Founding / AI-Native Tech Lead

AI-First B2B SaaS Platform (Media & Sports Intelligence)
 

We are partnering with a global B2B SaaS company to hire a Founding / AI-Native Tech Lead for an AI-first platform that processes, analyzes, enriches, and operationalizes large volumes of multimedia and social content for enterprise customers across sports and media.

This is not a traditional Tech Lead role.

While the company operates at enterprise scale, we expect the Tech Lead in this role to operate with a startup-style mindset: strong personal ownership, comfort with ambiguity, rapid iteration, and a bias toward shipping and learning in production.

We are looking for a high-agency, AI-native engineering leader who owns outcomes end-to-end, treats AI as a default way of working (not an add-on), and is comfortable defining problems as often as solving them.
 

About the Project

The platform aggregates content from social media posts, podcasts, online articles, images, and videos into a single searchable index. It enriches this content with AI-generated metadata such as taxonomy, sentiment, storyline links, and contextual insights.

These insights are used to power:

• automated reporting,
• conversation and trend analysis,
• content generation.

The system is fully AI-enabled and is being rolled out widely across the customer base.
 

Responsibilities

Own outcomes, not just tickets

• Lead a squad of 2–4 engineers (mix of senior and junior) to deliver measurable product impact
• Set clear goals and success metrics (e.g. latency, reliability, adoption)
• Break work into small, reversible slices and ship on a steady cadence

Design and build production systems

• Architect and implement .NET services and APIs with SQL Server for a multi-tenant B2B SaaS platform
• Make pragmatic trade-offs around idempotent writes, rate limiting, caching/ETag usage, indexing and query shaping, back-pressure, and failure-mode handling

Operate what you build

• Instrument services with logs, metrics, and traces
• Own p95/p99 performance and availability SLOs
• Run incident reviews that produce systemic fixes and clear documentation (runbooks, dashboards)

Prioritise for the business

• Partner with PM, Design, and Customer teams to translate goals into scope
• Cut or resequence work when data changes
• Keep stakeholders aligned with concise updates, risks, and ownership

Create clarity and accountability

• Set explicit expectations with reports
• Give direct, kind-but-candidate feedback
• Use lightweight mechanisms (PR templates, decision records, checklists) to make accountability routine

Grow people and the codebase

• Mentor engineers through pairing, reviews, and 1:1s
• Create growth plans and celebrate momentum
• Keep standards high: tests where they matter, clear interfaces, and intentional debt management

Leverage AI effectively

• Use AI assistants to accelerate development and documentation
• Verify AI outputs with tests and metrics
• Help the team adopt safe practices (no secrets, anonymised data, prompt discipline, simple evals)

Collaborate across the product suite

• Work with iOS, Android, and Web SDK teams to ensure backend APIs and contracts are stable, well-documented, and easy to integrate
• Support enterprise client integrations, balancing reliability with delivery speed

Hire and onboard

• Contribute to interviews and evaluation rubrics
• Onboard new teammates with clear goals, documentation, and a first-week win

Qualifications

Must-haves

• Technical leadership experience: leading a small team (2–4 engineers) to ship and operate production software end-to-end
• Practical problem solving: starting from constraints and business goals, making trade-offs explicit, and choosing the smallest reversible step that works
• Clear, direct communication with engineers and stakeholders
• Ownership and accountability mindset
• Flexibility and product sense: ability to re-prioritise when data changes
• Learning mindset and AI fluency: adopting new tools (including AI assistants) and validating outputs with tests and metrics

Nice to have

• Cloud and infrastructure experience (Azure or equivalent), CI/CD, feature flags, safe rollouts
• Experience across media, SaaS, SDKs, or high-throughput event ingestion
• Strong C# / modern .NET experience building and operating Web APIs
• SQL Server depth: schema design, indexing, query shaping, concurrency
• Interest in sport and fan engagement

If you’re excited about building AI-driven content intelligence systems and leading high-impact engineering teams, we’d be happy to discuss this opportunity with you.