Technical Delivery Lead

• Provide hands-on technical leadership across AI/ML, automation, and integration delivery workstreams
• Review and approve system architecture, technical designs, and solution proposals before release
• Ensure engineering output meets enterprise-grade standards for performance, scalability, security, and maintainability;
• Establish and enforce coding standards, design patterns, and technical best practices across the team
• Conduct architecture reviews and technical risk assessments for all active delivery streams;

• Own the QA strategy across all delivery workstreams, including automated testing frameworks, code review gates, and acceptance criteria
• Define and monitor engineering KPIs: code coverage, defect escape rate, deployment frequency, mean time to recovery (MTTR), and change failure rate
• Champion shift-left testing practices, including AI model validation, integration testing, and performance benchmarking
• Lead post-incident reviews (PIRs) and blameless retrospectives to drive continuous improvement
• Ensure compliance with industry standards (SOC 2, ISO 27001, GDPR) and applicable regulatory requirements

• Drive technical delivery across multiple concurrent projects using Agile/Scrum methodologies
• Partner with the Scrum Master, engineering leads, and the engagement owner to define sprint goals, manage dependencies, and remove blockers
• Own technical risk registers, mitigation plans, and escalation pathways - surfacing risks early to the engagement owner
• Manage cross-functional coordination between AI/ML engineers, data engineers, DevOps, automation engineers, and QA
• Prepare technical status reports, roadmaps, and delivery milestones for internal consumption and engagement owner review
• Translate high-level solution requirements from the engagement owner into actionable technical work for the engineering team

• Mentor and coach senior engineers, fostering a culture of technical excellence and continuous learning
• Lead hiring efforts including technical interview design, candidate evaluation, and onboarding
• Drive adoption of emerging technologies, frameworks, and AI/ML best practices across the team
• Facilitate knowledge sharing through tech talks, brown bags, architecture decision records (ADRs), and internal documentation

• 8+ years of progressive experience in software engineering, with at least 3+ years in a technical delivery lead, engineering manager, or technical program manager role
• Proven track record of delivering complex, multi-workstream AI/ML or enterprise software projects end-to-end
• Deep understanding of modern AI/ML stack: LLMs (GPT-4o, Claude, Llama), RAG architectures, vector databases, agentic AI frameworks (LangChain, LangGraph, CrewAI, AutoGen)
• Strong hands-on background in at least two of: Python, TypeScript/JavaScript, Go, or Java
• Experience with cloud platforms (AWS, Azure, GCP) and infrastructure-as-code (Terraform, Pulumi)
• Demonstrated expertise in QA strategy: automated testing (Pytest, Playwright, Selenium), CI/CD pipelines, and observability (Datadog, Grafana, OpenTelemetry)
• Strong internal communication skills - able to clearly convey technical status, risks, and trade-offs to the engagement owner and engineering peers
• Strong understanding of Agile/Scrum delivery, including sprint planning, backlog refinement, and velocity management
• Experience with compliance frameworks: SOC 2, ISO 27001, GDPR, HIPAA, or financial services regulations
• Fluent English, both written and spoken.
• Proven experience in international projects, including collaboration with global and multicultural teams.
• Strong communication, stakeholder management, and problem-solving skills.

• Experience in insurance, financial services, or other highly regulated industries
• Familiarity with MLOps practices: model versioning, A/B testing, drift detection, and automated retraining pipelines
• Certifications: PMP, SAFe, AWS Solutions Architect, Azure Solutions Architect, or equivalent
• Experience managing hybrid onshore/offshore delivery teams
• Track record of building and scaling AI Centers of Excellence or innovation teams
• Familiarity with AI governance frameworks, responsible AI practices, and EU AI Act compliance
• Experience with platform engineering concepts: developer portals, internal developer platforms (IDPs), and self-service infrastructure

• All team members must demonstrate hands-on experience with CI/CD pipelines, containerization (Docker/Kubernetes), cloud platforms, and deployment automation.

• Proficiency with at least one IaC toolchain (Terraform, Pulumi, CloudFormation/Bicep) is required across all roles - not just DevOps.

• Working knowledge of at least one major cloud provider (AWS, Azure, or GCP).

• Git-based workflows, code review practices, and collaborative development are expected of every team member.

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field is preferred.

• Brazil based role with a 100% remote working model.
• Close collaboration with international stakeholders and teams across regions.
• Schedule flexibility may occasionally be required for critical milestones

• PJ

• 100% remota

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