Senior AI Engineer

About the Role We are looking for a passionate Senior AI Engineer to join our growing AI team and help design, build, and deploy cutting‑edge Generative AI solutions.

You will play a key role in developing intelligent conversational systems, advanced Retrieval‑Augmented Generation (RAG) architectures, and autonomous AI agents.

Working across the full AI lifecycle, you will be responsible for data ingestion, semantic indexing, model orchestration, deployment, observability, and continuous optimization of production‑grade AI applications.

This is an opportunity to work with the latest LLM technologies and help shape innovative AI products that deliver real business value.

Key Responsibilities Design and develop advanced conversational AI solutions leveraging Large Language Models (LLMs) and RAG architectures.

Optimize information retrieval pipelines using embeddings, vector search technologies, and reranking models to improve response relevance and accuracy.

Design and implement autonomous AI agents capable of utilizing external tools and services through Model Context Protocol (MCP) environments.

Build robust data ingestion and semantic indexing pipelines for complex document types, including structured technical documentation, tables, and multi‑column PDFs.

Implement intelligent chunking and document processing strategies to maximize retrieval effectiveness.

Containerize and deploy AI services using modern cloud‑native technologies, ensuring scalability, reliability, and maintainability.

Monitor model performance, costs, latency, and output quality through LLMOps practices and observability platforms.

Analyze prompts, traces, and user feedback to continuously enhance AI system effectiveness and user experience.

Collaborate closely with technical teams and business stakeholders to deliver innovative AI‑driven solutions.

Requirements Proven experience with Python and modern web development frameworks such as Fast API or Flask for building RESTful APIs.

Strong hands‑on experience with LLM orchestration frameworks, including Lang Chain, Llama Index, or direct LLM API integrations.

Deep understanding of Retrieval‑Augmented Generation (RAG) architectures and semantic search systems.

Experience working with Vector Databases such as Qdrant, Milvus, Pinecone, Weaviate, or pgvector.

Solid knowledge of Prompt Engineering techniques and AI agent development through function calling and tool integration.

Experience with containerization using Docker and orchestration with Kubernetes.

Familiarity with enterprise cloud environments, particularly Google Cloud Platform (GCP) and/or Microsoft Azure.

Experience managing source control, CI/CD pipelines, and software delivery processes using Git Lab.

Hands‑on experience with LLM observability and monitoring platforms, particularly Langfuse, including prompt tracking, latency monitoring, token usage analysis, and user feedback collection.

Preferred Qualifications Experience with automated RAG evaluation frameworks such as Ragas or Tru Lens.

Strong knowledge of advanced document parsing techniques, including OCR and layout detection.

Practical experience fine‑tuning open‑source models using approaches such as Lo RA and QLo RA.

Strong problem‑solving mindset and ability to navigate uncertainty within a rapidly evolving AI landscape.

Product‑oriented attitude with a focus on delivering AI solutions that solve real user problems.

Excellent communication skills and the ability to effectively interact with both technical teams and business stakeholders.

Why Join FORFIRM?At FORFIRM, you will have the opportunity to work on innovative AI projects within a highly collaborative and forward‑thinking environment.

You will contribute to the development of next‑generation AI solutions while continuously expanding your technical expertise through challenging and impactful initiatives. #J-18808-Ljbffr