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.
Part of Agentic AI team
BE Computer, 4-8 years of experience