engineer

2 weeks ago

Chennai, Tamil Nadu, India beBeeArtificialIntelligence Full time ₹ 18,00,000 - ₹ 25,00,000
AI/ML Engineer

About the Role:

We're seeking a seasoned software engineer with expertise in Large Language Models (LLMs) and AI to join our team. This role focuses on developing, integrating, and deploying generative AI solutions into enterprise-grade software systems.

The ideal candidate brings strong software engineering fundamentals, hands-on experience with AI/ML frameworks, and the ability to design scalable, production-ready AI-powered applications.

Key Responsibilities:

  • Design & Development: Develop, integrate, and optimize applications leveraging LLMs, generative AI frameworks, and vector databases.
  • Ai Integration: Implement APIs and SDKs from platforms such as OpenAI, Hugging Face, LangChain, and LlamaIndex into production systems.
  • Prompt Engineering & RAG: Design, test, and optimize prompt strategies, embeddings, and retrieval-augmented generation workflows.
  • Data Engineering: Work with structured/unstructured datasets, SQL/NoSQL systems, and modern storage solutions to prepare data pipelines for AI applications.
  • Scalable Systems: Build performant, maintainable, and secure AI-enabled services with a focus on distributed computing and cloud-native deployments.
  • Collaboration: Work closely with product managers, data scientists, and software engineers to deliver AI-powered features aligned with business goals.
  • Evaluation & Monitoring: Apply AI model evaluation techniques to validate model performance, reliability, and fairness in real-world applications.

Required Skills & Experience:

  • Experience: 2 to 4 years in software engineering, with at least 1 year hands-on in AI/ML development and integration.
  • Programming: Proficiency in Python (preferred for AI/ML), with additional experience in JavaScript/TypeScript for frontend or service integration.
  • Ai/Ml Ecosystem: Practical experience with OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex, FAISS, Pinecone, or ChromaDB.
  • Cloud & Deployment: Familiarity with deploying GenAI applications in AWS or Azure environments.
  • Data Systems: Knowledge of relational databases (SQL), NoSQL systems, and data pipelines for AI workloads.
  • Apis & Frameworks: Strong understanding of RESTful APIs, microservices, and modern web frameworks.
  • Software Engineering: Exposure to distributed computing, system design, and building production-grade software.
  • Foundations: Bachelors degree (or higher) in Computer Science, Engineering, or a related technical field.

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