Saxo
FinTech
SeniorAIEngineer
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“Senior AI Engineer at Saxo. Skills: AI agents, LLMOps, Cloud-native development, Copilot Studio. Define engineering standards. Own engineering standards”
What You'll Achieve.
Bring agents to market; Improve agent quality; Improve agent safety; Improve agent grounding; Reduce cost; Reduce latency; Maintain audit ready documentation
Industry & Context.
Troubleshooting; Root cause analysis
What They're Looking For.
Must Have
7+ years software engineering, 3+ years cloud development, 2+ years production LLM/agent work, Coding in C#/.NET, Coding in Python, Hands-on Copilot Studio experience, Hands-on Power Platform experience, Hands-on MCP server experience
Nice to Have
Microsoft Agent Framework experience preferred, Experience with LiteLLM preferred, Experience with Microsoft Fabric preferred, Experience with Prompt Flow preferred, Vector database experience preferred, Graph database experience preferred, Experience in financial services helpful, Familiarity with evaluation tools helpful, Familiarity with safety tools helpful, Kubernetes experience beneficial, Kafka experience beneficial, Low-latency architectures experience beneficial, API design skills beneficial, Cost modeling experience beneficial, SRE practices for LLM workloads beneficial, A2A protocol experience advantageous, Agent Client Protocol experience advantageous
What You'll Do.
Define engineering standards
Own engineering standards
Build reusable frameworks
Support LiteLLM access layer
Design production grade agents
Deliver production grade agents
Integrate agents with enterprise systems
Establish LLMOps practices
Implement Responsible AI controls
Collaborate across product lifecycle
Translate business needs
Define success metrics
Own architecture docs
Provide build vs. buy guidance
How You'll Work.
Team & Collaboration
Product development; Risk stakeholders; Security stakeholders; Technology stakeholders; Business stakeholders; Cross-functional teams; Engineering teams; Security teams; Risk teams; Compliance teams; Business teams
Communication Scope
Enablement sessions; Guides; Playbooks; Solution reviews; Architecture docs; ADRs; Roadmaps
Process & Methodology
Roadmaps, Iterative delivery
Full Job Description
Saxo is building the capability for secure, compliant, and scalable AI agents to power internal productivity and client-facing experiences. We are looking for a Senior AI engineer who is equally comfortable building with zero/low-code tools in Microsoft Copilot Studio _and_ delivering high-quality production code in C#/.NET and Python in cloud-native environments. You will set engineering standards, build reusable frameworks and accelerators, coach colleagues, and ship working agents end-to-end. You will work closely with product development (“client journeys”), risk, security, and other technology and business stakeholders to ensure our agents are safe, reliable, cost-effective, and measurable in a regulated financial-services environment. **Responsibilities** * Define and own engineering standards for agent development across low code/zero code (e.g. Microsoft Copilot Studio) and high code (cloud-native, C#/.NET, Python), covering design patterns, testing, telemetry, security, and documentation * Build reusable frameworks, SDKs, and templates for prompt management, tool/function orchestration, RAG, evaluation/guardrails, and observability with cost and rollback controls * Support a centralized LiteLLM based access layer, including model routing, failover, caching, rate/cost optimization, and governance across Azure OpenAI and other providers * Design and deliver production grade agents in Copilot Studio (incl. Power Platform integrations) and in highcode services using REST/gRPC, Azure components, and containers. Experience with Microsoft Agent Framework is preferred, ideally in C#/.NET * Integrate agents with enterprise systems via standard MCP patterns, OpenAPI‑based internal APIs, data platforms, Kafka, Microsoft 365/Graph, and secure auth (Entra ID, OAuth2, managed identities) * Establish LLMOps practices: evaluation pipelines, prompt/version management, staged rollouts, hallucination reduction, safety defenses, and robust monitoring/incident response * Partne
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