AI Engineering Lead

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IMA Financial Group, Inc.

WebsiteLinkedInAlle Stellen

1001 - 5000 Mitarbeiter

Gegründet 1980

🏗️ Bauwesen

🏥 Gesundheitswesen

🏨 Gastgewerbe

💰 Private Equity Round im 2020-11

Construction • Healthcare • Hospitality

IMA Financial Group, Inc. ist ein diversifiziertes Finanz- und Versicherungsdienstleistungsunternehmen, das spezialisierte Versicherungslösungen für verschiedene Branchen anbietet, darunter Agrarwirtschaft, Bauwesen, Digital Risk, Bildung, Energie, Gesundheitswesen, Gastgewerbe, Lebenswissenschaften, Fertigung, Schifffahrt, Private Equity, Immobilien und Technologie. Das Unternehmen bietet eine breite Palette von Versicherungsdienstleistungen an, wie z. B. Unternehmensversicherungen, Mitarbeiterleistungen, private Versicherungen, Altersvorsorgelösungen, Großhandelsversicherungen, Vermögensverwaltung und mehr. IMA ist bestrebt, Vermögenswerte zu schützen und Herausforderungen vorherzusehen, um sicherzustellen, dass die Kunden auf die Zukunft vorbereitet sind. Das Unternehmen legt großen Wert auf den Einfluss in der Gemeinschaft, Philanthropie und kundengesteuerte Lösungen und unterstützt sowohl Innovation als auch die Verbesserung der Gemeinschaft.

Beschreibung

• Design, build, and deploy production-grade end-to-end AI solutions, including workflow automation agents, RAG pipelines, and copilots embedded in business workflows • Translate business needs into technical designs and working products to deliver usable, high-impact solutions, not just proofs of concept • Architect and implement AI-assisted data workflows and agentic systems • Build and maintain LLM-enabled services, prompt frameworks, and coding standards • Develop semantic/context layers ensuring AI outputs align with business logic and data models • Design multi-agent workflows, including human-in-the-loop controls • Make pragmatic tradeoffs to ship quickly while maintaining long-term sustainability • Create scalable patterns for prompt design & orchestration, agent-based workflows, and API integrations & data access • Inform architecture decisions for AI systems balancing speed, security, scalability, maintainability, and cost • Help establish engineering standards and best practices for applied AI across the organization • Establish reusable components, frameworks, and templates to accelerate AI development • Integrate AI automation with enterprise systems, APIs, and data platforms • Evaluate and recommend tooling across the stack (models, frameworks, vector stores, orchestration layers) • Define data requirements and, when needed, build or extend data pipelines to ensure AI systems have reliable, production-ready inputs • Design and implement evaluation frameworks to define and track AI system performance, including task success, accuracy, latency, cost, and business impact; establish feedback loops to continuously improve quality, reliability, and cost-efficacy in production environments • Build guardrails and validation layers to reduce hallucinations, enforce structured outputs, and ensure safe system behavior • Establish monitoring and observability across AI systems (performance, usage, cost, latency, failure modes) • Implement modern engineering practices including CI/CD, versioning, rollback strategies, and automated testing • Ensure solutions meet security, compliance, and governance requirements in a regulated environment • Partner with business leaders, operations & service teams, and product stakeholders to shape use cases and turn them into working solutions • Work closely with AI Enablement to refine workflows and improve adoption • Drive fast iteration cycles, quickly moving from idea to working solution to scaled implementation; iterate solutions based on real user feedback and usage patterns

🎯 Anforderungen

• 7-10+ years in software engineering, data engineering, or AI/LLM experience • Hands-on experience building and deploying production AI systems • Hands-on experience building applications using LLMs and modern AI tooling • Experience with cloud platforms (Azure preferred), Python, APIs, containerization, and CI/CD practices • Experience building RAG pipelines, agent-based workflows, or orchestration layers • Experience with vector databases, embedding pipelines, and retrieval systems • Strong problem-solving ability and bias toward practical, efficient solutions; ability to operate in a fast-moving, ambiguous environment • Experience translating business needs into technical solutions

🏖️ Vorteile

• Annual Performance Bonus • Stock Purchase • Medical Plans • Prescription Drugs • Dental • Vision • Family Assistance Program • FSA • HSA • Pre-Tax Parking Plan • 401(k) • Life/AD&D • Accident • Critical Illness • Hospital Indemnity • Long Term Care • Short-term Disability • Long-term Disability • Business Travel Accident • Identity Theft • Paid Time Off • Flexible Work Options • Paid Holidays • Sabbatical • Gift Matching • Well-Being Stipend • Personal and Professional Development