Tech Lead in Manchester

We're the team behind the AI-powered customer engagement platform that's transforming how businesses connect with their customers - turning every conversation into a revenue-driving moment. Our platform helps contact centre teams achieve their goals through intelligent automation, predictive insights, and seamless customer experiences. We build technology that empowers people, not replaces them. We are proud of our reputation for combining cutting-edge tech with down-to-earth people, we have big ambitions and a clear sense of who we are. Our culture is driven by our values: we take ownership, move fast, challenge the status quo, and learn constantly.

Working at MaxContact means being stretched, you’ll be trusted with responsibility early, expected to think commercially, and encouraged to act decisively. We don’t stand still, and neither will you. At the same time, we believe high performance only works in a safe, supportive environment. You’ll be surrounded by smart, driven people who want to see you succeed, who value openness and honesty, and who see mistakes as part of learning quickly and getting better.

We're builders, problem-solvers, and customer champions who believe in innovation with purpose, human-first technology, and delivering results that matter. You'll work alongside passionate colleagues building technology that directly impacts how thousands of businesses connect with millions of customers every day.

If you’re ambitious, curious, and excited by the idea of building something meaningful in a fast-moving tech business, we are looking for an ambitious and technically excellent Technical Lead.

Role Profile

As a Technical Lead at MaxContact, you will be accountable for the technical leadership and delivery of a dedicated Scrum team. You will combine hands-on engineering with ownership of sprint outcomes, ensuring work is well-shaped, delivered predictably, and meets a high bar for quality, reliability, and security in live contact-centre environments. You are responsible for turning Product intent into clear technical plans, guiding the team through discovery, design, delivery, and production readiness. You will actively lead sprint execution, manage technical risk, and ensure the team balances feature delivery with operational excellence, modernisation, and customer-impacting defects. Beyond delivery leadership, this role places strong emphasis on AI-driven engineering practices and technical standards.

You will model and embed responsible use of AI developer tools, collaborate closely with engineers to continuously refine practices, and ensure AI-enabled capabilities are built safely and are production-ready for a mission-critical platform. You will work closely with Product and Platform to shape technical direction, lead safe modernisation of legacy technology to modern .NET and Vue.js frameworks, and help the team respond effectively to real, customer-impacting incidents and defects while maintaining sustainable ways of working.

Responsibilities

• Sprint Leadership & Delivery
  • Act as technical owner for a Scrum team, accountable for sprint outcomes, delivery predictability, and technical quality.
  • Lead technical refinement, breaking down work into thin, well-understood slices with clear acceptance criteria, dependencies, and risks.
  • Partner closely with Product to shape scope, manage trade-offs, and ensure sprint commitments are realistic and value-focused.
  • Actively manage delivery risk during the sprint, unblocking engineers and adjusting approach to maintain momentum.
• Engineering & Architecture
  • Design, build, and evolve backend services and APIs using C# / .NET, making pragmatic architectural decisions aligned to team and platform standards — directly and through AI agent delegation — ensuring that agent-generated code meets the same quality, security, and architectural standards as human-authored code.
  • Guide the team through complex changes, refactors, and migrations, ensuring safe rollouts and production readiness.
  • Lead frontend standards and evolution using Vue.js, supporting migration from legacy technologies.
• Reliability & Operational Ownership
  • Ensure reliability is built into sprint delivery through appropriate testing, observability, and operational readiness.
  • Own incident response for the team’s areas: lead root-cause analysis and ensure learnings translate into durable fixes and runbooks.
  • Champion monitoring, alerting, and sustainable on-call practices to support the platform’s mission-critical nature.
• AI-Driven Engineering Practices
  • Lead by example in responsible, effective use of AI developer tools to improve delivery speed, test coverage, and documentation.
  • Establish and continuously refine team practices for AI-assisted development, focusing on collaboration, validation, and shared learning.
  • Support engineers in using AI to explore edge cases, improve tests, and reduce rework without compromising quality or security.
  • Drive a culture of active AI tool experimentation and rapid workflow adaptation within the team.
  • Evaluate emerging AI engineering capabilities and make pragmatic decisions about adoption.
  • Ensure the team uses AI agents as primary workflow partners — not just inline code completion — for code generation, refactoring, test creation, and documentation.
  • Set standards for AI task delegation, context management (e.g. repository instruction files, prompt templates), and output validation across the team.
• Coaching, Collaboration & Quality
  • Provide day-to-day technical leadership through pairing, code reviews, and design discussions.
  • Use AI tools to augment code review effectiveness — including automated security scanning, consistency checking, and pre-review analysis — focusing human review effort on architectural judgement, business logic correctness, and design quality.
  • Set and uphold clear quality bars for the team, ensuring testing and review depth matches customer and operational risk.
  • Foster a collaborative, high-trust team environment aligned with Agile values and continuous improvement.
  • Maintain high-quality architectural documentation, coding standards, and domain context that serves both human engineers and AI development tools.

