Engineering Team Lead at TeKnowledge in Lagos, Lagos, Nigeria

Overview

We are building an AI-Native Engineering team and are looking for an Engineering Team Lead who is a strong hands-on technologist first and a leader second. You will lead a cross-functional team of full stack engineers, quality engineers, and DevOps engineers, taking end-to-end accountability for the design, delivery, quality, and operation of the software the team ships. You will partner closely with product managers and architects, set the technical direction for the team, and personally contribute to architecture, code, pipelines, and production readiness.

The ideal candidate has deep full stack experience, working knowledge of modern DevOps and cloud infrastructure, and treats AI tooling and prompt engineering as core craft. They raise the bar technically, automate aggressively, and consistently move the team from concept to production software at pace. If this describes you, we would like to hear from you.

Mindset & Ways of Working

• Strong bias toward automation and efficiency
• Comfortable in rapid, iterative environments
• Curious and proactive in adopting new tools and approaches
• Able to move from idea → prototype → production quickly
• Focused on outcomes and speed, not just code quality
• Excellent organizational and problem-solving skills

At TeKnowledge, your work makes an impact from day one. We partner with organizations to deliver AI-First Expert Technology Services that drive meaningful impact in AI, Customer Experience, and Cybersecurity. We turn complexity into clarity and potential into progress—in a place where people lead and tech empowers.

You’ll be part of a diverse and inclusive team where trust, teamwork, and shared success fuel everything we do. We push boundaries, using advanced technologies to solve complex challenges for clients around the world.

Here, your work drives real change, and your ideas help shape the future of technology. We invest in you with top-tier training, mentorship, and career development—ensuring you stay ahead in an ever-evolving world.

Why You’ll Enjoy It Here:

• Be Part of Something Big – A growing company where your contributions matter.
• Make an Immediate Impact – Support groundbreaking technologies with real-world results.
• Work on Cutting-Edge Tech – AI, cybersecurity, and next-gen digital solutions.
• Thrive in an Inclusive Team – A culture built on trust, collaboration, and respect.
• We Care – Integrity, empathy, and purpose guide every decision.

We’re looking for innovators, problem-solvers, and experts ready to drive change and grow with us.

We Are TeKnowledge. Where People Lead and Tech Empowers.

Responsibilities

• Lead a cross-functional team of full stack engineers, quality engineers, and DevOps engineers
• Own end-to-end delivery across design, development, testing, deployment, and operation
• Set and evolve the technical direction, architecture, and engineering standards for the team
• Contribute personally to architecture, code, code review, and production troubleshooting
• Plan and prioritise work in collaboration with product managers and architects
• Drive rapid prototyping and iteration cycles, and decide when to invest vs. when to discard
• Own delivery commitments, technical risk, and trade-off decisions for the team
• Define and uphold engineering practices: branching, code review, testing, release, and on-call
• Own CI/CD, environments, infrastructure-as-code, observability, and production reliability with the DevOps engineers
• Own the team's quality strategy together with QA: test pyramid, automation coverage, release gates, and UAT
• Apply secure coding and secure operations practices throughout the SDLC (OWASP Top 10, input validation, authentication, secrets management, vulnerability remediation, least-privilege access)
• Lead incident response: triage, mitigation, root cause analysis, and follow-up actions
• Mentor and grow engineers, QA, and DevOps team members; give direct, actionable feedback
• Recruit, interview, and onboard new team members
• Communicate progress, risks, and decisions clearly to product, architecture, and stakeholders
• Document architecture decisions, designs, runbooks, and post-incident reviews

AI-Native Engineering Leadership

• Set the team's AI-native engineering practice: how the team uses Claude, GitHub Copilot, Cursor, and similar tools day to day
• Lead by example in using AI tools to design, build, test, document, and operate software
• Apply prompt engineering and structured prompting techniques to generate code, tests, documentation, and operational runbooks
• Design and evolve workflows that integrate AI into the full software development and delivery lifecycle
• Champion AI-assisted testing strategies in partnership with QA, including automated test generation and edge-case simulation
• Use AI tools to identify bugs, vulnerabilities, and performance issues earlier in the cycle
• Drive AI-assisted observability, incident triage, and operational automation in partnership with DevOps
• Critically evaluate AI-generated outputs and ensure they meet production-quality standards before they ship
• Build and maintain internal AI-assisted development frameworks, prompts, and reusable patterns
• Continuously evaluate and adopt emerging AI development, testing, and DevOps tools, and roll the best ones out across the team

Qualifications

Experience

• Minimum 5 years of professional software engineering experience, including significant full stack delivery
• Minimum 2 years leading a software engineering team or tech-leading a cross-functional squad
• Proven track record of shipping production systems end-to-end, from architecture through operation
• Hands-on experience across software development, scripting, DevOps/CI-CD, and Agile/Scrum delivery
• Demonstrated ability to operate autonomously and partner directly with architects, product, and senior stakeholders
• BSc/BA in Computer Science or a related degree

Technical Skills

• Strong, current, hands-on command of core languages and frameworks: Node.js, TypeScript, React, C#, Python; familiarity with Flutter
• Strong system design skills: distributed systems, APIs, data modelling, and service boundaries
• Solid understanding of JSON, REST, and OpenAPI spec, and of API versioning and contract design
• In-depth knowledge of relational databases (MySQL, PostgreSQL) and NoSQL databases (Cosmos DB, MongoDB), including schema design, indexing, and query performance
• Hands-on experience with DevOps and platform engineering: CI/CD pipelines (e.g., Azure DevOps, GitHub Actions), containers (Docker), and orchestration (Kubernetes)
• Experience operating workloads on at least one major cloud (Azure, AWS, or GCP), including IAM, networking, and cost awareness
• Working knowledge of infrastructure-as-code (e.g., Terraform, Bicep, ARM) and configuration management
• Experience with observability and SRE practices: logging, metrics, tracing, alerting, SLOs, and incident response
• Familiarity with Windows and Unix operating systems
• Strong grasp of secure coding and secure operations practices, including secrets management and vulnerability remediation
• Experience defining and enforcing engineering standards: code review, testing strategy, branching, and release management

AI & Automation Skills

• Hands-on experience using AI-assisted coding tools (Claude, Copilot, Cursor) in real production workflows
• Strong understanding of prompt engineering and structured prompting techniques
• Ability to validate, refine, and harden AI-generated code, tests, and configuration before it ships
• Familiarity with AI/LLM APIs (Anthropic, OpenAI, Azure OpenAI), including cost, latency, and safety trade-offs
• Experience building automation workflows or internal tools using AI to accelerate engineering, QA, or DevOps work
• Demonstrated ability to roll out AI-native ways of working across a team, not just use them individually

Preferred Qualifications

• Experience leading teams that include engineers, QA, and DevOps in the same delivery group
• Experience building AI-powered applications (chatbots, copilots, agents, automation tools) in production
• Familiarity with vector databases, embeddings, RAG architectures, and evaluation of LLM outputs
• Experience integrating AI into enterprise workflows, including data, security, and compliance considerations
• Experience with performance and security testing strategies at a team level
• Experience owning on-call, SLOs, and production reliability for customer-facing systems
• Excellent organisational, coaching, and stakeholder-management skills
• Analytical mind with strong problem-solving aptitude and sound technical judgement under pressure