AI Engineer – L3
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Job Description
AI Engineer at Robots and Pencils supporting the delivery of LLM-powered applications for enterprise clients. Collaborating with senior engineers to implement and evolve intelligent features using modern tooling.
Responsibilities:
- Contribute to building and optimizing Retrieval Augmented Generation (RAG) pipelines, including document ingestion, chunking strategies, and retrieval workflows
- Develop and refine prompts and guardrails supporting domain-specific LLM applications
- Support implementation of hallucination mitigation and response validation techniques
- Build embeddings-based semantic search and recommendation capabilities.
- Assist in testing AI features with users and iterate based on feedback and performance data
- Support implementation of evaluation frameworks measuring LLM quality and relevance
- Assist with monitoring production AI systems and identifying quality or performance issues
- Analyze evaluation data to improve prompts, retrieval strategies, and outputs
- Participate in debugging and continuous improvement of live AI systems
- Develop backend services in Python supporting AI workflows and application integration
- Work with vector databases to enable semantic search and retrieval
- Integrate AI features into user-facing products alongside product and engineering teams
- Support scalable and secure deployment of AI capabilities aligned with enterprise standards
- Collaborate closely with product managers, designers, and engineers in cross-functional teams
- Participate in agile delivery environments with evolving requirements
- Communicate technical concepts clearly with teammates and stakeholders
- Contribute to delivery outcomes across experimentation, iteration, and production deployment
Requirements:
- 4+ years of professional software engineering experience
- 1–3 years working with applied AI/ML, data platforms, or LLM-powered applications
- Experience building backend services using Python
- Exposure to LLM applications including prompt engineering or RAG workflows
- Familiarity with embeddings, semantic search, or vector databases
- Experience integrating APIs or cloud services into production applications
- Understanding of software engineering best practices including testing and observability
- Ability to work effectively in ambiguous or fast-moving environments
- Bachelor’s degree in Computer Science, Engineering, Data Science, or equivalent practical experience
Benefits:
- Work on production AI solutions delivering measurable client impact
- Learn alongside senior engineers across the full AI lifecycle
- Exposure to modern GenAI delivery including RAG, evaluation, and observability
- Collaborative teams with direct exposure to enterprise clients
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