Key skills
.NETAI/ML production deploymentLLMs integrationModel APIsVector databasesML pipelinesAI system architectureAI performance optimizationAI model integrationAI system reliabilityAI system observabilityAI system maintainabilityAIMLOpenAIAzurePerformance OptimizationPrototypingCommunication
About this role
ImagineX is a tech company that deploys AI-assisted teams to build and secure mission-critical enterprise solutions. They are seeking a Senior Software Engineer, AI/ML who combines a strong .NET engineering foundation with hands-on experience building AI-powered systems in production.
Responsibilities:
- Design, build, and deploy AI‑powered features and systems within a modern .NET environment
- Own technical direction for AI/ML components, including architecture, model integration, and performance optimization
- Partner with product, engineering, and client stakeholders to shape the roadmap for AI‑driven capabilities
- Evaluate and integrate LLMs, vector search, embeddings, and other modern AI techniques into production workflows
- Lead by example through high‑quality code, strong engineering practices, and thoughtful technical decision‑making
- Drive experimentation, prototyping, and rapid iteration to validate AI‑powered product ideas
- Ensure AI systems are reliable, observable, and maintainable in production environments
- Mentor engineers and contribute to a culture of technical excellence and innovation
Requirements:
- Strong .NET engineering background with experience building production-grade systems
- Demonstrated experience shipping AI/ML features in production, not just experimentation or conceptual familiarity
- Hands-on experience integrating LLMs, model APIs, vector databases, or ML pipelines
- Ability to influence architecture, product direction, and long-term technical strategy
- Strong problem-solving skills and comfort operating in high-autonomy environments
- Excellent communication skills and the ability to collaborate with cross-functional teams
- Experience working in fast-paced, client-facing, or consulting-style environments is a plus
- Experience with Azure AI, OpenAI, or other enterprise AI platforms
- Background in ML Ops, model evaluation, or production monitoring of AI systems
- Experience with distributed systems, event-driven architectures, or cloud-native design
- Prior work on financial, payments, or risk-related systems