Senior AI Solutions Engineer /Sr AI ML Specialist

The Senior AI Solutions Engineer /Sr AI ML Specialist **(will build and scale intelligent systems that improve healthcare outcomes. You will design, build, and deploy machine learning and LLM-based systems, taking models from experimentation to production within assigned client group, business unit or corporate department and utilizing various customer technology platforms.

How You Will Make an Impact: Maintains active relationships with product, data, engineering, architecture, and business teams to translate business problems into scalable AI/ML solutions.

• Applies AI/ML capabilities and modern AI tools to solve meaningful business problems, improve healthcare outcomes, and enable practical adoption across business workflows, digital products, and enterprise applications.
• Owns the change request process and may coordinate with other teams as necessary.
• Provides technical advice and weighs in on technical decisions that impact cross-functional teams, including AI/ML and advanced analytics solutions.
• Researches and may propose new technologies, keeping abreast of developments in AI and applying them to enterprise use cases where relevant.
• Designs, builds, and deploys end-to-end ML and LLM-based systems (data pipelines, models, prompts, APIs, and monitoring).
• Develops, evaluates, deploys, and monitors machine learning models for predictive, classification, optimization, personalization, and decision-support use cases. Builds applied AI solutions such as semantic search, RAG pipelines, and embedding-based systems.
• Develops production-ready AI/ML services, APIs, pipelines, and reusable components; improves performance, scalability, reliability, usability, and operational readiness in production.
• Performs technical design reviews and code reviews; provides technical leadership through solution design, best practices, troubleshooting, and mentoring junior team members.
• Assesses status and supports data information planning.
• Coordinates on-call support and ensures effective monitoring of systems, including AI/ML model performance and reliability.
• Mentors others and may lead multiple or small to medium-sized projects; influences engineering standards and technical direction.
• Identifies and proposes strategies around technical problems affecting the team, communicates standards, and gains buy-in on solutions.

Minimum Requirements:

• Requires an BA/BS degree in Information Technology, Computer Science or related field of study and a minimum of 5 years related experience; multi-dimensional platform experience; experience with business and technical applications, or any combination of education and experience, which would provide an equivalent background.

Preferred Skills, Capabilities, and Experiences:

• Masters or PhD preferred.
• Advanced Python skills for machine learning and data processing preferred.
• Experience across the full ML lifecycle (development → deployment → monitoring) preferred.
• Hands-on experience with fine tuning SLMs, LLMs, embeddings, RAG, or modern NLP techniques using vector search technologies like OpenSearch preferred.
• Experience building production AI systems (APIs, pipelines, microservices) preferred. Experience designing evaluation frameworks for ML/LLM systems preferred.
• Familiarity with responsible AI principles (fairness, explainability, privacy) preferred.
• Experience with cloud-based ML platforms and scalable architectures (AWS Bedrock, or equivalent AI model cloud providers) preferred.
• Healthcare domain experience, including familiarity with data privacy and regulatory requirements preferred.