Lead Software Engineer
Confirmed on the employer's own hiring board on Oct 4, 2026. First seen by Alion on Oct 1, 2026.
Description
Lead Software Engineer
Why YOU want this position
At Enverus, we’re committed to empowering the global quality of life by helping our customers make energy affordable and accessible to the world.
We are the most trusted energy-dedicated SaaS company, with a platform built to maximize value from generative AI, and our innovative solutions are reshaping the way energy is consumed and managed. By offering anytime, anywhere access to analytics and insights, we’re helping our customers make better decisions that help provide communities around the world with clean, affordable energy.
The energy industry is changing fast. But we’ve continued to lead the way in energy technology, creating intelligent connections across the entire energy ecosystem, from renewables, power and utilities, to oil and gas and financial institutions. Our solutions create more efficient production and distribution, capital allocation, renewable energy development, investment and sourcing, and help reduce costs by automating crucial business operations. Of course, this wouldn’t be possible without our people, which is why we have built a team of individuals from a diverse range of backgrounds.
Are you ready to help power the global quality of life? Join Enverus, and be a part of creating a brighter, more sustainable tomorrow.
We are looking for a Lead Software Engineer to join our team in Brno.
The Team:
As part of the Marginal Unit Team, you will be a key contributor to the fastest growing product line at Enverus. We pair complex algorithms and machine learning with powerful computational infrastructure and an intuitive UI that is unmatched in the industry. Small, fast paced, and highly collaborative, this team values engineers who enjoy tackling difficult technical and domain problems while continuously learning from one another.
Engineers on this team own systems end-to-end, including architecture, implementation, observability, reliability, and operational support.
Performance Objectives
Lead the design and development of our AI-powered analyst agent, including LLM integration, skill-based tool architecture, and agentic reasoning pipelines
Drive architectural decisions for backend services built in Python, including async task execution, API design, and structured output modeling
Take technical ownership of existing systems and services, redesigning them as necessary to reduce complexity or leverage new technologies
Define engineering standards and patterns across the team and mentor engineers at multiple levels
Partner with product and domain experts to translate power market problems into scalable, maintainable software
Integrate and evolve our use of frontier AI models (Claude via AWS Bedrock) as capabilities and APIs continue to advance
Challenges You'll Face:
Highly complex domain (the power grid itself, and the markets that sit on top of it)
Building reliable, observable agentic systems where LLM behavior is inherently non-deterministic
Continuously evolving AI capabilities requiring ongoing architectural adaptation
Stability and observability of a distributed system involving dozens of semi-independent services
Maintaining performance while working with complex computations on large-scale real-time data
Competitive Candidate Profile
BS in Computer Science, or equivalent experience
8+ years of software engineering experience with significant Python backend development
Demonstrated experience leading technical direction on a team or system, not just delivering within one
Experience designing and operating AI-powered or agent-based systems (LLM integration, tool use, structured outputs)
Significant experience working with data-rich applications and pipelines
Proven success in delivering highly reliable and scalable software systems
Experience with task queuing systems (Dramatiq, Celery, or similar) and async distributed workflows
Experience using SQL, and NoSQL databases
Familiarity with Kubernetes on GCP or AWS
Experience learning and working in a highly complex domain (financial trading or power systems is a plus)