AI Solutions Architect & Field Engineer

• Proven Track Record: 8+ years of hands-on experience in software engineering, technical consulting, solution architecture, or client-facing platform engineering.
• Enterprise & Regulated Experience: Demonstrated capability in architecting and deploying large-scale systems within highly regulated industries (e.g., banking, healthcare, government).
• Applied AI & GenAI Expertise: Practical experience developing and orchestrating LLM applications, RAG pipelines, AI agents, vector databases, and prompt engineering frameworks.
• Core Software Engineering: Strong proficiency in modern backend languages (Java, Python, C#, or similar), RESTful microservices, and distributed systems architecture.
• Cloud & DevOps Ecosystem: Production experience across major cloud platforms (AWS, Azure, GCP) alongside containerization and delivery tooling (Docker, Kubernetes, CI/CD, Infrastructure as Code).

We are looking for a versatile AI Solutions Architect & Field Engineer to serve as the key technical bridge between our core product development and client operations. In this role, you will embed directly with enterprise customers to analyze complex operational bottlenecks, architect tailormade GenAI solutions, and drive hands-on deployment of production-grade platforms. You will play a pivotal role in translating customer feedback into scalable, high-impact product features. ,[Client-Facing Solution Architecture: Partner directly with enterprise stakeholders to translate business pain points into scalable, technical AI blueprints., Hands-on Deployment & Integration: Lead the end-to-end implementation and integration of GenAI platforms, custom AI agents, and RAG architectures within complex client environments., Product-Engineering Feedback Loop: Act as an internal advocate for customer requirements, turning client-specific customizations into repeatable product capabilities., Technical Delivery & Value Realization: Ensure enterprise deployments strictly adhere to security, compliance, and scalability standards while delivering clear business ROI.] Requirements: AI, LLM, RAG, Java, Python, C#, REST API, Microservices, Cloud, DevOps, Cloud platform, AWS, Azure, GCP, Docker, Kubernetes, CI/CD, Infrastructure as Code