Full-Stack AI Engineer (Prompt Engineering & Agentic Systems) Python, Azure

We help the world Be Everyday Ready™ Today’s threatscape is relentless. So are we. At Cyderes, we specialize in building practical IAM, exposure management, and risk programs, and stopping active threats fast with MDR that works with your existing security tools — all augmented by AI and driven by seasoned operators. Our tireless global team is laser-focused on cybersecurity, arming organizations with the people, platforms, and perspectives they need to conquer whatever tomorrow throws their way. Role Summary We are hiring a Full-Stack AI Engineer to design, build, and operate production-grade agentic AI systems. The role focuses on prompt engineering, PromptOps, Python backend services, Azure-native cloud architecture, and full-stack delivery of reliable AI workflows at scale. Responsibilities

Design, test, and optimize 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.

Build and maintain 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 via serverless, containerized, and event-driven architectures.

Deploy AI workloads on Azure App Services, Functions, AKS, Logic Apps, Event Grid.

Implement IaC using Azure Bicep / ARM.

Enforce security, RBAC, Key Vault, secrets management, and runtime policies.

Optimize cost, performance, observability, and reliability.

Build and maintain 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.

Translate ambiguous business needs into measurable AI workflows.

Partner with security, engineering, and product teams.

Produce clear documentation (architecture, prompts, runbooks).

Act as an internal SME for agentic systems and modern AI development patterns.

Required Skills

Advanced prompt engineering (Gemini, GPT, Claude; multi-model systems).

Strong Python, FastAPI, async programming.

Deep experience with Azure cloud services and serverless patterns.

Hands-on RAG and vector databases (Azure Search, Pinecone, FAISS, etc.).

Agent frameworks (LangChain, LlamaIndex, AutoGen, or custom).

Frontend experience with React + TypeScript.

Strong CI/CD, GitHub Actions, and DevOps practices.

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.