Pioneering the future of Generative AI

Come grow with us at the frontier of AI. ArcFusion is expanding rapidly, and we are looking for passionate engineers to help us deliver the most exciting GenAI projects in the region. We are fully focused on staying ahead of the curve in Enterprise AI, building solutions that truly help our clients.

If you are looking for a high-performing and supportive team where you can work on cutting-edge tech and accelerate your career, we'd love to meet you.

The Role

You will design, develop, and maintain software systems with integrated generative AI. You'll be building APIs, designing databases, writing comprehensive tests, deploying to production, and supporting systems in production — GenAI is your specialization area, not your whole job.

Beyond solid engineering practices, we value the ability to move fast with ideas. We use GenAI coding tools to rapidly prototype and validate concepts, and we're looking for engineers who are comfortable doing the same — turning an idea into a working proof of concept before investing in a full build.

Responsibilities

• Design, implement, and maintain scalable and robust generative AI systems that meet performance, cost-effectiveness, and latency requirements

• Build and maintain production backend services, and APIs that power AI-driven applications

• Implement comprehensive testing strategies — unit, integration, and end-to-end — for AI systems, including evaluation frameworks and monitoring

• Participate in code reviews and contribute to engineering best practices for production AI systems

• Rapidly prototype and build proofs of concept using AI-assisted development tools to validate ideas, demonstrate feasibility, and iterate quickly

• Identify potential applications of generative AI for clients and provide expert advice and guidance on their implementation

Requirements

• Minimum 3 years of experience in software engineering with a focus on building production-ready systems, with exposure to ML or data engineering

• Experience with Python is required. Experience with other modern programming languages is a plus

• Experience with large language models (LLMs), including prompt engineering, RAG architectures, and LLM frameworks for agentic workflows such as LangChain or LangGraph

• Familiarity with vector databases (e.g., Pinecone, Weaviate, Qdrant, pgvector) or other NoSQL database technologies

• Ability to clearly articulate technical concepts and ideas to both technical and non-technical audiences

• Familiarity with cloud platforms such as Azure, AWS, or GCP

• Ability to quickly adapt to changing requirements and evolving technologies

• Familiarity with frontend technologies such as React is a plus

What We Value

We believe the best solutions come from open collaboration. We're looking for engineers who don't just execute tasks — but actively contribute ideas, challenge assumptions, and speak up when they see a better approach. If you thrive in an environment where your voice matters and continuous improvement is the norm, you'll fit right in.

If you're missing some required experience, don't let that stop you. We care more about your fundamentals, your ability to learn quickly, and your passion for building reliable systems than checking every box on a list.

Responsibilities:

• Design, develop, and maintain scalable ETL pipelines to process structured data from various sources.

• Collaborate with AI engineers to define data requirements and ensure smooth data integration with Generative AI solutions and machine learning models.

• Build and optimize data models to support engineering and business needs, ensuring accuracy, consistency, and performance.

• Implement and enforce data quality standards, ensuring data is clean, validated, and up to date.

• Develop storage solutions that enable efficient querying, analysis, and reporting.

• Monitor, troubleshoot, and optimize data pipelines to ensure reliable and timely delivery of data.

• Stay informed on best practices and advancements in data engineering with a focus on extending data platforms with semi- and unstructured data.

Requirements

• Experience: Minimum of 5 years of hands-on experience working with enterprise-grade data platforms.

• Technical Skills:

  • Proficiency in SQL and PySpark and experience with large-scale data processing.

  • Strong command of common data engineering languages such as Python, Scala, or Java.

  • Familiarity with cloud-based data platforms like Databricks, Google BigQuery and DataProc, or AWS Redshift and EMR is a plus.

  • Proficiency in data modeling, including design and implementation of raw data layer (bronze), refined data layer (silver), business/consumption layer (gold)

  • Experience with ETL tools, data pipeline orchestration frameworks (e.g., Apache Airflow), and version control.

  • Knowledge of data warehousing concepts and best practices for large-scale data environments.

• Platform Development Interest: A strong interest in the full stack of platform development, including software engineering, machine learning, front-end development, and generative AI.

• Curiosity: A keen interest in expanding knowledge and skills in generative AI, with the motivation to work on cutting-edge AI-driven projects.

• Problem-Solving Mindset: Ability to solve complex data challenges in innovative and efficient ways.

Collaboration: Ability to work in a cross-functional environment, collaborating with a diverse team of engineers.