Senior AI Engineer – Agentic AI Architect

About the role

CodeNinja is seeking an experienced Senior AI Engineer / Agentic AI Architect to design, build, and deploy enterprise‑scale AI solutions for the banking and financial services sector. The role focuses on delivering production‑grade AI applications with strong emphasis on scalability, security, observability, governance, and performance.

Key responsibilities

• Design and develop enterprise‑grade AI solutions using modern LLMs and Agentic AI frameworks.
• Architect multi‑agent systems capable of planning, reasoning, tool usage, and workflow orchestration.
• Build production‑ready Retrieval‑Augmented Generation (RAG) platforms that integrate structured and unstructured enterprise data.
• Develop scalable APIs and AI services in Python using FastAPI, Flask, or similar frameworks.
• Implement robust evaluation frameworks for LLM quality, safety, and performance.
• Deploy and manage open‑source LLMs in production, ensuring cost‑optimized, secure, and compliant operations.

Required profile

• 8‑12+ years of software engineering experience, including 5+ years in AI/ML and Generative AI.
• Strong software engineering fundamentals and expert‑level Python programming.
• Experience delivering production‑grade backend systems, RESTful APIs, and microservices.
• Proven ability to mentor engineering teams and collaborate with architects, product owners, and DevOps.

Required skills

• Python, FastAPI, Flask, async programming, microservices architecture.
• Agentic AI frameworks: LangGraph, CrewAI, OpenAI Agents SDK, AutoGen, Semantic Kernel, LlamaIndex.
• RAG technologies: embedding models (OpenAI, Voyage AI, Cohere), vector databases (Pinecone, Qdrant, Milvus, Weaviate, ChromaDB), graph databases (Neo4j, Amazon Neptune, Memgraph).
• LLM evaluation tools: Ragas, TruLens, DeepEval, OpenAI Evals, LangSmith.
• Observability and guardrails: LangSmith, Langfuse, Arize Phoenix, Weights & Biases, MLflow, OpenAI Moderation.
• Model deployment & inference: Llama, Mistral, Qwen, DeepSeek, vLLM, TensorRT‑LLM, TGI, SGLang, GPU optimization, quantization.
• MLOps: MLflow, Kubeflow, Docker, Kubernetes, CI/CD (GitHub Actions, GitLab CI).
• Cloud platforms: Google Vertex AI, Microsoft Azure AI, AWS Bedrock, OpenAI Azure.

What we offer

• Competitive compensation based on experience.
• Opportunity to work on enterprise‑scale technology and digital transformation projects in banking and financial services.
• Professional growth and learning opportunities in AI, data, and emerging technologies.
• Collaborative, technically driven work environment with experienced technology and consulting professionals.