Forward Deployed AI Product Engineer

Emploi pas sur LinkedIn

🕒 il y a 21 jours

🇺🇸 États-Unis – Télétravail

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

🧑‍💻 Développeur Full-Stack

🦅 Parrain de Visa H1B

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phData

Site WebLinkedInTous les Emplois

201 - 500 employés

Fondée en 2014

💼 Conseil

🏥 Santé

🏭 Fabrication

💰 €2 500 000 Seed Round en 2018-03

Consulting • Healthcare • Manufacturing

phData est une entreprise spécialisée dans la fourniture de solutions d'ingénierie de données, d'analytique et de migration vers le cloud. Elle propose des services comprenant des stratégies d'IA et d'apprentissage automatique, d'analytique et de visualisation, ainsi que des opérations élastiques pour aider les entreprises à construire et à mettre en œuvre des produits et applications de données modernes. phData est un partenaire d'élite de Snowflake et fournit des services de conseil de bout en bout pour développer des applications de données modernes et traiter efficacement de vastes ensembles de données. Elle répond aux besoins d'industries telles que la santé, les services financiers et la fabrication en optimisant les plateformes de données et en fournissant des informations exploitables grâce à une technologie de pointe et une expertise avérée.

Description

• Builds AI-native applications and agents that solve high-value business problems on top of the client’s data and AI platform. • Deployed directly into strategic customer accounts to lead AI-powered solutions. • Collaborates with business stakeholders, central platform teams, and other phData consultants to shape AI use cases. • Prototypes and implements MVP-grade agents, applications, and workflows to demonstrate value quickly. • Owns the end-to-end lifecycle of AI-native solutions: discovery, design, implementation, and handoff. • Works closely with executives and frontline operators to understand real-world constraints and deliver quickly.

🎯 Exigences

• 4+ years of hands-on software engineering experience (more for Senior/Principal levels), including building and operating production systems. • Prior consulting, customer-embedded engineering, or product engineering experience in data/AI-heavy environments strongly preferred. • BA/BS in computer science, engineering, mathematics, operations, or related fields preferred. Equivalent practical experience considered. • Rapid Prototyping: Design and build full-stack, MVP-grade prototypes for AI-native applications, agents, and workflows that can be validated quickly with end users. • Full-Stack Execution: Deliver end-to-end solutions using a mix of Python, SQL, and TypeScript/JavaScript, including APIs, back-end services, and front-end experiences. • AI Agents and Workflows: Implement AI-powered workflows and agents that solve real business problems, including RAG pipelines, AI agents, workflows, skills, memory, and model-context protocols where appropriate. • User Interfaces: Build high-fidelity, production-ready user interfaces (e.g., Streamlit/Gradio/React or similar) that make AI capabilities usable and intuitive for business users. • Data Transformation/Manipulation: Move, transform, and harmonize disparate data sources into the client’s data platform (e.g., Snowflake, Databricks, cloud data warehouses), exposing clean, reliable data to applications and agents. • Pattern Feeding: Capture and contribute technical patterns, best practices, and anti-patterns back into the client’s platform and phData’s internal playbooks to build long-term leverage. • Platform Advocacy: Bridge the gap between business-unit needs and central platform capabilities. Identify capability gaps (CI/CD, orchestration, observability, streaming ingestion, vector search, AI gateways, etc.) and help prioritize their development. • Pull-Through Identification: Identify new data sources, platform capabilities, and integration opportunities that create demand for additional phData services (data engineering, ML engineering, Analytics, Workforce AI, platform operations). • Use Case Discovery: Lead or support discovery sessions with business stakeholders to surface high-impact AI opportunities, unconstrained by legacy processes or “the way we’ve always done it.” • Value Articulation: Define success metrics in terms of business KPIs and quantify measurable ROI to justify additional services and platform investments. • Operational Empathy: Spend significant time on-site with end users and operational teams to deeply understand workflows, constraints, and edge cases; design solutions that fit real-world usage. • Client-Facing Communication: Engage confidently with executives, managers, and technical teams. Clearly communicate trade-offs, timelines, and risks, and maintain trust while moving quickly.

🏖️ Avantages

• Health insurance • Flexible work arrangements • Professional development opportunities