Senior Full Stack Software Engineer ( Strong backend - Python & Go + frontend)

As a Senior Software Engineer on the ChampionAI core platform team, you will independently drive solutions, resolve complex technical challenges, and take full ownership of core platform capabilities and agent architectures. You will serve as a technical subject matter expert — delivering enterprise-scale AI products at Champion Pace while mentoring junior engineers and helping Applied AI teams across business units build, deploy, and operate Champion agents correctly.

WHAT YOU'LL DO

• Independently design, build, and lead feature development across Champion platform repositories using trunk-based development and PR-gated merges.
• Optimize system architecture and developer experience: tooling, scaffolding, internal documentation, and onboarding paths for engineering teams.
• Architect, maintain, and evolve the MCP tool server and multi-agent infrastructure that business unit teams depend on for production deployments.
• Proactively debug and resolve complex technical issues, performance bottlenecks, and friction points across cloud-native and agentic platform architectures.
• Provide technical leadership, guidance, and mentorship to junior team members and Applied AI engineers across business units.
• Lead complex cross-team code and architectural reviews for agent implementations — focusing on prompt quality, scope enforcement, security/auth configuration, and deployment setup.
• Establish engineering standards and contribute to internal architectural guides and skills documentation.
• Partner with DevOps, Cloud, and BU engineers on Kubernetes manifest creation, database registration, and feature flag/prompt rollouts.
• Drive end-to-end design and implementation of Champion agents for high-impact business unit use cases.
• Engage in high-level cross-functional collaboration

MUST-HAVE QUALIFICATIONS

• 5+ years of software development experience in enterprise SaaS environments (3+ with a Master's), specialising in Python, Golang and cloud-native AI-driven systems.
• Solid understanding of Model Context Protocol (MCP), Agent-to-Agent (A2A) protocol, multi-agent architectures, prompt engineering, and evaluation design.
• Proficiency in Python (async, FastAPI, Pydantic, pytest, pytest-asyncio, DeepEval), Docker, PostgreSQL, and Git.
• Proven ability to independently lead feature development, architectural reviews, and cross-team technical decisions.
• Experience mentoring junior engineers and setting engineering standards in a team environment.

NICE-TO-HAVE

• Working knowledge of AWS (ECR, EKS, Bedrock), Kubernetes, and Terraform.
• Familiarity with LaunchDarkly and AI-native development tools (Cursor, Claude Code).
• M.S. / M.Tech in Computer Science, AI, or ML.
• Experience in manufacturing or industrial software domains.

PROFILE

You are a self-sufficient senior engineer who does not need day-to-day direction. You take ownership from design through deployment, proactively identify and resolve issues, and make the engineers around you better. You bring both technical depth and cross-functional maturity — comfortable driving architectural decisions and collaborating across teams.

KEY SKILLS

🐍 Async Python & FastAPI & Golang Pydantic · pytest · FastAPI · Docker · PostgreSQL

🤖 Agent Architecture & MCP Multi-agent · A2A · Orchestration · Tool Calling

🧪 Agentic Evaluation & Observability DeepEval · pytest-asyncio · Monitoring · Cloud-native

🧑‍💼 Technical Leadership Mentorship · Code Reviews · Engineering Standards · Delivery

EDUCATION

Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience). M.S. / M.Tech in Computer Science or AI/ML is a plus.

Your health and well being are important to us at QAD. We provide programs that help you strike a healthy work-life balance.

• Opportunity to join a growing business, launching into its next phase of expansion and transformation.
• Collaborative culture of smart and hard-working people who support one another to get the job done.
• An atmosphere of growth and opportunity, where idea-sharing is always prioritized over level or hierarchy.
• Compensation packages based on experience and desired skill set

About QAD:

QAD | Redzone is redefining manufacturing and supply chains through its intelligent, adaptive platform that connects people, processes, and data into a single System of Action. With three core pillars — Redzone (frontline empowerment), Adaptive Applications (the intelligent backbone), and Champion AI (Agentic AI for manufacturing) — QAD | Redzone helps manufacturers operate with Champion Pace, achieving measurable productivity, resilience, and growth in just 90 days.

QAD is committed to ensuring that every employee feels they work in an environment that values their contributions, respects their unique perspectives and provides opportunities for growth regardless of background. QAD’s DEI program is driving higher levels of diversity, equity and inclusion so that employees can bring their whole self to work.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.

QAD | Redzone is redefining manufacturing and supply chains through an intelligent, adaptive platform that connects people, processes, and technology into a single System of Action. Founded in 1979 and headquartered in Miami, Florida, the company serves manufacturers across more than 100 countries in industries including automotive, consumer products, food and beverage, high technology, industrial equipment, and life sciences.

The platform is built on three core pillars: Redzone (frontline empowerment), Adaptive ERP (the intelligent backbone of manufacturing operations), and ChampionAI (Agentic AI purpose-built for manufacturing). Together, these enable manufacturers to achieve measurable productivity, resilience, and growth — in as little as 90 days.