Senior AI Solutions Engineer; Engineer Senior

Senior AI Solutions Engineer (Engineer Senior)

Location:

This role requires associates to be in-office 1-2 days per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace. Ideal candidates will be able to report to our Pulse Point location in Atlanta, GA. Alternate locations may be considered if candidates reside within a commuting distance from an office.

Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law.

The Senior AI Solutions Engineer (Engineer Senior) 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. Also responsible for delivery of end-to-end application, system development and maintenance on complex multi technology platforms within assigned client group, business unit or corporate department and utilizing various customer technology platforms.

• 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 proposes 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‑size 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.

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

• Masters or PhD preferred.
• Advanced Python skills for machine learning and data processing preferred.
• Experience across the full ML lifecycle (development, deployment and monitoring) preferred.
• Hands‑on experience with LLMs, embeddings, RAG, or modern NLP techniques using vector search technologies like Open Search preferred.
• Experience building production AI systems (APIs, pipelines, microservices)…