Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A global management consulting and technology organization focused on combining data, science, technology, and human ingenuity to create innovative solutions and improve outcomes across industries. The organization works collaboratively with clients to develop customized solutions and technology products that address critical business needs.
Key Responsibilities
Build and Lead the AI Engineering Function
- Lead the dedicated AI Engineering team by hiring, structuring, and establishing the technical culture.
- Define an engineering team model that scales through engineering pods organized around platform capabilities and distributed across geographies.
- Own the complete talent lifecycle, including sourcing, hiring, onboarding, performance management, development, and retention.
- Partner with Product and Quality Assurance teams to establish AI-native development practices, including evaluation frameworks, LLMOps discipline, and agent observability standards.
Own the Agentic Platform Architecture
- Drive architecture decisions for the Agentic AI platform, covering orchestration, retrieval, validation-gate agent patterns, cost management, and multi-agent coordination.
- Lead the technical integration between AWS Bedrock AgentCore, orchestration and observability infrastructure, and AI applications.
- Establish standards for determining when to use RAG, fine-tuning, or long-context approaches.
- Enforce architectural standards through code reviews and design reviews.
- Ensure the platform meets enterprise-grade requirements for latency, cost per inference, audit trails, hallucination management, and PII handling.
- Lead the transition of agentic capabilities from alpha through beta and general availability while maintaining accountability for product delivery and adoption timelines.
Define and Enforce Engineering Quality
- Establish evaluation frameworks for every AI feature before it is released to clients.
- Maintain a clear distinction between demonstration-quality and production-quality AI systems.
- Lead efforts to build high-quality, accurate, reliable, and consistent AI applications.
- Establish pull request review standards for LLM-powered features that can be adopted across current and future engineering teams.
Represent AI Engineering Externally
- Engage with client technical leadership and communicate architectural decisions with credibility to executives and enterprise architects.
- Contribute to thought leadership around trusted Agentic AI for enterprise environments.
- Evaluate emerging AI frameworks, models, and infrastructure options.
- Make build-versus-buy-versus-integrate decisions with speed, technical rigor, and sound judgment.
Required Qualifications
- 15+ years of software engineering experience.
- 5+ years of AI, machine learning, or data engineering experience in production environments.
- At least 5 years of experience leading 3–5 Scrum teams across multiple locations.
- Direct experience delivering multi-agent or RAG-based systems in enterprise B2B environments.
- Hands-on experience with technologies such as LangGraph, LangChain, or equivalent agent orchestration frameworks.
- Ability to read, evaluate, and critique agent orchestration implementations.
- Experience managing engineering organizations of 15+ individuals, including hiring and developing senior engineers.
- Strong expertise in evaluation frameworks, LLMOps, and production-readiness standards for AI systems.
- Experience with AWS, ideally including Bedrock, SageMaker, or related enterprise AI services.
- Excellent written and verbal communication skills.
- Ability to produce both detailed technical design documents and executive-level stakeholder briefs.
- Experience building multi-tenant enterprise SaaS products, particularly business applications or platforms supporting multiple applications.
- Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related field.
Disclaimer
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