Technical Lead

Overview:

The Technical Lead is responsible for owning the technical execution and engineering delivery of complex application and AI-enabled solutions across the software development lifecycle. This role serves as the primary technical authority for the engineering team, translating architecture and business requirements into executable technical plans, ensuring delivery quality, and guiding engineers through implementation.

The Technical Lead manages the day-to-day technical delivery of engineering teams comprising junior, mid-level, and senior software engineers, working closely with Forward Deployed Engineers (FDEs) on customer-driven solution implementation and Technical Program Managers (TPMs) on delivery planning, milestone tracking, and dependency management.

The role requires strong expertise in system design, cloud-native development, AI application integration, engineering quality practices, and technical mentoring, with accountability for technical stability, delivery predictability, and implementation excellence.

Responsibilities:

Own the technical execution of software delivery across engineering workstreams, ensuring alignment with business requirements and solution architecture

Break down high-level architecture into implementable technical components, APIs, services, and engineering tasks

Lead system design discussions across application, data, and integration layers

Define and enforce engineering standards across development, testing, deployment, and documentation

Guide and support SDE1, SDE2, and SDE3 engineers in implementation, debugging, and technical problem-solving

Conduct code reviews and ensure adherence to coding standards, maintainability, and architectural integrity

Collaborate with FDEs on AI application integration patterns including LLM workflows, RAG pipelines, and agent orchestration

Work with TPMs to support effort estimation, technical dependency planning, and delivery sequencing

Identify technical risks early and define mitigation strategies across system design, integrations, and delivery execution

Ensure implementation of testing strategies including unit testing, integration testing, contract testing, and performance validation

Oversee CI/CD implementation and deployment readiness across development environments

Ensure observability, monitoring, and operational readiness are embedded into engineering solutions

Support incident troubleshooting and root cause analysis for production issues

Mentor engineers and support technical capability growth across the team

Improve team productivity by promoting engineering accelerators, automation, and effective use of AI-assisted development tools

Requirements:

Experience

6 to 10 years of software engineering experience

At least 2 to 4 years of technical leadership experience leading software engineering teams or major system components

Experience delivering enterprise-grade systems in complex engineering environments

System Design & Application Architecture

Strong hands-on expertise in system design and application architecture

Strong understanding of microservices architecture, service boundaries, and API contracts

Experience in distributed systems design, asynchronous processing, and event-driven patterns

Strong understanding of design patterns, SOLID principles, and modular application design

Experience designing systems for scalability, fault tolerance, and maintainability

Backend Engineering

Strong hands-on backend development experience using Python and/or JavaScript/TypeScript

Strong expertise in FastAPI or equivalent backend frameworks

Strong understanding of REST API principles, service orchestration, and integration patterns

Experience with asynchronous workflows and backend performance optimization

Frontend Engineering

Working knowledge of frontend development using React and modern UI frameworks

Understanding of frontend integration patterns and real-time interaction mechanisms (e.g., SSE)

Ability to guide frontend engineers on implementation quality and architecture alignment

AI Application Engineering

Working knowledge of LLM-based application development and applied AI integration patterns

Understanding of RAG architecture, retrieval optimization, and evaluation loops

Familiarity with guardrails, prompt workflows, and AI reliability mechanisms

Ability to support engineering teams implementing AI-enabled application workflows

Data Engineering & Data Handling

Strong understanding of data modeling and data flow design

Experience with SQL and NoSQL databases

Understanding of data pipelines, transformations, and data quality practices

Experience handling structured and semi-structured application data

Cloud & DevOps

Strong experience with Docker, Kubernetes, and containerized deployments

Strong understanding of CI/CD pipelines and release automation

Experience with Infrastructure-as-Code (Terraform)

Experience deploying applications in cloud environments (AWS, Azure, GCP)

Strong understanding of environment management and release strategies

Testing & Quality Engineering

Strong understanding of Test Driven Development (TDD)

Experience implementing unit, integration, and end-to-end testing strategies

Strong debugging and troubleshooting capability

Experience driving engineering quality improvements across teams

Security & Observability

Understanding of IAM, OAuth2, API security, and access control patterns

Understanding of secure application design principles

Experience implementing observability using Prometheus, Grafana, and OpenTelemetry

Strong understanding of logging, monitoring, and production diagnostics

Delivery Collaboration

Ability to collaborate effectively with TPMs on delivery planning and dependency management

Ability to collaborate with FDEs on customer-driven technical implementations

Strong understanding of Agile/Scrum engineering workflows

Experience working in structured sprint-based engineering environments

Soft Skills

Strong technical leadership and engineering decision-making capability

Strong mentoring and team enablement capability

Ability to communicate technical trade-offs clearly to both technical and business stakeholders

Strong problem-solving and root cause analysis mindset

High ownership and accountability for technical delivery outcomes

Strong collaboration across cross-functional teams

Ability to remain effective under delivery pressure and shifting priorities

Nice to Have

Experience supporting AI-first or GenAI application delivery

Experience with vector databases and semantic retrieval systems

Experience in enterprise-scale cloud modernization or digital transformation programs

Experience in telecommunications or other regulated industries

Experience working in multicultural or distributed teams

Japanese language proficiency preferred for client-facing or Japan-based roles

Language Requirements

English: Proficiency required

Japanese: Desirable