AI Engineer

As a core member of the engineering team, you will design and implement AI-driven applications including retrieval-augmented systems, conversational agents, document intelligence solutions, and generative content tools. You will collaborate closely with product, data, and strategy teams to translate business objectives into scalable AI architectures., * Design and deploy machine learning and LLM-based solutions across use cases such as document processing (OCR), RAG pipelines, AI agents, and generative applications.

• Develop, test, and refine prompt strategies to improve output quality and alignment with business requirements.
• Evaluate, fine-tune, and benchmark ML and language models using structured experimentation and performance metrics.
• Build and maintain data pipelines for model training, evaluation, and deployment workflows.
• Collaborate cross-functionally to integrate AI capabilities into client-facing platforms and internal tools.
• Deploy models to production environments and monitor system performance, reliability, and cost efficiency.
• Stay current with advancements in generative AI, deep learning, and emerging frameworks to continuously enhance system capabilities.

Artificial Intelligence (AI), Machine Learning, Business Solutions, Artificial Intelligence (AI), Production Systems, Deep Learning, System Architecture, Operational Measurement, Open Source, Ecosystems, The ideal candidate has strong experience working with leading commercial and open-source LLM ecosystems and understands how to optimize, evaluate, and productionize AI systems responsibly and efficiently., * 5+ years of experience in AI/ML engineering or related roles.

• Bachelors or Masters degree in Computer Science, Engineering, or a related technical discipline.
• Hands-on experience working with major LLM platforms (commercial APIs and open-source models).
• Strong background building retrieval-augmented generation systems, LLM pipelines, or agent-based architectures.
• Proficiency in Python and experience with deep learning frameworks such as PyTorch (or equivalent).
• Solid foundation in machine learning, neural networks, and natural language processing.
• Experience evaluating model performance using appropriate validation and benchmarking techniques.
• Experience working with relational databases (e.g., PostgreSQL) and modern data warehouse systems.
• Strong analytical and problem-solving skills.
• Ability to communicate effectively across technical and non-technical stakeholders.

Preferred Experience

• Contributions to open-source AI projects or involvement in research communities.
• Experience deploying AI systems on major cloud platforms (AWS, GCP, or Azure).
• Familiarity with distributed data processing technologies (e.g., Spark or similar frameworks).
• Exposure to domain applications in sectors such as financial services, healthcare, retail, or enterprise technology.