AI/ML Engineering Manager

CORSAIR is building a production-grade AI/ML capability spanning intelligent automation, agentic systems, predictive analytics, and data engineering. As AI/ML Engineering Manager, you will lead a team while staying hands-on as a technical contributor. You will architect and build AI/ML systems that directly affect how the business operates, engage stakeholders across functions to surface automation opportunities, and own the full AI/ML lifecycle end-to-end.

Technical Leadership (40%)

• Lead and manage a team of engineers and contractors across multiple AI/ML and automation workstreams; own delivery standards, architecture quality, and team development

• Architect agentic AI systems end to end: multi-agent orchestration, tool use, memory management, human-in-the-loop controls, and evaluation frameworks

• Own the AI/ML technical roadmap; evaluate build vs. buy tradeoffs and align with VP-level stakeholders

• Engage business stakeholders across functions to map workflows, identify automation opportunities, and translate operational requirements into AI-driven solutions

Individual Contribution (60%)

• Design and ship production-grade agentic AI systems using modern LLM orchestration frameworks; own orchestration logic, state management, and output evaluation

• Build durable, fault-tolerant automation pipelines using workflow orchestration tools such as Temporal; design for reliability, retry logic, and long-running distributed tasks

• Develop and deploy predictive ML models; own the full lifecycle from feature engineering through production monitoring

• Implement RAG systems, vector retrieval pipelines, and prompt engineering strategies at scale; apply LLM fine-tuning when it delivers better ROI than retrieval or prompting

• Build and maintain data engineering pipelines (dbt, Dagster, Spark, Microsoft Fabric); diagnose data quality issues that affect AI system reliability

• Own MLOps infrastructure: experiment tracking, model versioning, retraining pipelines, and drift detection

What You Bring

Required

• 6+ years in AI/ML engineering or applied data science, with at least 1-2 years in a technical lead role

• Proven experience designing and deploying agentic AI systems in production: orchestration, tool use, memory, and evaluation

• Strong Python and SQL; hands-on with LLM frameworks (LangChain, LangGraph, CrewAI, Strands, or equivalent) and cloud AI platforms (AWS Bedrock, Azure AI Foundry, or Microsoft Fabric)

• Experience with durable workflow orchestration tools such as Temporal, Airflow, or Step Functions

• Solid ML fundamentals and end-to-end pipeline ownership; experience with data engineering tooling (dbt, Dagster, Spark)

• Demonstrated ability to lead engineers technically and communicate tradeoffs to VP-level stakeholders

Preferred

• Experience in gaming, consumer electronics, or hardware/peripherals

• Familiarity with LLM fine-tuning (LoRA, PEFT), vector databases, generative AI for images, or MLOps tooling (MLflow, W&B)

• Exposure to Docker, Kubernetes, and CI/CD pipelines for ML workloads

• Experience working cross-functionally with Product, Finance, Legal, and Operations stakeholders

The starting base pay for this position is $170,000,$210,000 USD.