Role Overview:

As the Senior AI/ML Engineer, you will be the primary architect and builder of the Agent. You will be responsible for the hands-on design, coding, and implementation of the agentic system. Your role involves selecting the right tools and frameworks (e.g., LangGraph) to create a robust, scalable, and reliable agent that fulfils the required task. You will transform the strategic blueprint into a functioning, production-ready application.

Key Responsibilities:

• Design and implement the agent's core architecture using a low-level, controllable framework like LangGraph for stateful, multi-step workflows.
• Develop the Retrieval-Augmented Generation (RAG) pipeline, connecting the agent to our internal knowledge bases.
• Engineer sophisticated, multi-step prompt chains that guide the agent's reasoning and logic.
• Integrate the agent with necessary internal data sources and external APIs.
• Write clean, maintainable, and well-documented code, ensuring the system is built for future scalability.
• Collaborate closely with the Data Scientist to optimize the knowledge base and with the QA Engineer to resolve bugs and performance issues.

Skills & Qualifications:

Must-Have:

• Technical:
• Expert-level proficiency in Python and its frameworks.
• Demonstrable experience building applications with LLM frameworks (e.g., LangChain, LangGraph).
• Hands-on experience designing and building RAG systems, including working with vector databases (e.g., Pinecone, Weaviate).
• Advanced prompt and context engineering skills.
• Strong experience with API development and integration (REST, etc.).
• Experience with LLMOps
• Non-Technical:
• Full English-language fluency.
• Strong problem-solving skills and the ability to work autonomously.
• A collaborative mindset and excellent communication skills.
• Experience working with a multicultural organization.
• The ability to think in terms of systems, workflows, and autonomous components.

Good-to-Have:

• Experience with MLOps practices (e.g., model deployment, monitoring, CI/CD for AI systems).
• Familiarity with cloud infrastructure (AWS, Azure, or GCP).
• Experience with TypeScript.
• Experience building multi-agent systems.