AES - DE - Generative AI Application Developers

Key Skills Required

• Core Engineering + Strong Python; TypeScript / Node.js a plus + REST / gRPC API design, async programming, FastAPI or equivalent + Experience building cloud-native microservices + Hands-on experience with Kafka-based event-driven architecture + Practical understanding of Domain-Driven Design (DDD) concepts + Git, GitHub Actions, FluxCD, GitOps workflows + Docker, Kubernetes, Helm
• GenAI / LLM Development + Hands-on with LLM APIs (OpenAI, Anthropic, Azure OpenAI, open-source models) + Prompt engineering, prompt versioning, structured output (JSON schema, Pydantic) + RAG pipeline implementation — chunking, embeddings, vector stores (pgvector, FAISS, Pinecone, Weaviate) + Function calling, tool use, and agent loops
• Agentic Frameworks & Tooling + LangChain, LlamaIndex, LangGraph, AutoGen, CrewAI, or equivalent + MCP server/client implementation + Familiarity with Speckit, GitHub Copilot extensions, Figma MCP integration + Experience building coding agents, review agents, or test-generation agents
• Evaluation & Guardrails + Working knowledge of eval frameworks (Ragas, DeepEval, promptfoo, LangSmith) + Guardrail implementation (NeMo Guardrails, Guardrails AI, custom validators) + Observability: LangFuse, OpenTelemetry, token/cost dashboards
• Data & Integration + SQL and NoSQL basics; data pipelines for ingestion and indexing + Integration with enterprise systems (Jira, Confluence, GitHub, Artifactory) + Cloud services (Azure / AWS / GCP) — storage, compute, identity
• Soft Skills + Collaborative team player; works closely with the Solution Architect and AI/ML Engineer + Quick learner who stays current with the fast-moving GenAI ecosystem + Strong ownership — ships production-grade code, not prototypes.