Technology Consulting - Data & AI - AI Engineer

Job Description Roles & Responsibilities Job Summary We are seeking a highly skilled AI Engineer (Agentic AI) to support the design and delivery of next-generation AI solutions leveraging large language models (LLMs), autonomous agents, and advanced machine learning techniques. The role will enable AI-driven transformation by building intelligent systems such as copilots, multi-agent workflows, and RAG solutions. About the Role This role sits within the Technology Consulting Data & AI practice. The candidate will translate business challenges into AI use cases and deliver production-grade AI systems across the full lifecycle. Key Responsibilities - Design and develop AI agents and multi-agent systems - Build RAG pipelines - Develop scalable AI services using APIs and microservices - Integrate LLMs with enterprise systems - Apply Responsible AI practices - Engage with stakeholders and present solutions Required Experience & Qualifications - 2 6 years of experience in AI engineering or ML Key Skills & Competencies 1 - Agentic AI & LLM Eng Mandatory Weight 10 Core Competencies: AI Agents Autonomous Agents Multi-agent systems LLM Applications LLM Orchestration Generative AI Engineer AI Copilot Development Prompt Engineering 2 Framework and Tooling Mandatory Weight 10 Core Competencies: LangChain LangGraph Semantic Kernel AutoGen (Microsoft) CrewAI LlamaIndex OpenAI API / Azure OpenAI Hugging Face Transformers DSPy Instructor / Pydantic AI Guardrails AI LangSmith 3 Data Science/Machine Learning Mandatory Weight 10 Core Competencies: Deep Learning NLP (Natural Language Processing) Data Science Model training / evaluation Feature engineering Fine-tuning LLMs (LoRA / QLoRA) RLHF / alignment techniques Model benchmarking Transformer architecture 4 Cloud Native architecture Mandatory Weight 10 Core Competencies Python API development REST APIs Microservices FastAPI / Flask Async programming (asyncio) Docker CI/CD pipelines Event-driven architecture TypeScript (nice to have) 5 RAG & Retrieval Systems Mandatory Weight 10 Core Competencies RAG (Retrieval-Augmented Generation) Vector databases Embeddings Semantic search Hybrid search (BM25 + vector) Document chunking strategies Re-ranking (Cohere, cross-encoder) Knowledge graphs GraphRAG Contextual compression 6 Vector DB and Search Mandatory Weight 10 Core Competencies Pinecone FAISS ChromaDB Weaviate Azure AI Search Qdrant Milvus pgvector (PostgreSQL) 7 Cloud Platform & DevOps Mandatory Weight 10 Core Competencies Azure (Azure OpenAI, AI Foundry) OR AWS (Bedrock, SageMaker) OR GCP (Vertex AI) Docker Kubernetes Azure Container Apps GitHub Actions / Azure DevOps 8 Observability & Evaluation Mandatory Weight 10 Core Competencies LangSmith Weights & Biases Arize AI / Phoenix Prompt evaluation frameworks RAGAS (RAG evaluation) A/B testing of AI outputs Hallucination detection Tracing & distributed logging Eval-driven development 9 AI Safety and Governance Mandatory Weight 10 Core Competencies Responsible AI principles Prompt injection prevention Guardrails implementation Output filtering / content moderation Bias & fairness evaluation Model explainability (SHAP, LIME) Human-in-the-loop (HITL) EU AI Act / SDAIA NAII awareness Red-teaming LLMs 10 General - Optional Weight 10 Core Competencies GitHub with GenAI / agent projects Built chatbots / copilots in production Azure OpenAI / OpenAI APIs / Anthropic Claude Experience integrating tools into LLMs Production deployment experience Open-source contributions (LangChain etc.) Technical blog / papers on AI agents Conference talks or demos Additional Requirements - Fluent in English - Strong communication and stakeholder skills - Portfolio or GitHub projects preferred Company Industry BankingFinancial ServicesBroking Department / Functional Area Corporate PlanningConsultingStrategyM&A Keywords Technology Consulting - Data & AI - AI Engineer Get real-time job updates only on our App