Senior 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁

We are seeking a highly skilled Senior Agentic AI Architect to join our team in Pakistan under a hybrid work model, with sponsored visits to Saudi Arabia. The ideal candidate will have 8 to 12+ years of experience in software engineering, including at least 5 years specializing in AI, machine learning, and generative AI. This role involves designing, building, and deploying enterprise-grade AI solutions with a strong emphasis on Agentic AI, large language models (LLMs), retrieval-augmented generation (RAG), and AI platforms. Candidates should have proven experience delivering production-ready AI systems, preferably within banking and financial services environments. Availability to join within one month is required.

Key Responsibilities
- Design and architect enterprise AI and Agentic AI solutions tailored to complex business needs.
- Develop multi-agent systems that support planning, reasoning, tool usage, and workflow orchestration.
- Build scalable RAG platforms leveraging enterprise data for enhanced search and retrieval capabilities.
- Create production-grade AI APIs and backend services primarily using Python.
- Implement frameworks for LLM evaluation, safety, observability, and governance to ensure robust AI deployment.
- Deploy and optimize open-source LLMs in production environments, focusing on latency, scalability, performance, and cost efficiency.
- Collaborate closely with architects, product teams, business analysts, and DevOps to align AI solutions with organizational goals.
- Mentor engineering teams and establish best practices in AI engineering to foster technical excellence.

Required Qualifications
- Extensive expertise in Agentic AI technologies such as LangGraph, CrewAI, OpenAI Agents SDK, AutoGen, Semantic Kernel, or LlamaIndex.
- Experience with multi-agent orchestration, tool calling, planning, human-in-the-loop workflows, and agent memory/state management.
- Strong knowledge of LLMs, transformers, NLP, deep learning, embedding models, prompt engineering, function calling, and token/context optimization.
- Proficiency in RAG architecture, including hybrid, semantic, dense, and sparse retrieval methods; familiarity with BM25, reranking, and metadata filtering.
- Hands-on experience with vector databases (Pinecone, Qdrant, Milvus, Weaviate, ChromaDB) and graph databases (Neo4j, Neptune, Memgraph).
- Skilled in LLM evaluation and observability tools such as Ragas, DeepEval, TruLens, OpenAI Evals, LangSmith, with a focus on hallucination detection, faithfulness, and prompt tracing.
- Strong background in AI infrastructure and deployment using Python frameworks (FastAPI, Flask), REST APIs, microservices, asynchronous architectures, and GPU optimization techniques including quantization and multi-GPU scaling.
- Familiarity with MLOps and cloud platforms including Docker, Kubernetes, MLflow, Kubeflow, CI/CD pipelines, and major cloud providers (AWS, Azure, Google Cloud), along with AI-specific services like Azure AI, AWS Bedrock, and Vertex AI.
- Experience managing databases such as PostgreSQL, Oracle, MongoDB, Redis, and search engines like Elasticsearch or OpenSearch.

Preferred Qualifications and Benefits
- Prior experience in banking, financial services, enterprise AI, responsible AI, AI governance, or regulated environments is highly desirable.
- Knowledge of financial-sector regulatory frameworks such as SAMA or NCA is advantageous.
- Experience with AI copilots, document intelligence, OCR, intelligent automation, or workflow platforms like Appian, Camunda, or Pega will be considered a plus.
- The role offers the opportunity to work on cutting-edge AI technologies in a dynamic, enterprise setting with cross-border collaboration.

Candidates must be ready to take full ownership of AI solutions from architecture through deployment and maintenance, demonstrating strong communication, stakeholder management, and leadership skills. If you are passionate about advancing AI in regulated industries and meet the above criteria, this is an excellent opportunity to contribute to innovative AI initiatives.