Thiruvananthapuram, Kerala, India
Information Technology
Full-Time
Kapture CX
Overview
About The Role
We are looking for a Software Engineer passionate about Generative AI to join our team. You will work on building intelligent, production-grade applications using cutting-edge models like GPT, LLaMA, Claude, or open-source alternatives. This is a hybrid role that combines software engineering best practices with deep interest in AI/ML, especially LLM-based applications such as RAG, chatbots, agentic systems, and prompt engineering.
You’ll work alongside product managers, ML researchers, and engineers to deliver robust, scalable solutions with real-world impact.
Key Responsibilities
Build, deploy, and maintain LLM-powered applications using APIs or open-source models.
Implement and optimize RAG (Retrieval-Augmented Generation) pipelines.
Integrate and experiment with LangChain, LlamaIndex, and agentic frameworks.
Write production-grade code and deploy services in cloud environments (AWS, GCP, Azure).
Collaborate cross-functionally with design, ML, and backend teams.
Stay up to date with latest in GenAI: open models, prompting strategies, fine-tuning, etc.
Required Skills & Qualifications
2–4 years of experience in software development, preferably in Python or JavaScript/TypeScript.
Solid understanding of data structures, algorithms, and system design.
Experience building and deploying REST APIs or microservices.
Familiarity with GenAI concepts – LLMs, transformers, vector embeddings.
Hands-on Experience With One Or More
LangChain / LlamaIndex
OpenAI / Cohere / Anthropic / HuggingFace models
Pinecone / Weaviate / FAISS / Qdrant (vector DBs)
Nice-to-Have (Bonus Skills)
Experience working on chatbots, document Q&A, or agentic workflows.
Exposure to ML model fine-tuning or prompt optimization.
Familiarity with Docker, Kubernetes, or CI/CD pipelines.
Contributions to open-source GenAI projects.
What You'll Get
Work on real-world, AI-first products from scratch.
Exposure to state-of-the-art LLM tools and platforms.
Learn from a collaborative, hands-on engineering + ML team.
Fast-paced environment with full ownership and impact.
We are looking for a Software Engineer passionate about Generative AI to join our team. You will work on building intelligent, production-grade applications using cutting-edge models like GPT, LLaMA, Claude, or open-source alternatives. This is a hybrid role that combines software engineering best practices with deep interest in AI/ML, especially LLM-based applications such as RAG, chatbots, agentic systems, and prompt engineering.
You’ll work alongside product managers, ML researchers, and engineers to deliver robust, scalable solutions with real-world impact.
Key Responsibilities
Build, deploy, and maintain LLM-powered applications using APIs or open-source models.
Implement and optimize RAG (Retrieval-Augmented Generation) pipelines.
Integrate and experiment with LangChain, LlamaIndex, and agentic frameworks.
Write production-grade code and deploy services in cloud environments (AWS, GCP, Azure).
Collaborate cross-functionally with design, ML, and backend teams.
Stay up to date with latest in GenAI: open models, prompting strategies, fine-tuning, etc.
Required Skills & Qualifications
2–4 years of experience in software development, preferably in Python or JavaScript/TypeScript.
Solid understanding of data structures, algorithms, and system design.
Experience building and deploying REST APIs or microservices.
Familiarity with GenAI concepts – LLMs, transformers, vector embeddings.
Hands-on Experience With One Or More
LangChain / LlamaIndex
OpenAI / Cohere / Anthropic / HuggingFace models
Pinecone / Weaviate / FAISS / Qdrant (vector DBs)
Nice-to-Have (Bonus Skills)
Experience working on chatbots, document Q&A, or agentic workflows.
Exposure to ML model fine-tuning or prompt optimization.
Familiarity with Docker, Kubernetes, or CI/CD pipelines.
Contributions to open-source GenAI projects.
What You'll Get
Work on real-world, AI-first products from scratch.
Exposure to state-of-the-art LLM tools and platforms.
Learn from a collaborative, hands-on engineering + ML team.
Fast-paced environment with full ownership and impact.
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