Responsibilities:

• Core engineering with strong Python and OOP skills
• Test automation using pytest, Playwright/Cypress, Pact
• Managing Git, GitHub Actions, FluxCD, and GitOps workflows
• Working with Kubernetes, Docker, and Helm basics
• Hands-on with LLM APIs and prompt engineering
• Building and managing RAG pipelines, embeddings, and vector stores
• Using orchestration frameworks like LangChain or LlamaIndex
• Applying fine-tuning and model adaptation techniques
• Evaluating LLMs using frameworks and metrics
• Designing golden datasets and regression harnesses
• Implementing observability with OpenTelemetry, LangFuse, MLflow
• Implementing guardrails and trust mechanisms
• Validating output schemas and detecting PII/IP leakage
• Ensuring quality with SonarQube and code review automation
• Integrating AI tests and evaluations into CI/CD pipelines

Additional responsibilities:

• Collaborate across GenAI Architect, domain developers, and QA
• Provide clear documentation and evidence-based reporting
• Operate in a hybrid Zensar + Vanderlande POD environment

More skills:

OOP, typing, packaging, pytest, Playwright, Cypress, Pact, Git, GitHub Actions, FluxCD, GitOps workflows, Kubernetes, Docker, Helm, LLM APIs, FAISS, pgvector, orchestration frameworks, LLM evaluation frameworks, DeepEval, promptfoo, LangSmith, OpenTelemetry, LangFuse, MLflow, NeMo Guardrails, Guardrails AI, Llama Guard, policy engines, Pydantic, JSON schema, SonarQube, static analysis, code review automation, CI/CD integration, Speckit-driven workflows, agentic delivery workflows