JOB DESCRIPTION :

We are seeking an experienced AI Engineer with strong expertise in Python, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Vector Databases, and end-to-end AI system development. You will design, build, and deploy AI-driven applications, leveraging state-of-the-art machine learning techniques and modern cloud technologies.

The ideal candidate is analytical, detail-oriented, and skilled in building scalable AI systems-from data ingestion and model orchestration to deployment, monitoring, and optimization.

WHAT YOU WILL DO :

- Work closely with product, engineering, and business teams to understand requirements and translate them into AI-driven solutions.

- Architect, develop, and deploy robust LLM-based applications, including custom pipelines, prompt engineering, and fine-tuning when needed.

- Build RAG systems using embedding models, vector search, and optimized retrieval pipelines.

- Design and manage Vector Databases (e.g., Pinecone, Chroma, Weaviate, Qdrant) to support scalable semantic search and knowledge retrieval.

- Develop high-quality Python applications, APIs, and automation workflows that integrate AI models into production systems.

- Implement data pipelines for ingestion, preprocessing, metadata enrichment, and evaluation.

- Optimize LLM performance, latency, cost, and accuracy through model selection, quantization, caching, and other engineering strategies.

- Deploy AI workloads to cloud platforms (AWS/Azure), including serverless and container-based environments.

- Conduct comprehensive testing, debugging, and performance tuning for AI services.

- Maintain documentation across the AI development lifecycle-design, experiments, deployment, and monitoring.

- Stay current with emerging AI research and tooling and apply best practices to enhance internal AI capabilities.

WHAT WE'RE LOOKING FOR :

Required Qualifications :

- BE/BTech degree in Computer Science, AI/ML, Information Technology, or related field.

- 4+ years of professional experience in software engineering, ML engineering, or AI application development.

- Strong hands-on experience with Python, Fast API/Flask, and microservices.

- Expertise in LLMs (GPT, Llama, Mistral, etc.) and modern AI frameworks.

- Experience building RAG pipelines, including embeddings, retrievers, chunking strategies, and context optimization.

- Proficiency with Vector Databases such as Pinecone, Chroma, Weaviate, Qdrant, FAISS, etc.

- Strong understanding of prompt engineering, model orchestration, and evaluation techniques.

- Solid experience with REST APIs, asynchronous processing, and cloud-native architecture.

- Knowledge of SQL and NoSQL databases and data modeling.

- Familiarity with CI/CD pipelines, Git, and automated testing.

- Understanding of MLOps principles, feature stores, and model deployment workflows.

- Strong debugging skills, analytical thinking, and attention to detail.

- Excellent communication and collaboration abilities.

Nice to Have :

- Experience fine-tuning or training custom LLMs.

- Knowledge of LangChain, Llama Index, or similar orchestration frameworks.

- Understanding of AWS/Azure AI services, serverless architecture, and containerization (Docker/Kubernetes).

- Familiarity with data engineering pipelines, ETL processes, and streaming frameworks.

- Experience with Generative AI for text, speech, or multimodal applications.

- Background in NLP, information retrieval, or knowledge graphs.