Lead Engineer, Digital Front Door AI

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com.

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:

Technology Product & Platform Management

Job Sub Function:

Technical Product Management

Job Category:

Scientific/Technology

All Job Posting Locations:

São José dos Campos, São Paulo, Brazil

Job Description:

The Lead Engineer, Digital Front Door AI will serve as the technical engineering leader for AI capabilities delivered through the Digital Front Door, owning key engineering and architectural decisions and helping shape the technical vision and roadmap. This role combines hands-on AI/software engineering with technical leadership, partnering with Product Management, architects, engineers, enterprise platforms, and HR stakeholders to translate business needs into scalable, secure, reusable AI solutions.

Consistent with the Product Lead Engineer role, this position is expected to solve complex engineering challenges while ensuring implementation aligns with architecture direction, technology roadmaps, engineering standards, and business needs

 

Key Responsibilities

AI Engineering, Architecture & Delivery

• Own the technical engineering direction, and key technology decisions for Digital Front Door AI capabilities.
• Lead the design, development, integration, deployment, and scaling of enterprise AI applications, agents, copilots, and automation supporting HR and employee experiences.
• Maintain a strong hands-on engineering presence, developing and reviewing code, prototypes, integrations, technical enablers, and solution designs.
• Establish reusable and modular engineering patterns that enable AI capabilities to scale across use cases ensuring quality, maintainability, and speed of delivery.
• Drive technical solution evaluation and selection, balancing business requirements, architecture standards, scalability, security, cost, performance, and long-term strategic fit.
• Establish and promote leading engineering practices across development, testing, CI/CD, observability, performance, reliability, and operational support.

 

Product Partnership & Technical Leadership

• Partner closely with Product Management and HR stakeholders to translate the Digital Front Door vision and business priorities into technical capabilities
• Guide technical discovery, solution design, experimentation, backlog priorities, architectural decisions, and engineering trade-offs.
• Partner with architects, enterprise platform teams, Product Owners, Lead Engineers, and other engineering teams to ensure alignment across products and platforms.
• Help prioritize technical backlogs, address technical debt, and balance near-term product needs with long-term architecture and engineering objectives.
• Identify and manage technical risks, impediments, and cross-product or cross-platform dependencies.
• Evaluate emerging AI technologies and conduct rapid experiments or technical spikes to determine their applicability to Digital Front Door use cases.

 

Technology Lifecycle, Governance & Responsible AI

• Own technical lifecycle considerations for Digital Front Door AI capabilities, including architecture evolution, integrations, APIs, technical debt, performance, and sustainability.
• Ensure AI solutions meet applicable enterprise architecture, cybersecurity, privacy, quality, compliance, and Responsible AI requirements.
• Build appropriate evaluation, testing, monitoring, observability, and quality controls into AI solutions throughout their lifecycle.
• Partner with relevant architecture, security, privacy, compliance, enterprise platform, and vendor teams to resolve technical requirements and risks.

 

Skills

• Experience in software engineering, AI engineering, solution architecture, and enterprise digital product delivery.
• Demonstrated experience designing and delivering enterprise AI applications, AI agents, copilots, intelligent automation, or related AI-enabled solutions.
• Strong hands-on software engineering capability and the ability to actively engage with engineers on architecture, design, code, and technical trade-offs.
• Deep knowledge of modern AI engineering concepts, including large language models (LLMs), agentic AI, orchestration, prompt engineering, retrieval-augmented generation (RAG), APIs, integrations, evaluation, and monitoring.
• Experience designing scalable integrations and services using APIs, cloud-native technologies, data platforms, and modern software engineering practices.
• Experience translating complex or evolving business requirements into scalable architecture, engineering strategy, and technical roadmaps.
• Strong understanding of SDLC practices, including CI/CD, automated testing, security, observability, and deployment practices.
• Experience working within Agile product development environments and managing technical priorities and dependencies across teams.
• Passion for applying AI to simplify HR services and create intuitive, scalable employee experiences.

 

 

Required Skills:

 

 

Preferred Skills:

Agile Product Development, AI Judgement Integration, Analytical Reasoning, Coaching, Collaboration, Competitive Landscape, Critical Thinking, Customer Alignment, Demand Forecasting, Human-Computer Interaction (HCI), Organizing, Product Development, Product Improvements, Product Strategies, Requirements Analysis, Research and Development, Software Development Life Cycle (SDLC), Software Development Management, Stakeholder Management, Technical Credibility, Technical Writing, Technologically Savvy