Artificial Intelligence Engineer 

Job Description

The Role :

We are looking for a seasoned AI Engineer who thrives at the intersection of AI research and pragmatic engineering. You will work alongside our consulting teams to design, build, and deploy cutting-edge AI solutions for clients across sectors. You bring deep technical fluency in large language models, retrieval-augmented generation, and machine learning – and you are native to AI-assisted development environments like Cursor, GitHub Copilot, and Replit.

As a practitioner of vibe coding, you know how to move fast without breaking things: using AI as a creative engineering partner, not just a code autocomplete tool. You will mentor colleagues, shape best practices, and help Ardberg AI stay ahead of the curve.

Key Responsibilities :

– Design and implement end-to-end AI systems including RAG pipelines, vector search infrastructure, and LLM-powered applications for enterprise clients.

– Champion vibe coding practices by leveraging AI-assisted development tools (Cursor, GitHub Copilot, Replit, etc.) to accelerate delivery without compromising code quality.

– Lead the fine-tuning, evaluation, and deployment of large language models (e.g., GPT, Claude, Llama, Mistral) tailored to client-specific use cases.

– Build and maintain prompt engineering frameworks, evaluation harnesses, and guardrail systems for production LLM deployments.

– Architect scalable vector database solutions using tools such as Pinecone, Weaviate, Qdrant, or pgvector to power semantic search and knowledge retrieval systems.

– Collaborate with cross-functional consulting teams to translate business requirements into technical AI architectures and working prototypes.

– Conduct code reviews, enforce engineering best practices, and contribute to the internal AI engineering playbook.

– Stay current with rapidly evolving AI research and tooling; evaluate and integrate new techniques and libraries as appropriate.

– Mentor junior AI engineers and contribute to a culture of continuous learning and knowledge sharing.

Required Qualifications :

– 5 – 8 years of professional software engineering experience, with a significant focus on AI/ML systems over at least the last 3 years.- Hands-on experience with AI-assisted development tools (Cursor, GitHub Copilot, Replit, Amazon CodeWhisperer, or equivalent) – you do not just use them, you master them.

– Deep expertise in large language models: prompt engineering, evaluation, fine-tuning, and API integration (OpenAI, Anthropic, Hugging Face, Cohere, etc.).

– Strong experience with Retrieval-Augmented Generation (RAG) architectures, embedding models, and vector databases (Pinecone, Weaviate, Qdrant, Chroma, pgvector).

– Proficiency in Python for ML/AI engineering; familiarity with frameworks such as LangChain, LlamaIndex, Haystack, or similar orchestration libraries.

– Experience with ML fine-tuning workflows including data preparation, PEFT/LoRA, RLHF, and model evaluation pipelines.

– Solid understanding of cloud AI services and deployment (AWS SageMaker, Azure AI, Google Vertex AI, or equivalent).

– Excellent communication skills – able to explain complex AI systems to technical and non-technical stakeholders alike.

Nice To Have :

– Experience working in a consulting or client-services environment.

– Familiarity with agentic AI frameworks (AutoGen, LangGraph) and multi-agent orchestration

patterns.

– Prior work with multimodal models (vision + language) or speech AI systems.

– Contributions to open-source AI projects or published research.

– Knowledge of MLOps tools and practices (MLflow, Weights & Biases, DVC, Kubeflow).

– Exposure to edge AI deployment or on-premise LLM hosting (Ollama, vLLM, TGI).

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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