Tech Lead (.NET) — AI-Powered Video Platform @ DNA325

Must‑haves

• Technical leadership: you’ve led a small team (2–4 engineers) to ship production software, setting direction, unblocking work, and owning outcomes end‑to‑end
• Practical problem solving: you start from constraints and business goals, enumerate options, make trade‑offs explicit, and choose the smallest reversible step that works
• Clear, direct communication: you set crisp expectations with reports, write succinct PRs/decision records, and give kind‑but‑candid feedback that changes behaviour
• Ownership & accountability: you finish hard things, leave systems better than you found them (tests, telemetry, docs), and make accountability routine rather than personal
• Flexibility & product sense: you can cut scope to hit outcomes, re‑prioritise quickly when data changes, and keep stakeholders aligned
• Learning mindset & AI fluency: you adopt new tools fast (including AI assistants) and verify outputs with tests/metrics, respecting privacy and data safety

Nice to have:

• Cloud & infra: Azure (or equivalent), CI/CD, feature flags, safe rollouts/rollbacks
• Experience across media/SaaS, SDKs, or high‑throughput event ingestion
• C# / .NET expertise: strong experience with modern .NET (.NET 8+), building and operating Web APIs; comfortable with Minimal APIs or controllers
• SQL Server depth: confident with schema design, indexing, query shaping, and concurrency (transactions, isolation levels, deadlocks, idempotency)
• Interest in sport and fan engagement (helpful, not required)

Own outcomes, not just tickets

• Lead a squad of 2–4 engineers (mix of senior/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/APIs with SQL Server for a multi‑tenant B2B SaaS platform
• Make pragmatic trade‑offs: idempotent writes, rate limiting, caching/ETag, indexing and query shaping, back‑pressure, and failure‑mode handling

Operate what you build

• Instrument services with logs/metrics/traces; hold the line on p95/p99 performance and availability SLOs
• Run incident reviews that produce systemic fixes and documentation (runbooks, dashboards)

Prioritise for the business

• Partner with PM/Design/Customer teams to translate goals into scope; cut or resequence work when data changes
• Keep stakeholders aligned with concise updates, risks, and owner/dates

Create clarity and accountability

• Set explicit expectations with your reports; give direct feedback; follow through with support and check‑ins
• Use lightweight mechanisms—PR templates, decision records, checklists — to make accountability routine

Grow people and the codebase

• Mentor engineers via 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 boilerplate and documentation, and verify 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 the iOS/Android/Web SDK teams to ensure that backend APIs and contracts are stable, well-documented, and easy to integrate.
• Support enterprise client integrations (often in sport), balancing reliability with delivery speed.

Hire and onboard

• Contribute to interviews and rubrics; onboard new teammates with clear goals, docs, and a first‑week win.

Kategorie

artificialIntelligence