About Tyba

Tyba is a modeling platform for energy companies developing, financing, and operating renewable energy infrastructure. Energy companies rely on technical models daily to make crucial infrastructure decisions.

Our mission is to make cutting-edge models accessible to cross-functional teams so that companies can build and operate more renewable energy more profitably. We are backed by leading climate and generalist VCs and work with many of the industry’s most innovative energy companies.

The Role

We're looking for a software engineer to join our Asset Operations Backend team and help power the clean energy transition. In this role, you'll work at the intersection of data science enablement and robust backend systems—operationalizing cutting-edge optimization and forecasting models while building the scalable infrastructure behind our growing portfolio of battery storage assets.

Our auto-bidding platform synthesizes price forecasts and bid optimization algorithms to deliver market-beating returns for our customers. You'll lead key initiatives that ship high-value features, working closely with cross-functional teams and going deep on the intricacies of power markets and their associated systems. This is a high-impact role at a startup where your work directly accelerates the energy transition.

You'll split your time between supporting our data science and optimization teams (who work with specialized Python libraries like cvxpy and neuralforecast) and building robust backend services and system architecture. You'll help shape how we evolve from our current architecture toward a more modular microservices approach across Python, Clojure, and Kotlin.

Tyba’s Product

Tyba has two main products—Operations and Project Simulation:

• Operations: Auto-bidding platform, powered by a proprietary neural network, that recommends and executes operating strategies based on industry-leading price forecasts and optimization methodology. Our platform delivers revenue outcomes in the top 5% of ERCOT assets.

• Project Simulation: Configurable simulation platform where developers can model realistic financial and physical outcomes based on location, market dynamics, and battery specifications.

As a software engineer on the Asset Operations Backend team, you'll primarily work on new features and initiatives for the Operations product backend. There are plenty of opportunities for collaboration on other portions of the product, including optimization and market orchestration.

Responsibilities

• Lead feature initiatives end-to-end: Scope, develop, test, release, and monitor new features—primarily backend, with collaboration across the frontend team

• Partner with data science and optimization teams to operationalize ML models and optimization algorithms into production systems

• Design, build, and maintain backend services that power real-time battery dispatch, bidding, and energy market operations

• Performance engineering: Identify, profile, and address computational bottlenecks in a live bidding system that must communicate with market systems on strict timelines

• Build and improve data pipelines and ETL processes using dbt and Python

• Develop integrations with market entities (QSEs in ERCOT, Scheduling Coordinators in CAISO) and site telemetry systems

• Contribute to infrastructure-as-code using Terraform/OpenTofu and manage AWS services (EKS, RDS, Redshift, S3, Kinesis)

• Evolve our CI/CD practices, building on our existing CircleCI foundation

• Enhance and steward system reliability: Conduct system migrations with minimal downtime, debug and fix production issues, and participate in an on-call rotation

• Break apart monolithic services into well-designed microservices

• Contribute across our polyglot stack (Python, Clojure, Kotlin)

Required Skills

• 8+ years of professional software engineering experience

• Strong proficiency in Python, including experience with data processing libraries (pandas, polars, NumPy) and production deployments

• Experience with SQL and relational databases (PostgreSQL), including data warehouses and database performance optimization

• Experience with cloud infrastructure, preferably AWS (EKS, RDS, S3)

• Familiarity with containerization (Docker) and Kubernetes

• Experience with infrastructure-as-code (Terraform/OpenTofu/Crossplane/Cloudformation or similar)

• Strong understanding of distributed systems and microservices architecture

• Experience with CI/CD pipelines

• Ability to work cross-functionally, synthesizing requests from non-technical team members and external parties into well-designed engineering solutions

• Comfortable working in a fast-paced startup environment with evolving requirements

• Basic proficiency with agentic coding tools (e.g., Cursor, Copilot, Claude Code, Warp Agent Mode): You should be able to leverage AI-assisted development to accelerate your workflow while maintaining a high bar for code quality. This means having the judgment to review machine-generated code critically, understanding where AI tools excel and where they can go astray, and knowing when to trust automation vs. when to write code yourself.

Preferred Skills

• Experience with JVM languages, particularly Kotlin

• Experience with Clojure or other Lisp-family languages

• Familiarity with data engineering tools (dbt, Snowflake, Redshift)

• Experience with time-series data and real-time systems

• Background supporting ML/data science teams in production environments

• Familiarity with optimization libraries (cvxpy) or forecasting frameworks (neuralforecast, PyTorch)

• Experience with GraphQL (Strawberry, Fulcro)

• Knowledge of energy markets (ERCOT, CAISO) or renewable energy systems

• Thought leadership in AI-assisted development: You've developed workflows, best practices, or tooling around agentic coding—perhaps contributing to prompt engineering, evaluating new tools, or helping teams adopt AI effectively while avoiding common pitfalls

• Passion for clean energy and the energy transition

Tyba’s Technical Stack

Tyba's machine learning stack is developed in Python and runs on AWS. We rely on PyTorch for building our neural network architectures. Our backend services span Python, Clojure, and Kotlin, with a data layer built on PostgreSQL and Redshift.

Compensation and benefits

• Salary: $180k-$230k

  This salary range is based on Bay Area market rates and is intended primarily for roles based in the San Francisco Bay Area. Compensation for candidates in other locations may vary based on local market data, role scope, and experience.

• Benefits: Parental leave, medical benefits, unlimited PTO

• Equity Options: Opportunity to own a stake in the company through an employee stock option plan.

• Flexible Work Environment: Hybrid work model, remote work options, and team offsites.

What is the interview process like?

Our interview process focuses on core competencies. We want to make sure that you are set up for success at a fast-growing and high-impact startup. We will first get to know each other through conversations about Tyba, your background, and what you are looking for in your next role. While the specifics vary, from there, we will focus on evaluating your skills and experience relevant to the role. Once we have determined whether or not you are a fit for the team, we will help you get to know the company better and speak with other team members to inform your decision. We prioritize transparency, clear communication, and ensuring that we do our best to find a mutual fit.