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Today's threatscape is relentless. So are we. At Cyderes, we build practical Identity & Access Management (IAM), Exposure Management, and risk programs, helping organizations stop active threats fast with Managed Detection & Response (MDR) that integrates with existing tools. Powering it all is Meridian, our entity fabric that connects identities, assets, and access into one trusted reality. Augmented by AI and driven by seasoned operators, our tireless global team arms organizations with the people, platforms, and perspectives they need to conquer whatever tomorrow throws their way.
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Role Summary
We are hiring a Full-Stack AI Engineer to develop production-grade agentic AI systems. You will focus on prompt engineering, PromptOps, Python backend services, Azure-native cloud architecture, and full-stack delivery of reliable AI workflows at scale.
You will report to Engineering Manager.
Responsibilities
Prompt Engineering & Agentic Systems
Design, test, and improve enterprise-grade prompts, system instructions, schemas, and agent workflows.
Build multi-step agentic pipelines, self-refining loops, and deterministic fallback logic.
Implement PromptOps: versioning, evaluations, regression testing, hallucination mitigation, token optimization, and governance.
Build RAG pipelines, vector search, memory layers, and grounding strategies.
Backend & Full-Stack Engineering
Develop Python-based microservices (FastAPI, async patterns, REST APIs).
Deliver full-stack AI applications (React, TypeScript) used by analysts for multi-turn AI interactions.
Manage GitHub, CI/CD, testing, branching, and release automation.
Integrate AI services through serverless, containerized, and event-driven architectures.
Azure Cloud & Infrastructure
Deploy AI workloads on Azure App Services, Functions, AKS, Logic Apps, Event Grid.
Implement IaC using Azure Bicep / ARM.
Enforce security, RBAC, Vault, secrets management, and runtime policies.
Increase cost, performance, observability, and reliability.
ML, Data & Observability
Build embeddings, feature pipelines, telemetry, and drift detection.
Perform data analysis and experimentation using KQL and Splunk SPL.
Support model selection, fine-tuning strategies, safety constraints, and evaluation frameworks.
Ownership
Translate ambiguous needs into measurable AI workflows.
Partner with security, engineering, and product teams.
Produce clear documentation (architecture, prompts, runbooks).
Be an internal subject matter expert for agentic systems and modern AI development patterns.
Required Skills
Advanced prompt engineering (Gemini, GPT, Claude; multi-model systems).
Python, FastAPI, async programming.
5+ years experience with Azure cloud services and serverless patterns.
Hands-on RAG and vector databases (Azure Search, Pinecone, FAISS).
Agent frameworks (LangChain, LlamaIndex, AutoGen, or custom).
Frontend experience with React + TypeScript.
CI/CD, GitHub Actions, and DevOps practices.
Good to have
Multi-agent or autonomous systems experience.
AI in security operations or automation.
Azure / ML Ops certifications.
SOC2 / ISO / AI governance exposure.
Open-source or AI tooling contributions.