Senior AI Engineer / Agentic AI Architect

CodeNinja is a global software and AI infrastructure company specializing in full-stack technology solutions across AI, software engineering, data, and digital transformation. Operating in Saudi Arabia and other global technology hubs, we partner with organizations across various industries to drive business innovation and transformation. Our expertise spans AI, software engineering, data analytics, cloud, enterprise technology, and digital transformation initiatives.

We are seeking an experienced Senior AI Engineer / Agentic AI Architect to design, build, and deploy scalable, secure, and production-grade AI solutions tailored for the banking and financial services sector. This role involves working extensively with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI to deliver enterprise AI platforms that emphasize observability, governance, and performance.

Key Responsibilities

- Design and develop enterprise-grade AI solutions leveraging modern LLMs and Agentic AI frameworks.
- Architect multi-agent systems capable of planning, reasoning, tool integration, and workflow orchestration.
- Build production-ready RAG platforms that integrate structured and unstructured enterprise data.
- Develop scalable APIs and AI services using Python and contemporary backend frameworks such as FastAPI or Flask.
- Implement robust evaluation frameworks to assess LLM quality, safety, and performance.
- Optimize AI applications for latency, throughput, and infrastructure cost efficiency.
- Deploy and manage open-source LLMs in production environments.
- Collaborate closely with architects, product owners, business analysts, and DevOps teams to deliver enterprise AI platforms.
- Ensure compliance with enterprise security standards, governance policies, and responsible AI practices.
- Mentor engineering teams and contribute to the development of AI best practices and reusable frameworks.

Required Qualifications

- 8–12+ years of software engineering experience, including 5+ years focused on Artificial Intelligence, Machine Learning, and Generative AI.
- Strong expertise in machine learning, deep learning, NLP, transformer architectures, LLMs, and embedding models.
- Expert-level proficiency in Python programming and solid software engineering fundamentals.
- Experience building production-grade backend systems, RESTful APIs, microservices, and scalable asynchronous architectures.
- Hands-on experience designing and implementing Agentic AI solutions using frameworks such as LangGraph, CrewAI, OpenAI Agents SDK, AutoGen, Semantic Kernel, or LlamaIndex Workflows.
- Proven skills in multi-agent orchestration, planning agents, tool calling, human-in-the-loop workflows, memory and state management, and agent collaboration patterns.
- Strong background in building enterprise RAG platforms with embedding models (OpenAI, Voyage AI, Cohere, etc.), vector databases (Pinecone, Qdrant, Milvus, etc.), graph databases (Neo4j, Amazon Neptune), and advanced search technologies.
- Experience designing LLM evaluation frameworks using tools like Ragas, TruLens, DeepEval, OpenAI Evals, and LangSmith Evaluation.
- Knowledge of guardrails and observability tools such as Guardrails AI, NeMo Guardrails, OpenAI Moderation, LangSmith, Langfuse, Arize Phoenix, and MLflow.
- Expertise in prompt engineering techniques including Chain-of-Thought, ReAct, Tree of Thoughts, few-shot prompting, function calling, and prompt optimization.
- Hands-on experience deploying open-source LLMs (Llama, Mistral, Qwen, etc.) and working with inference engines like vLLM, TensorRT-LLM, Ollama, and TGI.
- Familiarity with MLOps tools and platforms including MLflow, Kubeflow, Docker, Kubernetes, GitHub Actions/GitLab CI, model versioning, and continuous deployment.
- Experience with cloud AI platforms such as Google Cloud Platform (Vertex AI), Microsoft Azure AI, AWS Bedrock, or OpenAI Azure.
- Proficiency in database technologies including PostgreSQL, Oracle, MongoDB, Redis, and Elasticsearch/OpenSearch.
- Strong analytical, problem-solving, communication, and stakeholder management skills.
- Ability to lead technical discussions, architecture reviews, and mentor engineering teams.
- Comfortable working in Agile delivery environments.

Preferred Qualifications and Benefits

- Experience in the banking or financial services domain, including knowledge of enterprise AI governance, Responsible AI frameworks, and regulatory environments such as SAMA or NCA.
- Familiarity with AI copilots, enterprise AI assistants, OCR, document intelligence, and intelligent automation.
- Experience integrating AI solutions with BPM/workflow platforms like Appian, Camunda, or Pega.
- Bachelor’s degree in Computer Science, Artificial Intelligence, Information Technology, Engineering, or a related field.
- Professional certifications such as Google Professional Machine Learning Engineer, Microsoft Azure AI Engineer Associate, AWS Certified Machine Learning Specialty, Databricks Machine Learning Professional, NVIDIA AI Certifications, or relevant OpenAI/Anthropic ecosystem certifications are advantageous.

What We Offer

Competitive compensation aligned with experience and qualifications. Opportunities to work on enterprise-scale technology and digital transformation projects within banking, financial services, AI, and emerging technology sectors. A collaborative, technically driven environment that fosters professional growth and learning. The chance to work alongside experienced technology and consulting professionals.

This job description outlines the essential responsibilities and qualifications but is not exhaustive. CodeNinja reserves the right to modify duties and requirements as needed.