AI Engineer

Teserac, Inc. is building neuron™, a unified AI-native platform for data center observability, intelligence, and workflow automation. neuron™ processes real-time telemetry from thousands of sensors, meters, and control systems across heterogeneous environments, helping infrastructure owners monitor, analyze, automate, and proactively manage power operations with full situational awareness. You will work on a system designed to act as an always-on co-pilot for operators, detecting anomalies, correlating events, and surfacing recommendations 24/7.

This role is onsite in Santa Clara, CA and spans the full AI lifecycle. You will build production-grade AI powered applications and automation workflows, combining data pipelines, model integration, agentic orchestration, evaluation, and production support. Research thinking matters here, but the focus stays on translating ideas into systems that work in the physical world.

Benefits

• Health Care Plan: Medical, Dental & Vision
• Paid Time Off: Vacation, Sick & Public Holidays
• Free Food & Snacks
• Stock Option Plan
• 401(k)

What you will work on

• Multi-agent orchestration and LLM-driven triage workflows
• Time-series modeling for anomaly detection, failure prediction, and health forecasting on multivariate telemetry
• Retrieval-augmented knowledge systems for operations teams
• Data and ML pipelines, including ingestion, ETL, and dataset construction
• Fine-tuning and post-training of language models for operational use cases
• AI observability, evaluation frameworks, and production performance benchmarking

Responsibilities

• Design, develop, and maintain AI-powered applications and automation workflows
• Integrate and optimize LLM APIs for production use cases
• Build and refine retrieval and knowledge-augmentation pipelines
• Develop evaluation frameworks to benchmark AI system performance
• Implement monitoring, tracing, and debugging capabilities for AI systems
• Read and synthesize relevant research, bring ideas forward, and debate them with the team
• Contribute to AI architecture decisions and production hardening
• Stay current with the rapidly evolving AI/ML landscape

Requirements

• Degree in Computer Science, Machine Learning, Mathematics, or a related field, or equivalent demonstrated experience
• Strong proficiency in Python
• Solid software engineering fundamentals, including testing, version control, and CI/CD
• Experience working with LLM APIs in applied contexts
• Familiarity with agentic system concepts, including tool/function-calling and agent frameworks
• Daily use of AI-assisted coding tools (Cursor, Copilot, Claude Code, etc.)
• Ability to read ML research papers and translate ideas into practical experiments
• Strong analytical thinking and clear communication, including the ability to argue a position and update it when wrong

Technology you may use

• Python, Cursor, Copilot, Claude Code
• LLM APIs, LangGraph, LangChain, MCP
• PyTorch, vLLM
• GCP (Vertex AI)
• Niagara, BACnet, Modbus

Role fit

• Excited about AI and infrastructure, with the ability to learn fast and go deep
• Comfortable holding your own in technical debate and updating ideas when evidence changes
• Proactive and curious, with strong engineering fundamentals to ship reliable systems
• Interested in technically hard work that matters in the physical world
• Open to both junior and senior candidates, with strong fundamentals and self-directed learning

Preferred

• Professional AI/ML engineering experience (any level)
• Experience building agentic systems using frameworks such as LangGraph or LangChain; MCP a plus
• Time-series modeling for forecasting and anomaly/failure prediction on multivariate data
• Experience fine-tuning or post-training language models
• PyTorch and/or model serving frameworks (for example, vLLM)
• Experience building data and ML pipelines, including ingestion, ETL, and dataset construction
• Familiarity with cloud ML platforms, particularly GCP (Vertex AI)
• LLM evaluation and benchmarking, including harness design and eval loop development
• Domain experience with data center or industrial telemetry, BMS/OT protocols (Niagara, BACnet/Modbus)
• Background in DevOps, distributed systems, or observability tooling