Ndeavour

Senior AI Engineer (C# / .NET)

2w ago
SeniorRemote
Ndeavour

Senior AI Engineer (C# / .NET)

2w ago
SeniorRemotec#.netasp.net corereactgcp

Lead design, development and operation of AI agentic systems on cloud platform, managing .NET backend, React frontend and GCP infrastructure.

Responsibilities

  • We’re looking for a Senior AI Engineer (C# / .NET) to lead the design, development, and operation of cutting-edge agentic AI systems across a modern, cloud-based platform. In this role, you will connect internal developer productivity, enterprise intelligence, and user-facing products.
  • This is a hands-on technical leadership role where you will lead by example through daily coding, architectural design, and mentorship. You will set the technical direction across a .NET backend, React frontend, and GCP infrastructure, driving the company's AI strategy across three distinct layers:
  • Layer 1 (Engineering): Using AI agents to help our team build and test software faster.
  • Layer 2 (Company Brain): Unifying internal company data and tools into a single shared intelligence.
  • Layer 3 (Customer Features): Shipping predictive, data-driven AI features directly to our external users.
  • Build Agent Architecture : Lead the design of agent architectures in .NET/C# (planning, memory, multi-step reasoning) and build ASP.NET Core backends with clean APIs for a React frontend.
  • Optimize the SDLC (Layer 1): Design agentic workflows to assist with coding, testing, and CI/CD across our .NET and React codebases; standardize internal AI developer tools.
  • Connect Enterprise Data (Layer 2): Build robust data ingestion, retrieval (RAG), and memory layers over internal systems. Design secure integrations (tool calling, MCP servers) so agents can take action across internal tools.
  • Deliver Customer Intelligence (Layer 3): Ship safe, customer-facing predictive features using customer data as context. Ensure strict data isolation, privacy, and multi-tenant security boundaries.
  • Set Standards & Cloud Practices : Establish org-wide standards for deploying, monitoring, and cost-optimizing agentic systems on Google Cloud Platform (GCP).
  • Mentor & Guide : Conduct technical reviews, make high-level decisions on model selection, and grow the engineering team's agentic systems expertise.

Requirements

  • 6+ years of software engineering experience, with strong proficiency in C# and the .NET ecosystem (.NET 8+, ASP.NET Core).
  • 2+ years of hands-on experience building production applications with LLMs , including advanced prompt engineering and tool/function calling.
  • Demonstrated experience shipping agentic or complex LLM systems at scale, including solid knowledge of RAG , vector databases , and context management .
  • Experience using AI agents within the software development lifecycle and familiarity with .NET-native AI tooling (e.g., Semantic Kernel, Microsoft.Extensions.AI ).
  • Solid experience with Google Cloud Platform (GCP) (GKE, Cloud Run, Pub/Sub, Cloud Storage, etc.).
  • Expert grasp of API design, distributed systems, asynchronous programming, and multi-tenant security isolation.
  • Great communication skills, a collaborative mentoring mindset, and a strong sense of ownership.

Conditions

  • Remote or Hybrid Work Options
  • Private Health Insurance, including dental care
  • Additional Holidays after your 1st and 5th year
  • Sponsored Training & Certifications
  • Employee Referral Bonuses
  • Multisport Card – fully covered
  • Fun Office Space with relaxation zones and free parking

Other

  • Mobile Wave Solutions is a professional services company specializing in software development as a service. With a team of over 120 engineers, we deliver scalable, high-quality software that empowers our global clients to innovate and grow. We value collaboration, technical excellence, and a pragmatic approach to solving complex problems.
  • Experience with Vertex AI and the broader GCP AI/ML ecosystem.
  • Familiarity with cross-language interop (where parts of the AI ecosystem are Python-based).
  • Knowledge of LLM observability/evaluation tools (Cloud Monitoring, OpenTelemetry) and AI safety practices.