ConvergeHEALTH - Forward Deployed Engineer, Data Studio - Innovation_Delivery_Transformation

Deloitte•Tampa, FL

61d•$105,400 - $207,800•Hybrid

About The Position

This role is within Converge for Healthcare, Deloitte's industry-focused asset studio for healthcare, part of Deloitte Consulting's Innovation & Delivery Transformation (I&DT) practice. I&DT focuses on an engineering- and innovation-led approach to building, delivering, and scaling technology-enabled solutions. Data Studio is the foundational platform for Converge for Healthcare, integrating agentic AI and analytics capabilities with a unified healthcare data foundation to transform healthcare data into actionable insights and automated actions across the Converge for Healthcare product portfolio. Forward Deployed Engineers operate at the intersection of client delivery, applied engineering, and product strategy. They collaborate with account and product teams during the pre-sale phase to identify and define opportunities, and with client and delivery teams post-sale to demonstrate and accelerate agentic value. They also feed real-world learnings back into the platform roadmap. As a Forward Deployed Engineer, you will work directly with clients, Deloitte Consulting's broader Health Care consulting practice, and Converge for Healthcare's product and engineering teams. Your primary focus will be to build out Data Studio's agentic use cases, leveraging Deloitte's agentic and analytics platform and its unified healthcare data foundation. You will engineer these capabilities into production-scale solutions within each client's environment, aiming to improve provider and payer performance across financial, clinical, and operational areas. This is a techno-functional role requiring both deep technical expertise and comprehensive healthcare domain knowledge to tailor agentic capabilities to specific client workflows, data, and unique circumstances. You will engage with clients and Health Care consulting teams both before and after sales, and collaborate with Converge for Healthcare's product and engineering teams to translate field experiences into reusable functionalities. The role demands a broad understanding of the healthcare sector, encompassing both provider and payer domains, including areas like revenue cycle, clinical operations, network strategy, and actuarial science.

Requirements

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
Ability to travel up to 25%, on average, based on the work you do and the clients and industries/sectors you serve.
Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future

Nice To Haves

Master's degree in Computer Science, Engineering, Information Systems, or a related technical discipline
Genuine techno-functional profile — deep technical capability paired with deep healthcare domain fluency, applying both together to adapt agentic solutions to real client workflows
Strong healthcare domain knowledge spanning provider and/or payer domains — such as revenue cycle, clinical operations, network strategy, or actuarial — with the versatility to apply it across multiple areas rather than a single specialty
Strong hands-on engineering skills, including proficiency in Python and SQL and comfort working with APIs, data integration patterns, and cloud-based services (e.g., AWS) to build and deploy production-grade capabilities in client environments
Hands-on experience designing, adapting, or hardening agentic workflows — multi-agent coordination, tool invocation, memory/state management — using modern agent frameworks, with the judgment to take a working use case to a production-grade client deployment
Working knowledge of the retrieval and knowledge layer behind agentic systems — RAG pipelines, embeddings and vector stores, and increasingly knowledge graphs — including 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 pull toward what's next — actively following how agentic frameworks, tooling, and techniques are evolving, and quick to adopt new approaches in a field where today's stack may look very different in six months
Client-facing credibility to translate technical tradeoffs and constraints into clear business decisions, carrying both technical and executive conversations within the same engagement
Judgment to size each engagement — recognizing when an agentic use case can be reused with light configuration, when it needs substantial extension, and when a client problem calls for building greenfield
Solid 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 activities such as demos, use-case fit assessments, and solution qualification, alongside post-sale delivery and value realization work
Ability to build trust and durable working relationships quickly with client stakeholders and account teams in predominantly virtual and distributed delivery environments
Excellent written and verbal communication skills, including the ability to develop client-facing materials, lead technical discovery conversations, and work effectively across distributed teams and international time zones

Responsibilities

Partner with Health Care consulting teams and Converge for Healthcare's account and product teams during the sales cycle to run technical discovery, demonstrations, and use-case fit assessments that qualify client needs and shape a credible path to production value.
Work closely with clients to develop agentic use cases on Data Studio, which may involve adapting and extending Deloitte's existing library of use cases or building new solutions to address client-specific challenges, with a focus on engineering durable, production-scale capabilities.
Define the data and context required for agentic use cases to function reliably, verify that the unified data foundation can support these needs, and collaborate with data engineering and client teams to address any gaps, taking ownership of the use case's requirements rather than the underlying data pipelines.
Support client training, onboarding, and adoption initiatives, and remain engaged post-launch to identify expansion opportunities based on actual usage.
Capture recurring client needs, data patterns, and delivery learnings, and translate them into concrete requests for agentic capabilities and reusable extensions for product and engineering teams.