Forward Deployed Engineer

🕒 il y a 1 mois

🏖️ New Jersey – Distant

🏖️ New Jersey – Remote

💵 $200 000 - $300 000 / an

⏰ Temps Plein

🟠 Senior

🔴 Expert

👷🏻‍♀️ Ingénieur

🦅 Parrain de Visa H1B

Cette entreprise a parrainé des visas H1B par le passé.

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Brillio

Site WebLinkedInTous les Emplois

1001 - 5000 employés

🏥 Santé

🛡️ Assurance

📦 Logistique

💰 Private Equity Round en 2019-01

Healthcare • Insurance • Logistics

Brillio est une entreprise de conseil en technologie spécialisée dans la conduite de la transformation numérique pour les entreprises de divers secteurs tels que la banque, les services financiers, l'assurance, les sciences de la vie, les télécommunications et médias, la santé et le commerce de détail. Elle se concentre sur la transformation de l'expérience client, les données et l'IA, l'ingénierie de produits et plateformes, et propose des solutions d'infrastructure, de cloud et de sécurité. En mettant l'accent sur l'ingénierie de produits numériques et l'exploitation de l'IA générative, Brillio vise à fournir des solutions sur mesure qui aident les entreprises à prospérer à l'ère de l'IA et de la disruption technologique. Elle offre également des services pour aider les entreprises à s'adapter aux nouveaux défis technologiques et transformer les perturbations en avantages compétitifs.

Description

• Engage directly with business stakeholders, VPs, clinical leads, operations owners to surface ambiguous, high-value problems and translate them into buildable AI opportunities • Ask sharp questions, challenge assumptions, and define what a minimum viable AI solution looks like before writing a line of code • Map existing processes end-to-end, identify where AI can eliminate friction, reduce cost, or accelerate decisions and communicate your findings in business terms • Build lightweight scoping documents and ROI estimates that align stakeholders and set clear success criteria before development begins • Design and build working AI prototypes within days using Claude and the modern AI development stack • Develop full-stack AI applications spanning LLM orchestration, retrieval-augmented generation (RAG), agentic workflows, REST API integrations, and lightweight front-end interfaces • Own your technical architecture end-to-end from prompt design to data pipeline to user interface and be able to explain every design decision to both engineering and business audiences • Iterate based on real user feedback in the field ship early, learn fast, and drive toward production-grade quality with intention and speed • Partner with Brillio's AI Governance team to validate, harden, and evolve prototypes into production-grade, enterprise-ready systems. • Apply responsible AI principles bias review, explainability, HIPAA compliance, audit logging, and model monitoring as a standard part of every build. • Document solutions clearly and completely so they can be handed off, scaled, and maintained by broader engineering teams without rework. • Contribute to Brillio's reusable AI accelerator library turning client-specific solutions into patterns that can be deployed across engagements. • Participate in all client business rhythm meetings sprint reviews, program steering committees, and executive status updates • Demonstrate progress through live demos and working software not slide decks alone • Communicate technical concepts clearly to non-technical business leaders and build the trust required to move from pilot to scale • Surface blockers, dependencies, and risks early with clear, solutions-oriented framing • Develop genuine expertise in your client's business, their workflows, their data, their competitive pressures, and their regulatory environment • Understand healthcare operations deeply enough to generate your own problem hypotheses not just respond to inbound requests • Build relationships with business counterparts that go beyond project delivery, becoming a trusted advisor on what AI can and cannot do in their environment • Contribute to internal knowledge sharing bring learnings from client engagements back to Brillio's broader applied AI community

🎯 Exigences

• 8+ years of healthcare industry experience: Direct, hands-on experience in health insurance operations (underwriting, claims adjudication, utilization management, product launch) or health system clinical and operational workflows not adjacent or observational. You must understand how these environments actually work. • Proficiency with Claude (Anthropic) as a development tool. Demonstrated use of the Claude API including prompt engineering, tool use, and agentic patterns to build real applications. Using Claude as a chat interface does not qualify. You must have built with it. • Full-stack AI engineering capability: Ability to build and ship end-to-end AI applications independently. LLM integration, retrieval-augmented generation (RAG), agentic orchestration, REST API development, and lightweight front-end interfaces sufficient to put a working demo in front of a client. • Demonstrated ability to prototype at speed: Proven track record of moving from a business conversation to a working AI prototype in days not sprints or quarters. You can show examples of what you built, how fast, and what problem it solved. • Business articulation and stakeholder communication: Ability to walk into a meeting with healthcare executives and explain what you built, why it matters, what it costs, and what comes next clearly, confidently, and without jargon. This is a non-negotiable for a client-embedded role. • Maturity to engage at the executive level: Comfortable participating in steering committees, executive briefings, and business rhythm meetings without needing hand-holding. You can hold the room, handle pushback, and demonstrate progress in terms business leaders care about. • Ability to structure ambiguous problems: When a business leader says 'we need to reduce risk in our underwriting process,' you know how to break that into a scoped AI opportunity with clear inputs, outputs, and success criteria before opening a laptop. • Quantitative fluency for ROI and impact measurement: Ability to build simple but credible business cases estimating time saved, cost reduced, or revenue protected and translate AI outputs into financial terms that resonate with finance and operations leaders.