Senior AI Solutions Engineer

Role Overview

AI adoption across the organization is accelerating, yet many initiatives stall between prototype and production—or are rebuilt repeatedly in silos. This role exists to break that pattern and multiply impact. We are seeking a Senior AI Solutions Engineer with strong full‑stack engineering experience who has shipped real, production-grade systems and uses AI as a core accelerator—not a novelty. This is not a one-off application role. You will design and build reusable AI frameworks, patterns, starter kits, and reference architectures that enable engineering teams to deliver AI-powered solutions faster, safer, and at scale. Operating at the intersection of software engineering, applied AI, and platform thinking, you will turn AI ambition into production reality.

What Success Looks Like

Success in this role is measured by:

• The number of teams you unblock and enable
• The speed at which AI solutions reach production
• The adoption and reuse of the platforms, patterns, and frameworks you build

Key Responsibilities

Build and Scale AI Solutions

• Design and deliver production-grade, AI-enabled applications using modern full-stack and cloud-native architectures
• Build reusable AI frameworks and reference implementations (e.g., RAG, document processing, agent and workflow patterns)
• Integrate AI capabilities into enterprise platforms and workflows with strong engineering discipline, including clean code, automation, reliability, and observability

Apply AI with an AI-First Mindset

• Leverage AI to accelerate delivery, reduce friction, and scale outcomes
• Implement applied GenAI patterns such as:
  • Retrieval-Augmented Generation (RAG)
  • Prompt and tool orchestration
  • Agentic workflows
  • Model evaluation, safety, and guardrails
• Design model-agnostic solutions that remain resilient as the AI ecosystem evolves

Enable Teams and Drive Engineering Excellence

• Transform complex AI implementations into simple, repeatable, and scalable patterns
• Mentor engineers and lead architecture and design reviews to raise quality and consistency
• Partner with stakeholders to define requirements and deliver shippable milestones
• Own DevOps and operational excellence, including:
  • CI/CD pipelines
  • Automated testing
  • Telemetry, monitoring, and alerting
  • Continuous improvement practices

Required Qualifications

• AI‑first builder mindset with a passion for reusable, scalable solutions and clear technical communication
• 6+ years of experience building and operating production full-stack systems at scale
• Hands-on experience with distributed, cloud-native architectures (APIs, data platforms, event-driven systems)
• Strong foundation in:
  • System and application design
  • Scalability and resiliency
  • Security and observability
• Proven, hands-on experience delivering AI / GenAI-powered applications in production (beyond POCs or experimentation)
• Applied GenAI expertise, including:
  • RAG
  • LLM integration and orchestration
  • Prompt design
  • Evaluation frameworks and guardrails
• Proficiency in Java and/or Python, using modern frameworks (e.g., Spring Boot, Python-based services)
• Experience with CI/CD pipelines, automated testing, and production observability tools

Preferred / Nice-to-Have Qualifications

• Public cloud experience (Azure preferred)
• Experience building internal platforms, frameworks, or developer tooling
• Familiarity with vector databases, embeddings, Kafka, or high-throughput messaging systems
• Experience working in regulated or financial services environments
• Experience collaborating with globally distributed engineering teams