Data AI Engineer

About Mindtech

Mindtech is your gateway to exciting, impactful technology projects. We specialize in staff augmentation and end-to-end software outsourcing, connecting top Latin American talent with global opportunities. Our agile approach ensures exceptional service and innovative solutions for our clients.

About the Role

We are seeking an experienced AI Engineer to join our dynamic team and drive the design, development, and deployment of cutting-edge artificial intelligence solutions. The ideal candidate has a strong foundation in machine learning, deep learning, and large-scale data systems, with hands-on experience in building production-grade AI applications. You will collaborate with cross-functional teams including data engineers, product managers, and software developers to deliver impactful AI-driven applications.

Key Responsibilities

• Design, develop, and deploy AI/ML models for enterprise-grade applications.

• Build end-to-end ML pipelines including training, evaluation, optimization, deployment, and monitoring.

• Architect and develop agentic AI systems including multi-agent workflows, RAG chatbots, and intelligent automation.

• Build RAG (Retrieval-Augmented Generation) applications tailored to insurance workflows.

• Develop multi-agent orchestration systems for complex P&C processes.

• Drive company-wide AI adoption by identifying high-impact use cases across P&C insurance functions.

• Conduct experimentation and research with state-of-the-art AI techniques and frameworks.

• Establish AI development standards, best practices, and governance frameworks.

• Collaborate with our Python-strong data engineering team on backend integrations.

• Design and implement AI solutions leveraging Microsoft Foundry and Copilot Studio, enabling enterprise-ready generative AI use cases and integrations.

Required Qualifications

• Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field (PhD preferred).

• 5+ years of professional experience in AI/ML engineering, with a proven track record of building and deploying production-grade AI systems.

• 2+ years of experience in data warehouse with Snowflake cortex, and orchestration with airflow

• Proven, hands-on experience with: Copilot Studio (designing, extending, and operationalizing copilots), Microsoft / Azure AI Foundry and Azure OpenAI Service
• Expertise in Python with proficiency in leading AI/ML frameworks such as TensorFlow, PyTorch, Hugging Face, and Scikit-learn.
• Hands-on experience with MLOps platforms, including Kubeflow, MLflow, and Azure Machine Learning (Vertex AI/SageMaker

• acceptable).

• Strong applied experience with LLMs (Large Language Models), RAG (Retrieval-Augmented Generation) techniques, and vector databases (e.g., Pinecone, Weaviate, FAISS).

• Practical experience with agent frameworks, workflow orchestration, and multi-agent systems.

• Proven hands-on experience with Microsoft Foundry and Copilot Studio for building, deploying, and governing generative AI and copilots in enterprise environments.
• Proficiency in full-stack development, including web frameworks, backend systems, API development (REST, GraphQL), and deployment on cloud infrastructure (Azure strongly preferred; AWS/GCP acceptable).

• Solid knowledge of containerization and orchestration tools such as Docker and Kubernetes.

• Familiarity with AI security, compliance, and governance standards, particularly for regulated industries.

• Hands-on experience with multiple database platforms, including SQL

• Server, Oracle, and Snowflake.
• Ability to thrive in ambiguity, demonstrating strong ownership, adaptability, and problem-solving in fast-paced, high-trust environments.
• Domain knowledge in Property & Casualty (P&C) insurance or experience addressing business problems in regulated industries is a strong plus.

We Offer

- 100% remote work

- Salary in USD

- Referral program

-Growth opportunities in a fast-scaling startup

-A global, multicultural work environment

Originally posted on Himalayas