Note: The job is a remote job and is open to candidates in USA. The Phoenix Group is seeking a Software Engineering Manager to establish and lead high-quality software engineering practices across the organization. The role will define coding, review, testing, deployment, developer tooling, and internal platform standards while supporting both traditional and AI-assisted development. Over time, the position is expected to evolve into a Head of Software Engineering role with broader organizational ownership.
Responsibilities
- Defining how the org writes, reviews, tests, and ships code; building or selecting the internal developer platform and tooling; establishing engineering culture and norms; and driving adoption of those standards across teams, in both human-written and AI-assisted contexts
- Driving adoption of those standards across teams, in both human-written and AI-assisted contexts
- Defining what a good AI-assisted PR looks like, how to review vibe-coded output, when an LLM-generated prototype is productionready versus a liability, and how to preserve code quality, test coverage, and architectural integrity when a large share of engineers are prompting their way to a first draft
Skills
- A track record leading software engineering teams specifically (not infrastructure or ops), with strong personal coding roots
- Experience building or owning an internal developer platform as a software product: golden paths, self-service tooling, CI/CD treated as a developer experience problem
- A way of thinking about developer productivity in terms of cycle time, PR quality, DORA metrics, and test coverage, not uptime, cost optimization, or cloud architecture
- Experience driving engineering standards adoption across an organization (coding standards, code review culture, testing practices, architectural guardrails) with the ability to sell it, not just mandate it
- Deep, practical command of classical SDLC, from requirements through design, implementation, testing, deployment, and maintenance, and experience building or enforcing those practices in real engineering orgs
- Hands-on experience navigating the AI-assisted development shift: deploying LLM-powered IDEs (Copilot, Cursor, Claude Code), building agentic coding workflows, and reasoning carefully about where AI accelerates engineering versus where it introduces risk without discipline
- The ability to set standards specific to the AI-assisted era: what a good AI-assisted PR looks like, how to review vibe-coded output, when an LLM-generated prototype is productionready versus a liability, and how to preserve code quality, test coverage, and architectural integrity when a large share of engineers are prompting their way to a first draft
- A genuinely considered, defensible point of view on the human+AI engineering workflow, neither cheerleader nor skeptic, but a practitioner who has thought it through and built real systems around it
Company Overview