AI Engineer

Responsibilities

• AI System Implementation
• Implement machine learning models, inference services, and supporting APIs
• Contribute to the development of training, evaluation, and deployment workflows
• Build data ingestion and feature engineering components aligned to defined architecture
• Ensure reliability, performance, and stability of AI services in production environments
• AI Pipelines & Infrastructure
• Contribute to the development and orchestration of AI pipelines and agentic workflows.
• Support LLMOps processes for automated model deployment, versioning, and prompt management.
• Implement monitoring and observability to track token usage, model drift, and hallucinations.
• Debug and resolve complex issues across LLM layers, data ingestion, and cloud infrastructure.
• Research-to-Production Support
• Collaborate with senior engineers to operationalize research prototypes
• Implement evaluation metrics and validation processes
• Support rollout and iteration of AI features based on performance data
• Collaboration & Delivery
• Work closely with product and engineering teams to implement AI-driven features
• Participate in sprint planning, estimation, and technical discussions
• Contribute to documentation and shared engineering standards
• Communicate progress, blockers, and risks clearly
• Required Skills & Qualifications
• 3-5 years of experience in AI/ML engineering or applied machine learning
• Experience building and deploying ML models in production environments
• Strong software engineering background (Python or similar)
• Familiarity with distributed systems and scalable data processing
• Experience contributing to ML pipelines and automated deployment workflows
• Working knowledge of MLOps concepts (model versioning, monitoring, CI/CD)
• Ability to debug issues across model, application, and infrastructure layers
• Strong problem-solving skills and attention to detail
• Effective communication skills within technical teams

Requirements

• Exposure to generative AI or LLM-based systems
• Familiarity with retrieval-augmented generation (RAG) architectures
• Experience working with cloud-based AI platforms
• Exposure to infrastructure-as-code or DevOps practices
• Experience working in consulting or delivery-focused environments
• Hands-on AWS experience supporting cloud-native or AI/ML production systems.
• AWS certifications (Associate or Professional level) or equivalent practical AWS expertise.
• Personal Competencies
• Execution-Focused - Delivers high-quality implementations within established architecture
• Engineering Discipline - Writes reliable, maintainable, and well-tested code
• Collaborative - Works effectively within cross-functional teams
• Problem-Solving Mindset - Investigates issues methodically across layers
• Ownership - Takes responsibility for assigned work from implementation through release
• Growth-Oriented - Seeks feedback and continuously improves technical craft
• Why Join Robots & Pencils?
• This is a role for builders who want to sharpen their craft, grow quickly, and deliver impactful AI systems within an elite global engineering ecosystem.

Additional Information

Robots & Pencils is seeking an AI Engineer to design, build, and deploy production-grade AI systems that deliver measurable business value. This is a hands-on engineering role focused on implementation and delivery. You will contribute to scalable AI systems and ML pipelines, working within established architectural direction while collaborating closely with senior engineers, product managers, and cross-functional teams. You will be expected to deliver independently on well-defined features, contribute to system design discussions, and maintain high standards for reliability, performance, and maintainability.

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