Engineering Manager

Description

The company has spent decades helping businesses in energy, agriculture and weather-driven industries make faster, more precise decisions under uncertainty. Its operational decisioning platform turns raw data into insights that customers use to manage supply chains, keep markets stable and protect infrastructure.

The company is growing, expanding internationally and adding AI-powered products. This role leads the engineers who build the foundation of the internal platform. That platform wraps cloud infrastructure in higher-level capabilities so engineers, solutions teams and customers can build data products, applications and AI tools without managing the cloud layer themselves.

The platform team builds the shared layer other teams depend on: APIs, SDKs, CLIs, developer tooling and managed services. Much of the work is greenfield, so you will help shape the architecture, engineering practices and long-term direction of a critical platform.

This is a hands-on role that combines people management, technical direction, delivery and operational ownership. You will write and review code alongside your team when needed, work closely with Architecture, Product and platform consumers, and set the quality and operational standards needed for secure, reliable, reusable services at scale.

Responsibilities

• Lead and manage platform engineers at several experience levels, including hiring, onboarding, performance reviews, career development and day-to-day delivery.
• Coach and mentor engineers, and build a collaborative culture where people take ownership.
• Set and enforce standards for code quality, technical execution, operational discipline and continuous improvement.
• Engage in architecture discussions, review designs critically, and help engineers work through hard technical trade-offs.
• Own the platform's technical direction together with senior engineers and architecture stakeholders.
• Guide the design and build of distributed, multi-account cloud systems on AWS.
• Oversee APIs, SDKs, CLIs, tooling and managed services that other engineering teams build on.
• Lead distributed-systems work covering secure cross-account communication, multi-tenant isolation, provisioning and lifecycle automation.
• Create abstractions that let engineers and solutions teams use purpose-built capabilities instead of raw cloud resources.
• Guide architecture decisions for new and existing capabilities, including large greenfield builds.
• Make sure the architecture supports scale, security, maintainability and reuse across products and teams.
• Build a shared platform that internal teams want to use and help improve.
• Grow reusable capabilities out of real engineering and customer needs.
• Create practices and incentives that encourage teams to use, improve and contribute to shared components.
• Make reuse the default by building tools that raise developer productivity and cut duplicate work.
• Work with Product on visible milestones, including a developer portal, technical documentation and first productized capabilities.
• Fold feedback from internal and external platform users into technical priorities and the roadmap.
• Own the platform's operational commitments for security, isolation, reliability and observability.
• Establish strong cloud identity and access management, isolation boundaries and security controls.
• Guide signed, authenticated service-to-service communication, least-privilege access and secure multi-account designs.
• Make end-to-end observability, monitoring and operational visibility core platform capabilities.
• Own on-call health, incident response and service-level objectives.
• Promote automated testing, infrastructure as code, trunk-based development and incremental, reversible releases.
• Balance availability, security and operational needs against the pace of delivering new capabilities.
• Work with Architecture, Identity, Product and Solutions/Field Engineering so the platform meets the needs of teams building on it.
• Turn strategy into concrete engineering roadmaps and measurable delivery milestones.
• Report on technical direction, progress, dependencies and risks to engineering leadership and other stakeholders.
• Weigh speed to value against building durable, scalable, reusable foundations.
• Coordinate across teams to resolve dependencies, align architecture and keep delivery on track.
• Work with Product and other stakeholders to make sure platform investment delivers business and developer value.
• Champion AI-assisted development, including coding assistants and agentic tools, to improve productivity and team velocity.
• Guide the design and integration of AI-augmented capabilities into the platform's modular architecture.
• Support platform features that use large language models, AI agents and related services.
• Assess new AI development technologies and decide how they can improve engineering workflows and widen what platform consumers can do.

Requirements

• At least 8 years of software engineering experience, including at least 2 years at Staff (T3) to Principal (T5) level and at least 2 years as a technical lead or engineering manager.
• Experience shipping, operating and supporting production software.
• A track record of hiring, coaching and developing engineers at different levels.
• Experience building a healthy culture based on accountability, collaboration, technical excellence and continuous improvement.
• Ability to lead technically while managing delivery, people development and operational duties.
• Strong grounding in AWS cloud-native architecture and distributed systems.
• Ability to work through system design with engineers, review designs critically and weigh architecture trade-offs.
• Experience with platform engineering, developer tooling, SDKs, infrastructure or similar teams that build foundations for other engineers rather than only end-user features.
• Solid understanding of secure multi-account and multi-tenant cloud architectures.
• Fluency in cloud identity and access management, tenant isolation boundaries and the security needs of distributed cloud systems.
• Understanding of the architecture and operations needed for scalable, secure, reliable shared platform services.
• Familiarity with modern AI development tools and AI-assisted workflows, including coding assistants and agentic tools.
• Understanding of how LLMs, agents and related services fit into modular platform components.
• Ability to coach engineers to adopt AI-assisted practices that raise productivity without lowering quality.
• Strong communication and stakeholder management across Engineering, Product, Architecture and Go-to-Market teams.
• Ability to explain technical decisions, trade-offs, progress and risks to technical and non-technical audiences.
• Proven ability to influence technical direction and coordinate delivery across teams with competing priorities.

Conditions

Base pay target: $110,000 to $145,000.

Pay is tied to performance, with room to grow over time.

Actual pay depends on factors including prior experience, education, transferable skills, business needs, internal equity and applicable laws. The range may change.

The role may also be eligible for variable pay and benefits.

Remote work is available, depending on the position.

The company is an equal opportunity employer and welcomes applicants of all backgrounds.

Benefits

• Competitive salary.
• Unlimited paid time off.
• Flexible working hours.
• Medical, dental and vision insurance.
• 401(k) with a 6% company match.
• Unlimited access to more than 13,000 courses on a learning platform.
• Employee assistance program.