Values and Behaviours

• Customer Centric - Design and deliver features, integrations and reliability improvements that directly improve customer success.
• Own It - Take end-to-end responsibility for delivery, quality and technical debt, be accountable for successful outcomes.
• One Team - Collaborate tightly with Product and Platform to build trust, share goals, remove blockers and coach the team to succeed together.
• Make It Count - Prioritise solutions that improve reliability, scalability, model quality and long-term velocity with measurable results.
• Challenge The Status Quo - Continuously question assumptions and improve systems, tooling and processes.

Success Measures

• The sprint team consistently meets commitments with high-quality, production-ready outcomes.
• Clear improvement in delivery predictability, reduced rework, and faster feedback cycles.
• Strong operational health in owned areas, with fewer repeat incidents and faster recovery.
• Drives measurable improvements in team throughput, quality, and lead time through the adoption and refinement of AI-native engineering workflows.
• Accountable for ensuring AI tools are embedded into the team’s definition of done — covering code generation, test creation, code review preparation, and documentation — with clear metrics tracking adoption and impact.

Training and Enablement

• As part of the role you will be expected to continuously develop your skill set, take ownership of your growth, and help uplift the team through shared standards and mentoring.
• Structured onboarding plan with clear expectations for technical ownership and impact.
• Dedicated time for learning and deep-dives into platform, reliability, and AI-enabled capabilities.
• Budget for relevant certifications and conference attendance.
• Peer collaboration and mentorship (both receiving and providing).
• Regular 1:1s and coaching from leadership, including career progression support.
• Opportunities to lead discovery, POCs, and technical proposals.
• Training and support on security, compliance, and operational excellence.

Skills and Experience

Essential

• Strong experience as a senior engineer or technical lead in Agile Scrum teams.
• Proven ability to lead sprint delivery while remaining hands-on with C# / .NET (6–8) and modern frontend frameworks (Vue.js or similar).
• Demonstrated ability to shape work from ambiguity into clear plans, thin slices, and dependable delivery, communicating trade-offs and risks.
• Strong coaching, communication, and stakeholder collaboration skills (Product, Platform, Support/Operations).
• High bar for code quality, testing strategy (unit/integration/end-to-end), and production readiness appropriate to customer impact.
• Experience owning production systems where reliability, security, observability, and correctness matter (including incident response and root-cause analysis).
• Comfortable using AI developer tools responsibly (e.g., Copilot or similar), with clear validation practices and awareness of security/privacy considerations.
• Proven experience leading teams that use agentic AI workflows as a standard part of software delivery.
• Able to set team-wide standards for AI task delegation, context management, and output validation.

Desirable

• Experience leading teams working on SaaS platforms in live customer environments.
• Strong experience with containerisation (Docker) and CI/CD pipelines, including improving build/release reliability and speed.
• Experience with cloud services and operational tooling (e.g., Azure/AWS), including monitoring and alerting.
• Hands-on exposure to AI-enabled systems (e.g., Azure OpenAI, vector search, RAG), including evaluation/guardrails and safe rollout practices.
• Track record modernising legacy codebases, reducing technical debt, and improving architectural fitness over time.
• Experience maintaining repository-level AI context and instruction files (e.g. CLAUDE.md, .cursorrules) that improve AI-assisted development quality and consistency across a codebase.
• Exposure to contact-centre, telephony, or CCaaS platforms operating in live customer environments.
• Awareness of emerging multi-agent development patterns and tools (e.g. parallel agent coordination, specialised review agents, automated CI/CD integration with agentic workflows) and interest in evaluating their applicability to team workflows.

Benefits and Perks

• 25 days annual leave plus your birthday off.
• Increased holiday entitlement with length of service.
• Enhanced maternity and paternity packages.
• Life insurance.
• Enhanced pension options.
• Company-paid sick leave.
• Personal training allowance.
• Buy and sell holiday options.
• Social, charity and culture committee events.
• Hybrid working (minimum two days in the office).
• Onsite gym facilities.
• Employee assistant programme.

AI in Our Hiring Process

At MaxContact, we expect engineers to work effectively with AI tools every day. We welcome candidates who use AI to prepare their applications and encourage you to demonstrate your ability to collaborate with AI during any take-home assessments. During live interviews, we will assess your ability to think through problems and make engineering decisions — both with and without AI assistance.

We are an equal opportunity employer, if you require any adjustments during the hiring process please contact [email protected]