Senior Software Engineer, Agents

About the role

This role defines and delivers the backend systems that enable production-grade AI agent workflows. It partners across platform teams to build reliable infrastructure for orchestration, tool use, and state management. The role serves developers who need scalable, intuitive systems for deploying agentic applications.

Software engineers turn product ideas into working code. Engineers work in small teams, review each other's work, and ship in small batches. Most teams follow agile practices such as sprints and daily standups. Engineers also write tests, fix bugs, and improve performance. The field values clear communication as much as technical skill. Engineers spend part of every week on planning, code review, and debugging, not just writing new code. The ability to explain a technical decision in plain words separates strong engineers from the rest.

Key facts

Requirements

Extensive experience building scalable backend systems using Go, Python, Rust, or similar languages, demonstrating mastery of performance and concurrency patterns.

Strong understanding of distributed systems, asynchronous processing, APIs, and cloud-native application architecture, with evidence of operating such systems.

Experience designing and operating production services at scale, showing a track record of reliability, monitoring, and incident response.

Hands-on experience building backend platforms, developer tools, or infrastructure products, shipping features that users depend on.

Familiarity with cloud platforms such as AWS, GCP, or Azure and container technologies including Docker and Kubernetes, used in real deployments.

Proven ability to take ownership of large technical initiatives from architecture through production, driving projects across ambiguity to delivery.

Commitment to software quality, automated testing, observability, and continuous delivery, with practices that prevent regressions and improve velocity.

Strong communication skills and the ability to collaborate effectively across engineering, product, research, and design teams, aligning on shared outcomes.

Ability to thrive in fast-moving, ambiguous environments while balancing technical excellence with product impact, navigating tradeoffs with clarity.

Practical notes

Occasional team and company offsites may occur. Lightning AI does not provide visa sponsorship for this position. Typical interview steps

Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds. Candidates often solve a coding problem, discuss past projects, and answer system design questions. Some loops include a take-home task. Final rounds typically cover team fit and give candidates a chance to ask questions. Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer. Practicing a few problems aloud and reviewing your own past projects are the best preparation.

Good to know

The role operates in a cloud-native environment using containers and infrastructure-as-code practices.

Engineers work on developer-facing platforms that abstract complexity for researchers and enterprises.

Production reliability, scalability, and observability are central to the work in this role.

Collaboration spans multiple engineering teams that own different layers of the stack.

Questions to ask

Good questions to ask the employer in the interview: what does success look like in the first six months, how is the team structured, what is the current biggest challenge, and how are decisions made. Asking about growth paths and the review process is also well received. Employers expect questions, and good ones show preparation.

Career growth

Engineering careers usually progress from individual contributor to senior, staff, and principal levels. Some engineers move into management and lead teams of five to twenty people. Others stay on the technical track. Growth follows demonstrated impact, not tenure alone. A typical engineering ladder has clear levels with defined expectations for scope, quality, and mentorship. Moving up usually requires owning outcomes end to end rather than completing assigned tickets.