Senior AI Engineer / Agentic AI Architect

About CodeNinja

Role overview

Core responsibilities

• Design enterprise AI solutions and multi-agent systems for planning, reasoning, tool use, and workflow orchestration.
• Build RAG platforms for structured and unstructured enterprise data and scalable Python APIs and AI services.
• Implement LLM evaluation for quality, safety, and performance; optimize latency, throughput, and infrastructure costs.
• Deploy and manage open-source LLMs in production and collaborate with architects, product owners, analysts, and DevOps teams.
• Ensure enterprise security, governance, and responsible AI practices; mentor engineers and contribute reusable frameworks.

Experience and engineering qualifications

• 8–12+ years of software engineering experience and 5+ years of hands-on AI, machine learning, and generative AI experience.
• Expert-level Python, strong software engineering fundamentals, and production backend systems experience.
• Experience with REST APIs, microservices, asynchronous programming, scalable architectures, and frameworks such as FastAPI or Flask.

AI and platform qualifications

• Experience with LLMs, machine learning, deep learning, NLP, transformers, embeddings, agentic AI, and multi-agent workflows.
• Experience building enterprise RAG platforms with embeddings, vector or graph databases, hybrid or semantic search, retrieval, and reranking.
• Experience with LLM evaluation, guardrails, observability, prompt engineering, open-source model deployment, inference, and MLOps.
• Experience with one or more cloud AI platforms, including Google Cloud, Azure AI, AWS Bedrock, or Azure OpenAI.

Additional qualifications

• Strong analytical, problem-solving, communication, stakeholder management, technical leadership, and mentoring abilities.
• Ability to work in Agile delivery environments.
• A bachelor’s degree in computer science, artificial intelligence, information technology, engineering, or a related field.

Preferred experience and certifications

• Banking or financial services, enterprise AI governance, responsible AI, financial regulation, AI copilots, OCR, document intelligence, or intelligent automation experience is nice to have.
• Integration with Appian, Camunda, or Pega is nice to have.
• Google, Microsoft Azure, AWS, Databricks, NVIDIA, OpenAI, or Anthropic certifications are advantageous.

What the employer offers

• Competitive compensation based on experience and qualifications.
• Enterprise-scale technology projects, professional growth opportunities, and a collaborative technical work environment.