AI Engineering Lead

Position Description:

FlexGen is at the forefront of the clean energy revolution, enabling the deployment of grid-scale battery storage systems that stabilize and secure our power infrastructure. Our HybridOS™ platform is transforming how energy assets are controlled, optimized, and maintained. Now, we’re building the next generation of intelligence into our platform—and we need your help to lead the charge.

As AI Engineering Lead, you’ll drive the architecture, development, and deployment of our applied LLM and data platform capabilities. This is a hands-on technical leadership role that combines deep machine learning expertise with strategic execution. You’ll work directly on production workflows that incorporate transformers, RAG pipelines, and fine-tuned models, while coordinating a small but high-impact engineering team to deliver scalable solutions. You’ll collaborate across product, platform, and engineering teams to embed AI into real-time industrial workflows that power the grid. This role is ideal for someone who thrives in a fast-moving, mission-driven environment and is excited to see their work make an impact at scale.

Major Job Responsibilities:

• Design and build production-grade AI systems that power intelligent features within our HybridOS™ platform
• Lead development of workflows involving transformers, RAG, prompt tuning, and model inference pipelines
• Establish robust CI/CD pipelines for model training, evaluation, and deployment
• Coordinate with product managers and domain experts to prioritize use cases and define execution plans
• Collaborate with data engineering and cloud platform teams to scale infrastructure and ensure reliability
• Mentor internal contributors and guide team development through code reviews, pairing, and technical design sessions
• Champion high standards in engineering, experimentation, and responsible AI practices

Position Requirements:

• 5+ years of experience in machine learning or applied AI roles, including 2+ years leading technical teams or initiatives
• Demonstrated success deploying LLM or transformer models into production environments
• Strong software engineering fundamentals and ability to write maintainable, high-quality code
• Clear track record of owning deliverables and managing roadmap/backlog for AI/ML initiatives
• Experience mentoring other engineers or scientists and promoting engineering best practices
• Excellent communication and collaboration skills across technical and non-technical stakeholders
• Degree in Computer Science, Engineering, Machine Learning, or related field (or equivalent experience)
• Technologies You Should Know
• • Python and frameworks like PyTorch or TensorFlow
  • Transformer-based models (e.g. BERT, GPT, LLaMA)
  • Retrieval-Augmented Generation (RAG) pipelines
  • Prompt engineering and fine-tuning methods
  • ML infrastructure tools: MLflow, Kubeflow, Weights & Biases
  • API development and integration workflows
  • CI/CD practices for ML systems
  • Cloud platforms (AWS, GCP, or Azure)
  • Bonus: experience with time-series or energy/grid-related data

FlexGen provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, FlexGen complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training. 

FlexGen expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. 

To the extent permitted by law, employees are subject to periodic random drug testing, and post-accident and reasonable suspicion drug and alcohol testing.