Note: The job is a remote job and is open to candidates in USA. Phaidra is building AI-powered control systems for industrial automation that enable facilities to learn and improve over time. The Senior AI Research Engineer will develop agent reasoning frameworks, prompts, guardrails, evaluation systems, behavioral patterns, and feedback loops for reliable and useful industrial AI products. The role also involves analyzing production interactions and collaborating across research, engineering, product, domain, and customer-facing teams.
Responsibilities
- You will own key parts of the research, behavioral quality, and applied intelligence layer of Phaidra’s agentic products. This includes agent reasoning patterns, personalities, prompts, guardrails, evaluation systems, domain-informed behavior, and the feedback loops used to improve agent performance over time
- Design and improve agent reasoning frameworks that help Phaidra’s agents solve complex industrial problems using tools, telemetry, ontology, historical context, and domain logic
- Define and maintain agent personalities, communication patterns, behavioral boundaries, and escalation rules across Phaidra’s agent portfolio
- Develop prompts, system instructions, tool-use policies, and execution loops that help agents act consistently and effectively in industrial contexts
- Build and maintain agent evaluations that measure behavioral quality, domain correctness, user usefulness, safety, hallucination risk, tool-use reliability, and alignment with business requirements
- Translate subject-matter expertise into reusable reasoning patterns, decision frameworks, eval rubrics, and behavioral tests
- Analyze production interactions, user feedback, telemetry, and qualitative signals to identify where agents are succeeding, drifting, or failing
- Partner with Agent Reasoning, Ontology, AI Platform, Product, Solutions, and customer-facing teams to improve agent reliability and usefulness
- Help agents reason over derived tags, operational math, alarms, recommendations, facility context, and customer-specific constraints
- Track state-of-the-art developments in agentic AI, evaluation methods, prompting, tool use, behavioral assurance, and domain-specialized LLM systems
- Contribute to Phaidra’s broader agent strategy by ensuring our agents are not only technically capable, but trustworthy, interpretable, and valuable to users
- You will learn Phaidra’s product, customer environments, and agent portfolio
- You will review the current architecture of our agents
- You will study existing prompts, guardrails, evals, user feedback, and known behavioral failure modes
- You will meet partners across Agents, Product, AI Platform, Solutions, Engineering, and Data Science
- You will shadow real or representative agent workflows involving operational insights, alarms, recommendations, or user interactions
- You will have a solid understanding of how Phaidra’s agents reason, communicate, and use tools today
- You will ship your first meaningful improvement to an agent prompt, reasoning pattern, eval, or feedback workflow
- You will identify key behavioral risks, drift patterns, or quality gaps in one or more agents
- You will begin defining standards for agent tone, uncertainty handling, escalation, domain reasoning, and evaluation quality
- You will independently own a behavioral improvement or evaluation initiative for a production agent
- You will have established a repeatable process for measuring and improving agent quality
- You will help define the AI research and behavioral assurance roadmap for the Agents Team
- You will become a trusted internal voice on whether agents are reasoning correctly, behaving usefully, and operating safely
Skills
- Strong applied AI, machine learning, data science, research engineering, or software engineering background
- Experience working with LLMs, agents, copilots, autonomous workflows, or other AI systems that reason over tools and context
- Ability to translate ambiguous product and domain problems into concrete experiments, prototypes, evals, and production improvements
- Experience evaluating model or agent outputs using qualitative and quantitative methods
- Strong product judgment: you understand what makes an AI system actually useful to users, not merely technically impressive
- Excellent written communication skills, with an ability to craft precise instructions, behavioral guidelines, research notes, and evaluation criteria
- Comfortable collaborating across engineering, product, domain experts, and customer-facing teams
- Ability to reason about ambiguity, uncertainty, edge cases, and failure modes in AI systems
- Good working knowledge of Python
- Shares Phaidra's company values: Agency, Velocity, Craft, Truth
- Phaidra is based in the USA, but we are 100% remote with no physical office. We hire employees internationally with the help of our partner, OysterHR
- • \•We are seeking teammates who are based in the UK or North America (Eastern timezone)
- Phaidra only hires individuals who are legally authorized to work in the specified location(s) above
- Candidates requiring visa sponsorship, either now or in the future, are not eligible for hire
- Experience designing or evaluating LLM agents, tool-using AI systems, prompt systems, guardrails, eval harnesses, red-teaming, or behavioral QA
- Experience with HVAC, datacenter operations, EPMS, BMS/BAS, industrial controls, alarm triage, or root-cause analysis
- Experience with time-series analysis, anomaly detection, derived tags, operational math, symbolic reasoning, or model-informed decision-making
- Experience with RAG systems, knowledge graphs, ontologies, semantic retrieval, or context engineering for AI agents
- Experience building dashboards, evaluation datasets, labeling workflows, or feedback loops for AI products
- Familiarity with agent frameworks, MCP/tool interfaces, LLM observability, or production AI infrastructure
- Track record of turning research ideas into reliable product capabilities
Benefits
- This position is eligible for equity.
- We are a 100% remote company.
- Meaningful equity.
- Outsized responsibilities & professional development.
- Training is foundational; functional, customer immersion, and development training.
- Medical, dental, and vision insurance (exact benefits vary by region).
- Unlimited paid time off, with a required minimum of 20 days per year.
- Paid parental leave (exact benefits vary by region).
- Flexible stipends to support your workspace, well-being, and continued professional development.
- Company MacBook.
- Our culture is documentation-first, and we prioritize asynchronous communication to support focus and flexibility across time zones.
- Weekly all-hands meetings help us align and build strong relationships.
- We regularly host virtual team-building activities and social events to maintain a sense of camaraderie.
Company Overview