Senior AI Engineer I
ultipro
Job Description
- Architect end-to-end AI systems that align business objectives, technical constraints, security requirements, and operational realities.
- Design intelligent workflows that support reasoning, planning, task decomposition, retrieval augmentation, tool use, and multi-step execution.
- Define system patterns for AI applications, including prompt-driven workflows, model routing, fallback strategies, context management, and state handling.
- Develop innovative approaches for knowledge discovery, classification, prediction, ranking, anomaly detection, and pattern extraction across structured and unstructured data.
- Build and optimize multimodal AI solutions involving text, image, and tabular data for advanced analytics and decision-making use cases.
- Design robust evaluation frameworks for AI systems, including offline testing, benchmark creation, quality scoring, red teaming, regression testing, and human-in-the-loop validation.
- Apply strong software architecture principles to ensure modularity, observability, maintainability, scalability, and fault tolerance of AI systems.
- Lead the design of secure AI integrations with APIs, enterprise data sources, workflow engines, and external tools.
- Develop and maintain scalable data pipelines, feature pipelines, and model pipelines supporting training, inference, and continuous improvement.
- Use cloud and distributed computing platforms to support model development, orchestration, deployment, and monitoring at enterprise scale.
- Apply statistical analysis and experimental methods to interpret results, validate hypotheses, measure improvements, and quantify model uncertainty.
- Establish model lifecycle processes covering versioning, traceability, reproducibility, testing, deployment, rollback, and monitoring.
- Collaborate closely with software engineers, data engineers, product teams, and stakeholders to define architecture, requirements, and implementation plans.
- Demonstrate proven product experience in designing and delivering agentic workflows, AI workflow orchestration, RAG-based architectures, and agentic coding solutions.
- Conduct proof-of-concepts for emerging tools, frameworks, and methods, and determine production readiness based on architectural, security, and performance criteria.
- Create clear technical documentation, architecture diagrams, decision records, experiment summaries, and executive-ready updates.
- Monitor AI system behaviour, data drift, model quality, latency, throughput, and operational reliability to ensure service-level expectations are met.
- Mentor junior AI engineers and data scientists on architecture patterns, implementation practices, evaluation methods, and responsible AI principles.
- Present technical work internally and externally through design reviews, workshops, technical forums, and conferences.
- Contribute to innovation through patents, invention disclosures, and reusable technical assets.
- Ensure AI solutions adhere to responsible AI standards, including safety, transparency, fairness, privacy, governance, and compliance.
- Drive software development teams using a structured spec-driven development (SDD) approach, with strong emphasis on clear specifications, implementation traceability, testing rigor, and delivery quality.
- Support and guide teams in agentic coding workflows, including AI-assisted development, code generation, code review support, debugging assistance, and automated test creation.