What The Role Is

We are seeking a talented Senior Data Engineer to design, build, and maintain our data infrastructure supporting mission-critical energy operations. You'll work at the intersection of renewable energy and data, developing pipelines that process everything from real-time asset performance data to complex trading and risk analytics. This hybrid role offers the opportunity to make a direct impact on clean energy operations while working with a cutting-edge data stack including Snowflake, Dagster, dbt, Modal, and GitLab.

What You'll Be Doing

Analytics Infrastructure & Data Warehouse Management

• Design, deploy, and maintain scalable data infrastructure to support enterprise analytics and reporting needs
• Manage Snowflake instances, including performance tuning, security configuration, and capacity planning for growing data volumes
• Optimize query performance and resource utilization to control costs and improve processing speed

Data Pipeline Development & Orchestration

• Build and orchestrate complex ETL/ELT workflows using Dagster to ensure reliable, automated data processing for asset management and energy trading
• Develop robust data pipelines that handle high-volume, time-sensitive energy market data and asset generation and performance metrics
• Implement workflow automation and dependency management for critical business operations

Data Transformation & Analytics Support

• Develop and maintain dbt models to transform raw data into business-ready analytical datasets and dimensional models
• Create efficient SQL-based transformations for complex energy market calculations and asset performance metrics
• Support advanced analytics initiatives through proper data preparation and feature engineering

Data Quality & Governance

• Implement comprehensive data validation, testing, and monitoring frameworks to ensure accuracy and consistency across all energy and financial data assets
• Establish data lineage tracking and privacy controls to meet regulatory compliance requirements in the energy sector
• Develop alerting and monitoring systems for data pipelines, including error handling, SLA monitoring, and incident response

CI/CD & DevOps

• Lead continuous integration and deployment initiatives for Dagster and dbt pipelines, and Streamlit/Gradio application deployments to Linux servers
• Implement automated testing and deployment automation for data pipelines and analytics applications
• Manage version control and infrastructure as code practices

Cross-functional Collaboration

• Partner with Analytics Engineers, Data Scientists, and business stakeholders to understand requirements and deliver solutions
• Work closely with asset management and trading groups to ensure real-time data availability for market operations and risk calculations
• Collaborate with credit risk teams to develop data models supporting financial analysis and regulatory reporting
• Translate business requirements into technical solutions and communicate data insights to stakeholders

Documentation & Security

• Create and maintain technical documentation, data dictionaries, and onboarding materials for data assets
• Implement role-based access controls, data encryption, and security best practices across the data stack
• Monitor and optimize cloud infrastructure costs, implement resource allocation strategies, and provide cost forecasting

What You'll Bring

• Experience: 4+ years of hands-on data engineering experience in production environments
• Education: Bachelor's degree in Computer Science, Engineering, or a related field
• Data Orchestration: Proficiency in Dagster for pipeline scheduling, dependency management, and workflow automation; Airflow experience a plus
• Cloud Data Warehousing: Advanced-level Snowflake administration, including virtual warehouses, clustering, security, and cost optimization
• Data Transformation: Proficiency in dbt for data modeling, testing, documentation, and version control of analytical transformations
• Programming: Strong Python and SQL skills for data processing and automation
• CI/CD: 3+ years of experience with continuous integration and continuous deployment practices and tools; proficiency in GitLab CI/CD required (GitHub Actions experience a plus)
• Database Technologies: Advanced SQL skills, database design principles, and experience with multiple database platforms
• Cloud Platforms: Proficiency in AWS/Azure/GCP data services, storage solutions (S3, Azure Blob, GCS), and infrastructure as code
• Data Integration: Experience with APIs, various data connectors, and formats
• Data Security: Understanding of data security best practices, access controls, encryption, and role-based access management
• AI & LLM Proficiency: Practical experience integrating and leveraging large language models (e.g., OpenAI, Anthropic, or open-source models) within data workflows; ability to apply LLMs efficiently and securely, with awareness of data privacy boundaries, prompt injection risks, and responsible AI usage in production environments
• Problem-Solving: Strong analytical and troubleshooting skills with attention to detail
• Communication: Ability to work effectively with both technical and business stakeholders
• Work Style: Comfortable with a hybrid work environment (2-3 days in office); highly autonomous and self-directed with a strong work ethic and growth mindset; exceptional attention to detail; able to take ownership of projects end-to-end with minimal oversight

What Would Be Nice

• Experience in the energy, utilities, or financial services industries
• Knowledge of energy trading concepts, market data, or asset management
• Familiarity with data governance frameworks and regulatory compliance (SOX, GDPR, CCPA)
• Experience with infrastructure as code (Terraform, CloudFormation)

Clearway will not sponsor non-immigrant visas for this position (H-1B, TN, E-3, etc.).

