Python AI Engineer

Healthcare Domain

Position Summary

As a Forward Deployed Engineer within Converge for Healthcare, you will collaborate directly with clients, the broader Health Care consulting practice, and Converge Health’s product and engineering teams. Together, you will develop Data Studio’s agentic use cases—starting with the agentic and analytics platform and its unified healthcare data foundation—and bring them into production-scale capabilities within each client’s environment. This work will support improvements in provider and payer performance across financial, clinical, and operational domains.

This is a techno-functional role that combines strong technical expertise with deep healthcare domain knowledge. You will apply both to tailor agentic capabilities to each client’s workflows, data, and unique nuances. You will act as an essential connector between client delivery, applied engineering, and product development—working with clients and healthcare consulting teams throughout the full lifecycle. You will also partner with Converge for Healthcare’s product and engineering teams to convert real-world insights into repeatable solutions and platform enhancements.

The role leverages healthcare breadth rather than focusing on a single specialty. It spans both provider and payer areas—covering revenue cycle and clinical operations, network strategy, actuarial, and more.

Work you'll do:

• Presales & solution shaping: Collaborate with Health Care consulting teams and Converge for Healthcare’s account and product teams throughout the sales cycle. Lead technical discovery, demos, and use-case fit assessments to validate client needs and define a credible route to production value.
• Agentic use case development: Build agentic use cases on Data Studio in close partnership with clients. You will sometimes adapt and extend Deloitte’s library of proven use cases, and other times create greenfield solutions to address client-specific challenges—engineering for durable, production-scale capabilities instead of one-off demonstrations.
• Data readiness for agentic use cases: Determine the data and context each agentic use case requires to perform reliably. Verify that the unified data foundation can support those needs, and work with data engineering and client teams to close any gaps. You will own what the use case needs to work, rather than the underlying pipelines that feed the foundation.
• Client enablement & value realization: Provide support for client training, onboarding, and adoption activities. Stay engaged after launch to identify expansion opportunities based on real usage.
• Field-to-product feedback: Identify recurring client needs, data patterns, and delivery learnings, then translate them into specific agentic capability requests and reusable enhancements for product and engineering teams.

The successful candidate would possess these skills:

• Techno-functional profile—strong technical capability paired with deep healthcare domain fluency—using both to adapt agentic solutions to real client workflows
• Broad healthcare domain knowledge across provider and/or payer areas (e.g., revenue cycle, clinical operations, network strategy, or actuarial) with the ability to apply it across multiple domains rather than focusing on a single specialty
• Strong hands-on engineering skills, including proficiency in Python and SQL, plus comfort working with APIs, data integration patterns, and cloud services (e.g., AWS) to build and deploy production-grade capabilities in client environments
• Hands-on experience designing, adapting, or hardening agentic workflows—including multi-agent coordination, tool invocation, and memory/state management—using modern agent frameworks, along with the judgment to drive a working use case to a production-grade client deployment
• Practical knowledge of the retrieval and knowledge layers supporting agentic systems—RAG pipelines, embeddings and vector stores, and increasingly knowledge graphs—understanding how to ground use cases in large volumes of unstructured healthcare data (e.g., clinical notes, payer policies, contracts) alongside structured sources
• Intellectual curiosity and a strong interest in emerging capabilities—tracking the evolution of agentic frameworks, tooling, and techniques, and rapidly adopting new approaches in a space where the current stack may differ significantly in six months
• Client-facing credibility to translate technical trade-offs and constraints into clear business decisions, including the ability to hold both technical and executive conversations within the same engagement
• Judgment to size each engagement—knowing when an agentic use case can be reused with light configuration, when it requires substantial extension, and when a client problem calls for building greenfield
• Strong understanding of healthcare data and data standards (e.g., claims, remittances, EMR data, HL7, FHIR, X12 EDI), with the ability to reason through data quality and business context
• Comfort supporting commercial and sales-adjacent efforts such as demos, use-case fit assessments, and solution qualification, alongside post-sale delivery and value realization
• Ability to build trust and maintain durable working relationships quickly with client stakeholders and account teams in primarily virtual and distributed delivery settings
• Excellent written and verbal communication skills, including the ability to create client-facing materials, lead technical discovery sessions, and collaborate effectively across distributed teams and international time zones

Qualifications

Required:

• Bachelor's degree in Computer Science, Information Systems, Engineering, Health Informatics, or a related technical discipline
• 4+ years of experience in software engineering, solution deployment, data engineering, or client-facing technical delivery roles
• 2+ years of experience with SQL and/or Python

Preferred:

Master's degree in Computer Science, Engineering, Information Systems, or a related technical discipline