SENIOR AI/ML FULL STACK ENGINEER

Job Summary:

• Design, develop, and implement AI software solutions to address business needs.
• Assist the System Architect in the complete AI solution development and release lifecycle.
• Communicate with product managers, designers, data scientists, and other internal and external stakeholders to gather requirements.
• Help provide technical leadership to the software engineering team.
• Take direction from the System Architect and help lead the team through the software design, development, testing, and release cycle to deliver and support the final AI solutions on-prem or on cloud.
• Actively seek ways to improve the software development process and keep the team up to date on the latest software technologies and processes.
• Provide clear and accurate status reports to management and stakeholders as needed.
• Guide and coach members of the software engineering team.
• Responsible for designing and developing scalable AI solutions that combine large language models, retrieval systems, structured and unstructured data, cloud services, and user-facing applications.
• Build RAG pipelines, document ingestion workflows, semantic search, embeddings, prompt engineering, evaluation frameworks, guardrails, APIs, and production monitoring.
• Collaborate closely with product owners, clinical or business stakeholders, and technical teams to gather requirements, communicate tradeoffs, and deliver reliable, measurable AI solutions.

Required Skills:

• Strong Python programming and SQL experience.
• Hands-on experience building Generative AI or RAG-based applications.
• Experience with LLMs, prompt engineering, embeddings, semantic search, query expansion, and citations.
• Experience with ML/NLP model development, evaluation, and performance monitoring.
• Familiarity with LLM evaluation metrics such as answer relevance, context relevance, faithfulness, hallucination reduction, and citation accuracy.
• Experience implementing AI safety guardrails, content moderation, blocked topics, or escalation logic.
• Experience with cloud platforms such as Google Cloud Platform, AWS, or OCI.
• Experience with tools such as Vertex AI, AWS Bedrock, SageMaker, BigQuery, Snowflake, OpenSearch, Cloud Run, Docker, Airflow, Terraform, or CI/CD pipelines.
• Experience working with healthcare, claims, clinical, regulatory, life sciences, or enterprise data preferred.
• Strong communication skills and ability to work with both technical and non-technical stakeholders.

Education Requirements:

• Bachelor’s degree required in Computer Science, Data Science, Engineering, Biomedical Engineering, Statistics, Applied Mathematics, or a related technical field.
• Master’s degree or higher preferred in Data Science, Computer Science, Biomedical Engineering, Artificial Intelligence, Machine Learning, Engineering, or a related field.
• Relevant certifications or coursework in Generative AI, Machine Learning, Cloud AI platforms, Data Science, or MLOps are preferred.