#LI-Hybrid

Sr SWE -AI

Senior Software Engineer, AI Platform (Corporate AI Team)

Team & Role Overview

Axon’s Corporate AI Team sits within the Enterprise Data organization and focuses on internal-facing AI solutions that help Axon employees do more high‑value work with less manual effort. The team builds and operates Cortex, Axon’s internal AI platform that provides GPT‑class models, chat assistants, and secure integrations with systems like Quip, Jira, Slack, Microsoft 365, Snowflake, and more.
We’re looking for a Senior Software Engineer, AI Platform to help design, build, and scale this platform. In this role, you’ll:

• Own core services and integrations that power AI experiences for thousands of Axon employees.
• Collaborate with Corporate AI, Data Engineering, and business teams to turn real workflows into secure, reliable AI‑powered tools.
• Help define best practices and patterns for building production‑grade LLM and agentic workloads at Axon.

This is a hands‑on senior IC role—you’ll spend most of your time designing, coding, and operating production systems, not managing people.

What You’ll Do

Build and Evolve the AI Platform

• Design, build, and operate services that power Axon’s internal AI platform (Cortex), including chat experiences, agents, and integrations with enterprise systems.
• Implement and standardize patterns for deploying AI‑driven applications (APIs, web services, workflows, agents) across Axon’s cloud environments.
• Own and extend connectors and MCP integrations (e.g., Jira, Quip, Slack, M365, Snowflake) that allow LLMs to safely read and write data in Axon systems.
• Measure and improve reliability, latency, and cost for AI workloads, using telemetry and feedback from real users.

Deployment, Integration, and Reliability

• Drive the end‑to‑end lifecycle of new AI features—from prototype to hardened production service (design, implementation, testing, rollout, and operations).
• Evaluate new AI services (e.g., OpenAI, AWS Bedrock, Azure ML) for fit, performance, and cost; recommend and implement the right options for each use case.
• Implement monitoring, alerting, and auditing for AI services, ensuring we can trace usage, detect anomalies, and keep systems healthy in production.

Enablement, Best Practices, and Architecture

• Help define and document best practices for GPT/LLM solution development, including prompt engineering, RAG patterns, agentic workflows, and safe tool use.
• Partner with Corporate AI and Enterprise Architects to shape reference architectures for AI‑enabled apps and workflows (scalability, resiliency, observability, data access).
• Contribute to internal starter kits, training content, and templates that help other engineers and analysts build on the platform effectively.

Security, Governance, and Responsible AI

• Implement and maintain secure patterns for API key management, secrets, and access to models and data sources, aligned with Axon’s security and compliance standards.
• Work with Data, Security, and Governance partners to operationalize responsible AI guardrails—e.g., model selection, data minimization, logging, and usage controls.
• Ensure that new capabilities respect permissions, auditing, and policy requirements across systems like Jira, Quip, Slack, M365, and Snowflake.

Collaboration and Communication

• Collaborate closely with Data Engineering, Solution Architecture, and business teams (Finance, Sales, Operations, etc.) to turn real workflows into repeatable AI solutions.
• Clearly communicate design decisions, trade‑offs, and status to technical and non‑technical stakeholders.
• Participate in brainstorming and discovery sessions to identify “big dumb problems worth solving” with AI and automation.

What You Bring

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 4+ years of professional software engineering experience, including building and operating production services or platforms.
• Strong proficiency in at least one of: Python, TypeScript/JavaScript, or Java.
• Experience with at least one major cloud provider (AWS, Azure, or GCP) and comfort working with cloud‑native services (functions, containers, managed databases, queues, storage).
• Solid understanding of web service fundamentals (APIs, authentication/authorization, observability, CI/CD) and how to build reliable, maintainable systems.
• Demonstrated interest in AI/ML and LLMs—for example, integrating with OpenAI, Bedrock, or similar APIs; building GPT‑style apps; or using AI‑assisted development tools.
• Basic understanding of security best practices (secrets management, least‑privilege access, audit logging) and eagerness to deepen this in the context of AI platforms.
• Strong communication and collaboration skills, with comfort working in a fast‑moving, experimental environment.

Preferred Experience

You don’t need all of these, but experience in several of the following will help you ramp quickly:

• Hands‑on work with LLM platforms and tools, such as OpenAI (ChatGPT / APIs), AWS Bedrock, Azure OpenAI, or Azure ML Studio.
• Experience integrating with enterprise systems like Jira, Confluence/Quip, Slack, M365, Salesforce, or Snowflake—especially via APIs or connectors.
• Familiarity with RAG (Retrieval‑Augmented Generation), semantic search, or vector stores in production contexts.
• Exposure to DevOps / platform engineering: Terraform or similar IaC, GitHub Actions or other CI/CD systems, containerization (Docker, Kubernetes), and application monitoring stacks.
• Experience building internal platforms or self‑service tools used by multiple teams.
• Participation in enablement activities (internal trainings, office hours, documentation, or community programs like Axon’s Champions Circle) is a plus.