Job Description
Ovii's Interpretation of the Role
Engineering Manager leading the backend AI‑native products (Agent Mode & AI Engineer) at Postman. You will own the roadmap, drive architecture, and grow a small engineering team while coding hands‑on and leveraging AI tooling to boost productivity.
Role Snapshot
- Lead backend engineering for AI‑native products
- Hands‑on code reviews and architecture decisions
- Drive AI tooling adoption for the team
- Mentor and grow engineers
- Own roadmap, sprint cadence and quality
- Partner with product, design and GTM
Must-Have Requirements
- backend engineering experience
- architectural depth
- hands‑on coding / code reviews
- team management with direct IC reports
- backend engineering
- system design
Nice-to-Have Signals
- exposure to agentic architectures
- LLM tool use
- MCP
- observability platforms
- developer tooling
- AI‑native product development
- agentic architectures
Work Setup
- Work mode: ONSITE
- Employment type: Full-Time
Eligibility Gates
- Visa sponsorship: unknown
Not Specified in JD
- Visa sponsorship
- Salary range
- Remote eligibility
- Coding test
What You'll Likely Work On
- Own the engineering roadmap for Agent Mode and AI Engineer, aligning with product and ensuring sprint cadence
- Make architectural decisions and uphold code quality across backend systems, staying hands‑on to spot issues early
- Track work, surface risks, and manage dependencies to keep the team moving efficiently
- Partner with product, design, and GTM to define AI‑native API development for enterprise customers
- Engage directly with customers and field teams to gather feedback and prioritize engineering effort
- Mentor engineers, expand their scope, and build a team capable of higher autonomy
- Leverage AI tooling to increase team output and reduce manual effort
Good Fit If You Have
- Experience with agentic architectures or LLM tool integration
- Familiarity with observability platforms or developer tooling
- Passion for building AI‑native developer products
Skills
- Backend engineering
- System architecture & design
- Hands‑on coding / code review
- Team leadership & mentorship
- AI/LLM tooling
- Observability platforms
- Developer tooling