Role
AI adoption across the firm is accelerating, yet many initiatives stall between prototype and production or repeat the same solutions in isolation. This role exists to break that pattern and multiply impact. We are hiring an AI‑First Solutions Engineer with deep full‑stack engineering experience who has shipped real production systems and now uses AI as a core accelerator, not a novelty. This is not a one‑off application role. You will build reusable AI frameworks, patterns, starter kits, and reference architectures that enable teams across the organization to deliver AI‑powered solutions faster, safer, and at scale.
Operating at the intersection of software engineering, applied AI, and platform thinking, you will:
- Deliver production‑grade AI‑enabled solutions
- Convert complexity into reusable, scalable building blocks
- Remove technical, architectural, and process bottlenecks
- Enable and upskill engineers to adopt AI responsibly and effectively
Success is defined by:
- The number of teams you unblock
- The speed at which AI solutions reach production
- The breadth of adoption of the platforms and patterns you build
Responsibilities
Build and Scale AI Solutions
1. Design and deliver production‑grade AI‑enabled applications using modern full‑stack and cloud‑native patterns
2. Build reusable AI frameworks and reference implementations (e.g., RAG, document processing, agent/workflow patterns)
3. Integrate AI into enterprise platforms and workflows with strong engineering discipline (clean code, automation, observability, reliability)
Apply AI with an AI‑First Mindset
1. Use AI to accelerate delivery, reduce friction, and scale outcomes
2. Implement applied GenAI patterns including RAG, prompt/tool orchestration, agentic workflows, and evaluation with guardrails
3. Design model‑agnostic solutions resilient to rapid AI ecosystem change
Enable Teams and Own Engineering Excellence
1. Turn complex AI implementations into simple, repeatable patterns
2. Mentor engineers; lead architecture and design reviews to raise quality and consistency
3. Partner with stakeholders on requirements and shippable milestones
4. Own DevOps hygiene (CI/CD, automated testing, telemetry, monitoring) and drive continuous improvement
Required Skills
- AI‑first builder mindset, designing reusable solutions for scale and impact, with clear technical communication
- 6+ years building and operating production full‑stack systems at scale
- Hands‑on experience with distributed, cloud‑native architectures (APIs, data, event‑driven systems)
- Strong foundation in system design, scalability, resiliency, security, and observability
- Hands‑on, production experience building AI/GenAI‑powered applications, not just experimentation or POCs
- Applied GenAI expertise including RAG, LLM integration/orchestration, prompt design, and evaluation/guardrails
- Proficiency in Java and/or Python with modern frameworks (e.g., Spring Boot, Python services)
- Experience with CI/CD, automated testing, and production observability
Desired Skills
- Public cloud experience (Azure preferred)
- Experience building internal platforms, frameworks, or developer tooling
- Familiarity with vector databases, embeddings, Kafka, or high‑volume messaging systems
- Experience in regulated or financial services environments
- Experience working with globally distributed engineering teams
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