AES - DE - Generative AI Prompt Engineers

Key Skills Required

• Core Engineering
• Strong Python; solid OOP, typing, packaging
• Test automation frameworks: pytest, Playwright/Cypress, Pact (contract testing)
• Git, GitHub Actions / FluxCD, GitOps workflows
• Kubernetes, Docker, Helm basics
• AI / LLM Engineering
• Hands-on with LLM APIs (OpenAI, Anthropic, Azure OpenAI) and prompt engineering
• RAG pipelines, embeddings, vector stores (FAISS, pgvector, or similar)
• LangChain / LlamaIndex or equivalent orchestration frameworks
• Fine-tuning and model adaptation basics (LoRA / PEFT awareness)
• Evaluation & Observability
• LLM evaluation frameworks: Ragas, DeepEval, promptfoo, LangSmith
• Metrics: groundedness, faithfulness, accuracy, latency, token cost
• Golden dataset design and regression harness setup
• Observability: OpenTelemetry, LangFuse, MLflow
• Guardrails & Trust
• NeMo Guardrails, Guardrails AI, Llama Guard, or custom policy engines
• Output schema validation (Pydantic, JSON schema)
• PII / IP leakage detection, hallucination checks, rate-limit and cost controls
• Quality & DevOps
• SonarQube, static analysis, code review automation
• CI/CD integration of AI tests and evals
• Familiarity with Speckit-driven and agentic delivery workflows
• Soft Skills
• Collaborative mindset — works across GenAI Architect, domain developers, and QA
• Clear documentation and evidence-based reporting
• Comfortable operating in a hybrid Zensar + Vanderlande POD environment