GEN AI ENGINEER

Job Title: GEN AI ENGINEER Experience: +5 Years Location: Remote (U.S. Working Hours) Start: Immediate purpose of the job We are seeking an AI/ML Engineer who will play a key role in designing, developing, and integrating intelligent AI solutions across our platform. The role involves working on a variety of AI initiatives — from model experimentation and fine-tuning to building intelligent agents and retrieval-augmented generation (RAG) systems. You will collaborate closely with cross-functional teams to bring AI capabilities into production and ensure seamless integration within our orchestration and application layers. Responsibilities Design, implement, and optimize AI agents leveraging frameworks such as LangChain, LlamaIndex, or Haystack. Build and maintain RAG (Retrieval-Augmented Generation) pipelines combining LLMs, embeddings, and vector search. Develop and fine-tune ML and NLP models for internal use cases, work with vector databases and design efficient retrieval workflows. Collaborate with other product teams to integrate AI components into the orchestration layer and business systems. Implement APIs and microservices that expose AI functionalities for broader system use. Experience of context & prompt engineering, model evaluation, and response optimization. Evaluate, benchmark, and monitor models using standard metrics and observability tools. Stay up to date with the latest trends in AI frameworks, LLMs, and orchestration technologies. Job Requirements Education & Experience 5+ years of experience in Product development and AI/ML or NLP solution development. Strong coding proficiency in Python with practical experience in libraries like FastAPI, Pandas, PyTorch, TensorFlow, or Transformers. Experience with LLM frameworks and strong understanding of retrieval systems, embeddings, and vector databases. Hands-on experience with RESTful API development, microservices, and containerized deployments (Docker/Kubernetes). Familiarity with cloud AI services such as GCP Vertex AI (preferred) or AWS Bedrock, Azure OpenAI etc.. Exposure to data pipelines, preprocessing, and production-grade model deployment. good to have skills Experience building multi-agent systems or orchestrated AI workflows. Familiarity with MLOps, CI/CD, and model lifecycle management. Contributions to open-source AI/ML projects or custom toolkits. Understanding of monitoring, cost optimization, and performance tuning for AI workloads.