Join a global health optimization organization focused on leveraging technology to improve lives. This role offers the chance to significantly impact health outcomes by connecting individuals with essential care, pharmacy benefits, and resources. You'll be part of an inclusive culture with talented colleagues, comprehensive benefits, and substantial career development opportunities. Help us advance health on a global scale and experience a culture of caring, connecting, and growing together.

As a Senior AI/ML Engineer, your primary responsibility is to align with employment contracts, company policies, and directives. This includes adapting to potential changes in work locations, teams, shifts, benefits, work environment, and alternative work arrangements. The company reserves the absolute discretion to modify or rescind these policies and directives as needed.

Key duties involve implementing cutting-edge AI/ML solutions. This includes hands-on experience with Generative AI, fine-tuning Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) architectures. You will also develop enterprise-level agentic solutions using open frameworks like Langgraph, Google ADK, or CrewAI. Expertise in vector databases, embeddings, Document AI, OCR, and structured data extraction is crucial. A deep understanding of both open-source and proprietary LLMs, along with NLP literature and relevant repositories, is expected. You will also utilize UI tools like Streamlit or Flask, and work with APIs and Docker containers.

We are seeking candidates with a minimum of 10 years of experience in AI/ML roles, holding a Bachelor's degree or higher in Computer Science Engineering. A proven track record of implementing real-world projects using Gen AI, fine-tuning LLMs, and RAG is essential. Experience in building enterprise-level agentic solutions with frameworks like Langgraph, Google ADK, or CrewAI is required, alongside proficiency with vector databases/embeddings. Candidates must have experience with Document AI, OCR, extraction solutions, and creating structured outputs. A strong understanding of both open-source and OpenAI LLMs and RAG architecture is necessary.

Familiarity with NLP literature, thrust areas, conference venues, and code repositories is expected. You should be comfortable with UI tools like Streamlit, Flask, FAST APIs, REST APIs, and Docker containers. Proficiency in Python, PyTorch, SQL, and other data analysis/modeling languages, with at least 5 years of specific Python experience, is mandatory. Experience with libraries like the OpenAI API is required, as is proficiency with cloud platforms such as Azure, AWS, and GCP. A demonstrated ability to implement multiple machine learning and AI techniques, including supervised, unsupervised, reinforcement learning, deep learning, and NLP, is key. Proven experience deploying and utilizing LLMs effectively, coupled with excellent analytical and problem-solving skills, is vital. A strong product mindset, with the ability to engage directly with business stakeholders, gather requirements, design solutions, and take ownership of end-to-end delivery, is highly valued.