Artificial Intelligence (AI) Engineer

About the Job

We are hiring an AI Engineer to design, build, and productionize AI solutions that solve business problems. You will collaborate with product, data, and software teams to deliver PoCs, validate them with stakeholders, and evolve the most promising ideas into robust MVPs and production services.
Your scope includes model and pipeline design, evaluation for accuracy, scalability and cost, integration with existing systems, observability and CI/CD for ML, and continuous optimization. You will also contribute to documentation, share best practices in an agile-minded environment.

Main Requirements

• Degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field.
• At least 3 years of professional experience building AI or ML solutions
• Good knowledge of PyTorch or TensorFlow, Python ecosystems, and MLOps practices for deploying and monitoring models.
• Knowledge of data processing at scale and API-first integration patterns for AI services.
• Comfortable collaborating with cross-functional teams to translate business needs into technical solutions, from PoC to MVP to production.
• Nice to have: experience with distributed data frameworks, vector databases, and cloud AI services.

Personality Traits

• Proactive;
• Result-driven;
• Growth mindset;
• Teamplayer.

What Can You Expect

Work on end-to-end AI initiatives, from ideation and PoC to scalable MVPs used in real-world scenarios. You will join a collaborative team with strong engineering standards, influence technical decisions, and see your work deliver measurable business value. Expect a flexible hybrid setup, opportunities to mentor, and a culture that values learning, experimentation, and high-quality delivery.

Tech Stack

Python; PyTorch; TensorFlow; LangChain; Hugging Face Transformers; Retrieval-Augmented Generation (RAG); Vector Databases (FAISS, Pinecone, pgvector); Prompt Engineering; FastAPI; Docker; Kubernetes; MLflow; Weights & Biases; Pandas; NumPy; Apache Spark; Apache Airflow; AWS SageMaker; GCP Vertex AI; Azure ML; Git; CI/CD; REST APIs; Kafka.

Work Model

Hybrid

Internal Ref: Developer

Date Posted: 2025-08-18

Valid Through: 2025-12-18