Agentic AI Developer

Project description

We are seeking a skilled AI Agentic Developer in implementing solutions within financial institutions.

You'll work inside a Tier‑1 wealth management bank in the Agentic Products crew, as part of the AI Transformation Stream in WMPC. Our team leverages the latest AI technologies to deliver value-driven solutions and agents. As an AI Engineer, you'll play a key role in driving innovation and shaping the future of agents.

We're a team that values collaboration, creativity, and continuous learning.

Responsibilities

• Design and develop Agentic AI applications with a focus on prompt engineering, LangChain, and agentic AI frameworks. Build scalable, secure, and sustainable solutions using Python and modern programming techniques.
• Problem-solving ability with logical reasoning.
• Design and develop reusable agentic AI workflows with LangGraph and LLMs.
• Craft and refine clear, effective prompts for diverse tasks.
• Understand Agent-to-Agent (A2A) design patterns.
• Write clean, production-grade Python code with comprehensive pytest unit tests.
• Use Git for version control and GitLab CI/CD to automate build, test, and deployment pipelines.
• Adapt to role flexibility and take on additional responsibilities as needed

Mandatory Skills

• 6+ years of overall working experience with 3+ years of experience in Agentic AI
• Python, SQL, and ML libraries (scikit-learn, PyTorch, TensorFlow)
• MLOps tools (MLflow, Kubeflow, Azure ML)

Qualifications

• Strong to average proficiency in Python, including writing pytest unit tests.
• Practical experience with Git and GitLab CI/CD in a team environment.
• Hands-on experience in agentic AI system design and orchestration.
• Good prompt engineering skills for LLM control and output reliability
• Proven ability to build and maintain LangGraph workflows and reusable components.
• Solid understanding of A2A orchestration principles.
• Able to understand the business requirements and convert into tech specifications.
• Ready to work in a rapidly changing environment.
• Azure cloud, Kubernetes setup, or experience configuring them.
• Handle data transformation and reusable components.