Team Lead, Engineering, Data & AI

Company Overview:

Arctiq is a global, intelligence-driven technology services company delivering professional and managed services across Hybrid Cloud Infrastructure, Networking & Connected Experiences, Cybersecurity, Data & AI, Autonomous Operations & Intelligence, and Enterprise Service Management. We help organizations operate, secure, and modernize complex environments by unifying infrastructure, networking, data, security, automation, and observability under a single, integrated operating model. Our work focuses on helping customers reduce operational friction, improve resilience, and make better, faster decisions as their environments evolve. Arctiq builds on decades of industry expertise and a customer-centric ethos to deliver exceptional value to clients across diverse industries.

Job Summary:

We are seeking a detail-oriented and proactive Team Lead, Engineering, Data & AI, to join our team. This role leads a team of solution engineers who deliver fixed-price, outcome-based data and AI projects for our clients. This is a high-accountability leadership role where technical excellence and commercial discipline are equally important — in a fixed-price model, every scoping decision, delivery risk, and scope change has a direct impact on project margin and client trust. Reporting to the Director of Data & AI, you will own the full delivery lifecycle across your team's client portfolio: from pre-sales scoping and SOW definition through to outcome acceptance. You will work in close partnership with the Architecture team to ensure solutions are right-sized and deliverable within agreed commercial boundaries, and you will be the senior escalation point for clients when engagements encounter turbulence.

Core Responsibilities:

Delivery Ownership & Commercial Management

Own the end-to-end delivery of a portfolio of fixed-price client engagements, ensuring outcomes are achieved on scope, on time, and within budget

Maintain rigorous visibility into project health across the team — tracking effort burn, milestone progress, and risk indicators on every active engagement

Lead scope management with discipline: identify scope creep early, facilitate change order conversations with clients, and protect project margin without damaging relationships

Ensure project financials are accurate and current — own gross margin reporting for your team's delivery portfolio in partnership with the Director

Conduct structured post-engagement reviews to capture lessons learned and feed improvements back into scoping, methodology, and estimation practices

Pre-Sales & Scoping

Partner with sales and business development to scope new client opportunities — translating client requirements into technically sound, commercially viable fixed-price proposals

Lead or oversee effort estimation for engineering deliverables, applying rigorous bottom-up analysis and incorporating appropriate risk buffers for uncertainty

Review and sign-off on SOW language relating to engineering deliverables, acceptance criteria, and out-of-scope boundaries before contracts are executed

Support client discovery workshops and technical due diligence, helping prospects build confidence in our delivery capability and approach

Client Relationship Management

Serve as the senior engineering point of contact for clients on active engagements, building trusted relationships with client-side technical leads and project sponsors

Proactively communicate project status, risks, and decisions — clients in a fixed-price model need confidence that their outcomes are being actively managed

Lead difficult conversations when engagements are off-track: own the recovery plan, align with the client on a path forward, and follow through

Represent the engineering team in client steering committees and executive check-ins as needed

Team Leadership & Development

Lead, coach, and develop a team of solution engineers — from junior to senior — building capability in both technical delivery and client-facing professionalism

Assign engineers to engagements thoughtfully, balancing project requirements, individual development goals, and team utilization

Set and model the standard for delivery quality, client communication, and commercial awareness within the team

Conduct regular 1:1s, structured performance reviews, and proactive career development conversations — invest in your people's long-term growth, not just immediate project needs

Build a team culture where engineers feel accountable for outcomes, not just activities

Methodology, Tooling & Repeatability

Build and continuously improve the delivery playbooks, estimation templates, and reusable accelerators that help the team scope and execute engagements more predictably

Identify patterns across client engagements and codify repeatable solution components that reduce delivery risk and improve margin on future work

Partner with the Architecture team to ensure delivery methodology stays aligned with sound technical design principles.

Evaluate and introduce tooling, frameworks, or AI-assisted development practices that meaningfully improve engineering throughput on client projects

Requirements:

Experience

7+ years in data engineering, ML/AI engineering, or a closely adjacent technical discipline

3+ years in an engineering leadership or delivery management role within a professional services, consulting, or systems integration firm

Demonstrated experience owning fixed-price or outcome-based client engagements — you understand the commercial mechanics and have managed both successful projects and recoveries

Track record of building and developing high-performing engineering teams in a client-delivery context

Experience supporting pre-sales processes, including scoping, estimation, and proposal development

Technical Skills

Strong working knowledge of modern cloud data platforms (e.g., Databricks, Microsoft Fabric, BigQuery, etc.) and the patterns used to build production data solutions on them

Familiarity with AI and ML engineering — including model deployment, MLOps, and practical application of LLMs (RAG pipelines, prompt engineering, API integration)

Proficiency in Python and SQL; hands-on familiarity with dbt, Airflow, Spark, or equivalent transformation and orchestration tooling

Ability to read, review, and provide meaningful technical feedback on engineering work — you may not be coding day-to-day, but you can tell good from poor solution design

Understanding of DataOps principles: CI/CD for data, data quality frameworks, testing, and observability in production

Commercial & Delivery Skills

Sharp commercial instincts — you understand how fixed-price projects make or lose money and can translate that understanding into the daily decisions your team makes

Strong estimation and risk assessment skills; you know how to build contingency into a scope without pricing yourself out of a deal

Experienced with SOW structure, acceptance criteria definition, and change order management

Comfortable with project financial reporting — burn rates, margin tracking, and forecasting at the portfolio level

Leadership & Client Skills

Confident, credible communicator with senior client stakeholders — you can hold a room, navigate difficult conversations, and maintain trust under pressure

Empathetic people manager who develops engineers as whole professionals, not just technical contributors

Organized and decisive — you manage ambiguity well, prioritize across competing demands, and keep your team focused on what matters

You bring calm to a crisis. When an engagement is at risk, you stabilize, assess, and lead a recovery rather than escalating the problem upward

Arctiq is an equal opportunity employer. If you need any accommodations or adjustments throughout the interview process and beyond, please let us know. We celebrate our inclusive work environment and welcome members of all backgrounds and perspectives to apply.

We thank you for your interest in joining the Arctiq team! While we welcome all applicants, only those who are selected for an interview will be contacted.