About the role
We are seeking an AI/ML Engineer with a strong blend of full-stack software engineering and applied AI expertise to design, build, and optimize generative AI-powered applications. The role involves developing scalable AI solutions, integrating LLMs into enterprise applications, implementing agentic workflows, and delivering secure, production-grade solutions that drive business value.
Responsibilities:
- Develop and enhance AI-powered features such as chatbots, summarization, knowledge search, and data extraction using LLMs.
- Design and implement RAG (Retrieval-Augmented Generation) solutions, including data preprocessing, embeddings, vector search, and retrieval optimization.
- Build and integrate AI services using OpenAI, Azure AI, and open-source LLMs.
- Develop agentic AI workflows, multi-agent frameworks, and intelligent automation solutions
- Improve model performance, reliability, and accuracy through prompt engineering, evaluation, guardrails, and fine-tuning techniques.
- Work with vector databases such as FAISS, Pinecone, and pgvector.
- Optimize AI applications for latency, throughput, scalability, and cost efficiency using caching, batching, quantization, and model optimization techniques.
- Collaborate with product, data, and engineering teams to deliver high-quality AI solutions.
- Participate in architecture discussions, code reviews, and knowledge-sharing initiatives.
Requirements:
- Preferred Skills: MLOps, React JS, Java Backend, CI/CD for ML, model monitoring, lifecycle management, Kubernetes, Docker, and JFrog.
- Experience deploying ML models to production environments.
- Distributed ML and scalable data platforms (e. g., Spark).
- Multimodal AI, including Computer Vision and Speech Recognition (ASR).
- Knowledge of AI governance, responsible AI, security, compliance, and model lifecycle management.
- Experience in healthcare, life sciences, payer/provider, or other regulated industries.
- Experience leading Agile teams and collaborating across cross-functional stakeholders.