Applied AI Engineer

Calimala partners with enterprises across the Gulf and Europe to design, build, and scale Data & AI teams. As an Applied AI Engineer, you’ll join a network of practitioners who understand both what modern AI can do—and what it takes to make it work inside real products, workflows, and constraints.

This role sits at the intersection of models, data, and user experience. You’ll design and build AI-powered features—often using LLMs, retrieval, and classic ML—across use cases such as copilots, document understanding, search and recommendation, or intelligent automation.

What you'll be doing

As an Applied AI Engineer at Calimala, you’ll lead and support engagements where AI is visible to end users and tied directly to business outcomes. One project might involve designing a retrieval-augmented LLM workflow to support operations teams; another could focus on embedding AI-driven decisioning into an existing product, from data ingestion through to UX.

“We treat AI features like any other product: clearly scoped, testable, explainable, and measured by the value they create — not just model scores.”

You’ll work closely with product owners, domain experts, and data and platform teams to frame problems, select appropriate AI approaches, and iterate quickly from prototype to production. You’ll help define evaluation strategies (offline and in-product), design safe interaction patterns, and ensure AI components are observable, maintainable, and cost-aware in real environments.

Who we're looking for

You’re comfortable moving between experimentation and engineering. You can prototype ideas quickly, pressure-test them with real data and users, and then turn the winning approach into clean, production-ready services.

You think in systems and workflows, not just models. You care about how users interact with AI, how failures are handled, and how behavior remains predictable over time.

You’ve likely worked in applied ML, LLM-powered products, or data-heavy engineering roles where AI was embedded into real systems—not just demos. At Calimala, we value depth, accountability, and partnership: you take ownership of the end-to-end AI solution, not just the model in the middle.

• Strong experience building AI-powered applications (LLM-based and/or traditional ML) from idea through to production

• Proficiency in Python, with the ability to write production-quality code (services, APIs, tests—notebooks alone)

• Solid understanding of how models consume data and how data quality, structure, and freshness impact AI behavior

• Practical experience designing and implementing LLM application patterns, such as: RAG, Prompt and system design, Tool-calling / function-calling workflows, Basic agentic patterns where appropriate

• Experience evaluating AI behavior beyond accuracy: relevance, consistency, latency, cost, and user trust

• Hands-on familiarity with modern AI/LLM tooling such as: Core ML libraries (e.g. PyTorch or TensorFlow at an applied level), LLM orchestration frameworks (e.g. LangChain or similar), Semantic search / vector databases (e.g. FAISS, Pinecone, Weaviate, or equivalents)

• Experience integrating models into products via APIs, microservices, or workflow engines

• Working knowledge of cloud platforms (Azure, AWS, or GCP), including managed AI/ML or LLM services

We’re looking for practitioners who see Applied AI as the craft of building useful, durable systems. People who enjoy collaborating across disciplines, validating ideas with users, and shipping AI features that teams come to depend on — not just impressive demos.