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ConvergeHEALTH-Full-Stack Software Engineer-Innovation_Delivery_Transformation
As a GenAI Full-Stack Application Engineer within Converge for Health Care, Deloitte's industry-focused healthcare and life sciences product studio, you will design, build, and scale production-grade applications that power next-generation analytics and AI-enabled solutions. Converge for Health Care develops and operates data, analytics, and AI-driven platforms purpose-built for healthcare providers, payers, and life sciences organizations seeking to improve performance, enable better decision-making, and drive measurable clinical, financial, and operational outcomes.<br><br>In this role, you will work across modern front-end frameworks (Angular, React), backend services (Node.js and Python), and AI orchestration layers to bring innovative industry solutions to life. You will help design and deploy AI-native systems leveraging Retrieval-Augmented Generation (RAG), agentic workflows, and multi-agent architectures within secure, scalable, cloud-native environments. This role blends strong engineering fundamentals with applied GenAI and modern software craftsmanship.<br><br>This position is ideal for a proactive, curious engineer who enjoys building real systems, experimenting with emerging AI capabilities, and translating cutting-edge ideas into enterprise-ready applications.<br><br>Recruiting for this role ends on 06/02/2026.<br><br><strong>Work you'll do<br><br></strong>As a GenAI Full-Stack Application Engineer on the Converge for Health Care team, you will:<br><br><ul><li>Design and implement full-stack applications using Angular or React on the front end and Node.js and Python-based services on the backend.</li><li>Design and build agentic AI systems, including multi-agent coordination, tool invocation workflows, memory/state management, and structured reasoning pipelines.</li><li>Implement AI-powered components such as RAG pipelines, embedding workflows, vector store integrations, and orchestration layers that connect LLMs to enterprise data and services.</li><li>Deploy AI-enabled applications in AWS environments, leveraging managed services such as ECS/EKS, Lambda, S3, and Bedrock, while applying cloud-native infrastructure patterns to support scalable, production-grade systems.</li><li>Integrate and operate open-source technologies across the stack, including model serving frameworks, vector databases, orchestration libraries, and containerized infrastructure components.</li><li>Containerize and orchestrate services using Docker and Kubernetes to ensure portability, reliability, and scalability across environments.</li><li>Integrate SQL, NoSQL, and vector databases to support high-performance inference, retrieval, and analytics workflows.</li><li>Apply robust testing, logging, monitoring, and observability practices to ensure performance, reliability, and secure AI deployment.</li><li>Collaborate with product managers, data scientists, and healthcare or life sciences domain experts to rapidly prototype, iterate, and harden AI-driven capabilities.</li><li>Participate in agile delivery cycles and contribute to architecture and engineering best practice evolution across the studio.<br><br></li></ul><strong>A strong candidate would possess these skills:<br><br></strong><ul><li>Strong working knowledge of both JavaScript/TypeScript and Python in production environments.</li><li>Practical experience building and deploying cloud-native applications in AWS, with familiarity across compute, storage, API, and managed AI services.</li><li>Hands-on experience designing or experimenting with agentic systems using frameworks such as LangChain, LangGraph, CrewAI, Strands, LlamaIndex, DSPy, or similar.</li><li>Working understanding of multi-agent coordination patterns, tool integration, memory persistence, and structured reasoning workflows.</li><li>Familiarity with vector databases and embedding-based retrieval strategies in RAG architectures.</li><li>Comfort working across open-source ecosystems beyond models, including orchestration libraries, model serving stacks, vector stores, observability tooling, and modern infrastructure frameworks.</li><li>Forward-thinking engineering mindset, including embracing AI-enabled development tools (e.g., Claude Code, GitHub Copilot) as productivity multipliers.</li><li>Experience working effectively with globally distributed engineering teams across international time zones.</li><li>Strong debugging, experimentation, and system-level thinking in distributed cloud-native environments.</li><li>Familiarity with healthcare or life sciences industry concepts and data domains (e.g., claims, FHIR, EDI, remittance data, clinical datasets)</li><li>Intellectual curiosity and bias toward building, testing, and iterating quickly in ambiguous environments.<br><br></li></ul><strong>The Team<br><br></strong>Converge for Health Care is Deloitte Consulting's industry-focused asset studio for healthcare and life sciences and operates within the firm's Innovation & Delivery Transformation practice. The studio develops, scales, and operates analytics, data, and AI-enabled products designed for organizations navigating complex clinical, regulatory, operational, and financial ecosystems.<br><br>As part of this product-centric engineering organization, you will collaborate across product management, engineering, data science, and delivery teams to build scalable, enterprise-grade platforms that power real-world healthcare and life sciences solutions.<br><br><strong>Qualifications<br><br></strong>Required<br><br><ul><li>Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field</li><li>2+ years of experience building front-end applications using Angular or React</li><li>2+ years of experience developing backend services using Node.js and/or Python</li><li>1+ years of experience working with SQL and NoSQL databases</li><li>1+ years of experience containerizing and orchestrating applications using Docker and Kubernetes</li><li>1+ years of experience implementing application security controls across services and data stores</li><li>Ability to travel up to 10%, on average, based on client and project needs</li><li>Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future<br><br></li></ul><strong>Preferred<br><br></strong><ul><li>Master's degree in Computer Science, Engineering, Artificial Intelligence, or related field<br><br></li></ul>The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $88,600 to $163,100.<br><br>You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.<br><br>Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html
