Senior Solutions Engineer in United

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.

• Requires an BA/BS degree in Information Technology, Computer Science or related field of study \n

• Minimum of 5+ years related experience; multi-dimensional platform experience; Minimum \n

• 3+ years of hands-on AI/ML experience \n

• Experience with business and technical applications \n

• Or a combination of education and experience, which would provide an equivalent background. \n, * Masters or PhD . \n

• Advanced Python skills for machine learning and data processing . \n

• Experience across the full ML lifecycle (development * deployment * monitoring) . \n

• Hands-on experience with fine tuning SLMs, LLMs, embeddings, RAG, or modern NLP techniques using vector search technologies like OpenSearch . \n

• Experience building production AI systems (APIs, pipelines, microservices) . \n

• Experience designing evaluation frameworks for ML/LLM systems . \n

• Familiarity with responsible AI principles (fairness, explainability, privacy) . \n

• Experience with cloud-based ML platforms and scalable architectures (AWS Bedrock, or equivalent AI model cloud providers) . \n

• Healthcare domain experience, including familiarity with data privacy and regulatory requirements . \n

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• Maintains active relationships with product, data, engineering, architecture, and business teams to translate business problems into scalable AI/ML solutions. \n

• 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. \n

• Owns the change request process and may coordinate with other teams as necessary. \n

• Provides technical advice and weighs in on technical decisions that impact cross-functional teams, including AI/ML and advanced analytics solutions. \n

• Researches and may propose new technologies, keeping abreast of developments in AI and applying them to enterprise use cases where relevant. \n

• Designs, builds, and deploys end-to-end ML and LLM-based systems (data pipelines, models, prompts, APIs, and monitoring). \n

• Develops, evaluates, deploys, and monitors machine learning models for predictive, classification, optimization, personalization, and decision-support use cases. \n

• Builds applied AI solutions such as semantic search, RAG pipelines, and embedding-based systems. \n

• Develops production-ready AI/ML services, APIs, pipelines, and reusable components; improves performance, scalability, reliability, usability, and operational readiness in production. \n

• Performs technical design reviews and code reviews; provides technical leadership through solution design, best practices, troubleshooting, and mentoring junior team members. \n

• Assesses status and supports data information planning. \n

• Coordinates on-call support and ensures effective monitoring of systems, including AI/ML model performance and reliability. \n

• Mentors others and may lead multiple or small to medium-sized projects; influences engineering standards and technical direction. \n

• Identifies and proposes strategies around technical problems affecting the team, communicates standards, and gains buy-in on solutions. \n

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