AI Engineer

We’re looking for an innovative ML Engineer to join our AI team and help design, prototype, and operationalize

advanced AI systems, including Retrieval-Augmented Generation (RAG) pipelines, MCP services, and agentic

workflows. You’ll work closely with Python Developers and MLOps Engineers to bring AI-powered features

from concept to production.

Key Responsibilities:

— Design, prototype, and iterate on AI models, RAG pipelines, MCP services, and agentic reasoning

systems.

— Develop AI-powered services using frameworks such as LangChain, LangGraph, CrewAI, LlamaIndex,

Haystack, and DSPy.

— Build and optimize prompts for AI-driven tasks like chat, summarization, information extraction, and

decision support.

— Integrate and tune vector databases (e.g., Chroma, FAISS, Pinecone, Qdrant) to optimize vector

search workflows.

— Collaborate with Python Developers to define service interfaces, APIs, and operational

requirements.

— Implement task decomposition, memory management, and tool-use strategies within agentic

systems.

— Monitor AI system performance, operational risks, and prompt evaluation metrics.

— Stay current with emerging AI frameworks, architectures, and best practices in AI observability and

evaluation.

Required Skills & Experience:

— Strong Python development skills with an emphasis on clean, scalable, and modular code.

— Hands-on experience working with LLMs and agent frameworks.

— Solid understanding of RAG architecture, vector search concepts (cosine similarity, MMR, late

interaction), and system design.

— Experience building multi-step agentic workflows and reasoning systems.

— Familiarity with AI performance metrics, model drift detection, and operational monitoring.

— Awareness of AI limitations, including latency, hallucination risks, and explainability challenges.

— Experience with DSPy or other prompt optimization tools is a plus.

— A curious, experimental mindset with a passion for testing emerging AI tools and frameworks.

— Bachelor’s degree in Computer Science or equivalent — preferred.