Role Overview

We are seeking a highly skilled Senior AI/ML Developer to design, architect, and deliver enterprise-grade Generative AI solutions, with a strong focus on healthcare use cases. The ideal candidate will combine deep technical expertise in machine learning, large language models (LLMs), and software engineering to build scalable, secure, and responsible AI systems.

Key Responsibilities

AI/ML Development & Architecture

• Design and develop scalable AI/ML solutions using LLMs and other machine learning models.

• Architect and implement Generative AI systems that are scalable, resilient, and aligned with ethical AI practices.

• Work as a Subject Matter Expert (SME) for Generative AI, partnering with Product and Engineering teams.

• Develop and maintain end-to-end AI pipelines, including:

  • Data preprocessing

  • Feature engineering

  • Model training and evaluation

• Build extensible APIs and integrations to connect AI models with enterprise systems.

• Develop low-code/no-code UI/UX solutions for rapid delivery cycles.

• Design structured outputs (JSON, arrays, HTML) with nested nodes, ensuring seamless frontend/dashboard consumption.

• Implement solutions integrating LLMs (e.g., GPT models) to extract insights and deliver actionable data.

• Architect and deploy solutions on cloud platforms such as AWS, Azure, or GCP.

• Build and maintain distributed, scalable systems for AI workloads.

• Optimize models and systems for performance, scalability, and efficiency.

• Optimize generative AI models for improved accuracy and response quality.

• Develop effective prompt engineering strategies based on understanding how AI interprets data.

• Implement advanced use cases such as:

  • Retrieval-Augmented Generation (RAG)

  • Conversational systems

  • Summarization and translation

• Design solutions aligned with Responsible AI principles:

  • Fairness

  • Transparency

  • Security

  • Accountability

• Identify, assess, and mitigate risks associated with generative AI systems.

• Ensure compliance with privacy and data protection standards, especially in healthcare environments.

• Collaborate closely with cross-functional teams including Product, Data, and Engineering.

• Translate business problems into actionable AI-driven solutions.

• Create clear documentation:

  • Technical specifications

  • Architecture diagrams

  • User guides and presentations

• Contribute to best practices and standards for AI/ML development across the organization.

• Proven experience delivering at least one large-scale Generative AI solution.

• Strong hands-on experience with:

  • Machine Learning & AI (especially NLP and Generative AI)

  • Frameworks: TensorFlow, PyTorch

  • Open-source platforms: Hugging Face

• Experience working with:

  • LLMs (GPT family, DALL·E, or similar)

  • Data pipelines and ML lifecycle management

• Strong software engineering skills for deploying AI into production environments.

• Experience building APIs, system integrations, and scalable architectures.

• Solid understanding of distributed systems design.

• Experience in healthcare domain or regulated environments.

• Hands-on experience with:

  • RAG architectures

  • AI-powered dashboards and visualization tools

• Familiarity with CI/CD and DevOps practices.

• Experience designing enterprise-grade, production-ready AI systems.

• Programming: Python (preferred), SQL

• AI/ML: NLP, LLMs, Generative AI

• Frameworks: TensorFlow, PyTorch

• Tools: Hugging Face, APIs, data pipelines

• Cloud: AWS, Azure, GCP

• Data formats: JSON, HTML, structured outputs

• Version control: Git

• Strong analytical and problem-solving abilities

• Excellent communication skills (technical and non-technical audiences)

• Ability to work in fast-paced, agile environments

• Strategic thinking and solution-oriented mindset