Mid-Level AI Engineer - Agentic Systems & Computer Vision

About the role

Dogma Group is hiring a mid-level AI engineer for a client services environment. The role delivers AI solutions under real deadlines and changing requirements, focusing on agentic systems backed by LLMs and computer vision applications, deployed as containerized, production-ready services. It involves multi-agent architectures, modern retrieval pipelines and standardized agent protocols.

Key responsibilities

• Design, build and deploy single-agent and multi-agent systems with LLMs, using LangChain and LangGraph or building from scratch in Python with Pydantic
• Connect agents to tools, data sources and other agents via protocols such as MCP and A2A
• Build production-grade RAG pipelines with hybrid retrieval and reranking with cross-encoders
• Work with vector databases such as Pinecone, Weaviate, Qdrant or pgvector
• Integrate computer vision solutions (object detection, image classification, segmentation, OCR) with OpenCV, TensorFlow or PyTorch and vision-language models
• Containerize services with Docker and deploy them on cloud and on-premise environments
• Maintain models and services in production with observability, tracing and evaluation pipelines
• Translate client requirements into technical scope, build data pipelines and communicate progress to technical and non-technical stakeholders
• Evaluate new AI tools, models and frameworks for adoption

Required profile

• 3+ years of experience in AI/ML development and deployment; Bachelor's degree in Computer Science, Computer Engineering, Data Science, Machine Learning or a related field
• Foundational knowledge of machine learning and deep learning, and of statistics, probability, linear algebra and calculus as applied to ML and DL
• Strong knowledge of GenAI and LLMs, with hands-on experience building LLM-based applications
• Experience with computer vision libraries such as OpenCV, YOLO and PIL
• Comfort in a fast-paced, client-facing environment with shifting priorities
• Awareness of privacy, data security and ethical considerations in GenAI

Required skills

• Python, Pydantic, LangChain, LangGraph, MCP and A2A
• Pinecone, Weaviate, Qdrant, pgvector, hybrid search and reranking
• TensorFlow and PyTorch
• Docker and at least one major cloud platform (Azure preferred)