AI-Driven Lead Engineer (Logistics & Transportation)

Company Overview

At Bridgenext, we engineer Growth Operating Systems. Most enterprises have spent millions on their revenue stack and still aren't seeing the growth they expected.They have tools that function, but no system that wins. We help growth-hungry companies close that gap by turning fragmented platforms, siloed teams, and disconnected data into one integrated Growth OS. More than a technology company or marketing agency, we're a global digital consultancy with experts in engineering, data, AI, creative and more.

Our teams are made up of experts who believe in engineering impact, starting with putting people at the center of everything we do. Every team member directly shapes our work, culture, and values. Nothing matters more to us than a kind, respectful, fulfilling environment that supports everyone. Our flexible, inclusive culture gives you the autonomy, resources, and opportunities to thrive.

Position Description

We're looking for an experienced technical lead with an AI-driven mindset, who already knows how to get more out of a team by working alongside AI agents.

The team combines developers and QA engineers with AI agents covering product, business, development and QA work, all building production systems for one of North America's largest transportation companies. Deciding what each of them works on, giving them the right context and reviewing their output sits at the center of the job.

Much of the work happens close to the business. Workshops with product owners and stakeholders are where assumptions get challenged, scope gets negotiated and goals become clear, buildable work. Delivery runs in short cycles: build something real, validate it with stakeholders, learn and adjust. Keeping architects, QA, product, and the DevOps and cloud teams aligned, and coaching the wider team in this way of working, completes the picture.

Responsibilities:

• Own delivery. Take full responsibility for what the team ships, including quality, timelines and production stability.
• Lead people. Manage a team of dev and QA engineers, covering priorities, growth and team health.
• Work with the business. Run discovery and requirements workshops with product owners and business stakeholders, negotiate scope, and turn the outcomes into clear specs. Product decisions stay with the client.
• Iterate in short cycles. Ship working increments quickly, validate them with product, business, QA and architecture, and feed what you learn into the next cycle.
• Align stakeholders. Keep architects, QA, product, and the DevOps and cloud teams on the same page, and explain trade-offs in terms each audience understands.
• Run AI agents. Coordinate agents across product, business, dev and QA work: break down tasks, run them in parallel, verify the output.
• Own the architecture. Design and evolve .NET microservices on Azure, built around events on Confluent Kafka.
• Curate the agents' knowledge. Maintain the specs, ADRs, conventions and skills that make agents reliable, and keep them up to date.
• Hold the quality bar. Test-first development, automated pre-PR gates, and security and correctness review of all AI-generated output.
• Coach the team. Help engineers adopt AI-augmented ways of working, mainly by example.

Workplace: This is a remote position open to candidates based in LATAM willing to work Central Timezone hours

Must Have Skills:

• Leadership and communication
  • 10+ years in software engineering, including 3+ years as technical lead of a mixed team (dev, QA, DevOps) of at least 5 people.
  • Has delivered and supported production systems, APIs and UI products.
  • Track record of delivering in short build-and-validate cycles, getting regular feedback from stakeholders and adjusting direction based on it.
  • Experience facilitating workshops with both technical and business audiences.
  • Comfortable working with architects, QA, product owners, business leaders, and DevOps and cloud teams.
  • Client-facing experience; English at C1/C2 level, spoken and written.
• Technical depth (demonstrable without AI)
  • .NET 10+ and C# at expert level.
  • Azure: Functions, Container Apps/AKS, Service Bus/Event Hubs, Managed Identity.
  • Event-driven microservices on Kafka, ideally Confluent (Schema Registry, delivery semantics, idempotency).
  • API design, CI/CD with GitHub Actions, and testing strategy.

Preferred Skills:

• Okta / OIDC / OAuth2
• Cosmos DB, Redis, OpenTelemetry
• Trucking, freight, telematics/IoT or fleet domain experience
• GitHub Copilot agent mode, Claude Code, MCP or RAG

Professional Skills:

• Strong English written and verbal communication
• Excellent problem-solving skills and comfort operating in a fast-paced, iterative environment
• Strong organizational and time management skills
• Strong team and individual player
• Maintains composure during all types of situations and is collaborative by nature
• High standards of professionalism, consistently producing high quality results

How we work with AI

This is how we build, and we'll help you go deep on it. Hands-on experience with any of the following is a strong plus; the rest you'll pick up with us.

• Running agents on real work. Coordinating several AI agents at once on delivery work, not just using a chat assistant.
• Giving agents the right context. Writing rules files, skills and specs that noticeably improve what agents produce.
• Building the harness, not just the prompt. Setting up tools and guardrails (analyzers, architecture tests, type and contract checks, hooks, pre-commit gates, MCP tools) that keep agents on track and make their output accurate by design.
• Proving the output is right. Where correctness isn't obvious, such as a front-end, creating ways for agents to check their own work: Playwright E2E flows, visual regression baselines, screenshot diffs, contract tests and golden datasets. "Done" means proven, not assumed.

Bridgenext is an Equal Opportunity Employer