About the job:

We are hiring a hands-on principal engineer to lead our new AI-first engineering pod a small, high-trust team that ships real product and platform work in our existing payments codebase, then helps the rest of engineering adopt what works.

This is not an advisory architecture role. You will code, review, unblock, and ship while building the AI-first operating model from evidence, not slides. Framework work should emerge from what the pod proves in production: tooling choices, review practices, guardrails, and team habits that other squads can pick up without reinventing the wheel.

Over time, as the model proves itself, the pod is expected to grow into a full scrum team and potentially split into two scrum teams, as delivery capacity and adoption mature. You should be comfortable starting lean and hands-on, then evolving into a team lead who can run backlog, ceremonies, and engineering practices at squad scale.

AI-frst means agent-first development with human checkpoints where they matter orchestrated pipelines, not a developer alone in a chat window. Work flows through defined steps: intake context assembly agent execution automated review gates human approval production.

Using Cursor or Copilot well is a baseline. We want someone who has designed and built agentic orchestration: pipelines that connect real systems (Slack, issue trackers, Git, CI/CD) and run multi-step agent workflows with guardrails, audit trails, and human escalation at the right points. It does not mean unmanned codegen or bypassing regulated change control.

How the team works:

- You will start with a lean pod (you plus a handful of engineers) owning a bounded slice of product or platform delivery. The pod is a reference implementation, not a silo. Success includes what the wider organisation learns from it.
- | Phase | Shape |
- | 0 6 months | Lean pod prove the workflow, draft the playbook |
- | 6 12 months | Full scrum team sustainable velocity and rituals |
- | 12+ months | One or two scrum teams delegation and org-wide champions |
- You will bring existing engineers along through pairing, short secondments, open working sessions, and a living playbook on tools, guardrails, and review practices. Expect roughly half your time on pod delivery, a quarter on codifying and teaching,



and the remainder on org-wide influence tool approval, guardrails, and high-risk design review.

Key Responsibilities:

- Lead pod delivery end-to-end: backlog refinement, technical breakdown, implementation, review, and release.
- Design and build agentic orchestration pipelines e.g. a bug reported in Slack or Plane flowing through triage, context gathering, fix attempt, PR creation, and automated review before a human merges.
- Wire agentic review triggers into PR and CI/CD workflows: security analysis, bug-risk review, test gap detection, dependency checks with clear pass/fail/escalate behaviour and auditability.
- Use AI-assisted development responsibly across coding, testing, debugging, refactoring, documentation, and code review coaching the pod without bypassing engineering fundamentals.
- Ship production-visible outcomes early and codify what works into standards, guardrails, and tooling choices the wider org can adopt.
- Provide pragmatic technical leadership on pod-owned work and high-risk cross-cutting decisions; advise (not own) wider platform architecture.
- Lead one high-leverage modernisation path the pod can execute including assessment of our .NET Core 2.1 estate and a pragmatic upgrade recommendation.
- Improve the pod s path to production: Git workflows, CI/CD (Jenkins and/or GitHub Actions), testing expectations, and quality gates then propose rollouts others can follow.
- Grow the pod: hiring, onboarding, scrum maturity, and mentorship across distributed and offshore engineers.
- Ensure everything ships with fintech-grade security, compliance, auditability, and operational discipline including careful evaluation of AI vendor and tooling risk.

Tech stack:

- You do not need expert depth in every technology on day one, but you must learn quickly and reason credibly across the stack.
- Frontend: React, TypeScript
- Backend: .NET / C# (including legacy .NET Core 2.1), Java, Go
- Data: SQL Server
- Platform: AWS,



Jenkins / GitHub Actions, Plane (Jira during transition)
- AI and agents: coding assistants plus agent orchestration multi-step workflows, MCP/tool integration, PR and CI/CD hooks, webhook-driven pipelines (not GUI-only usage)

Qualifications:

- 8+ years in software engineering, with senior technical leadership experience.
- Robust hands-on skills in existing production codebases not only greenfield.
- Experience leading or contributing materially to a small team shipping real work.
- Track record of mentoring and rolling out new engineering practices beyond your own team.
- Practical, safe use of AI-assisted development tools.
- Built agentic pipelines, not only used an AI IDE. You can describe systems you designed: triggers, agent steps, human checkpoints, CI/CD integration, and what happened when they failed.
- React/TypeScript and .NET/C# experience; strong architecture and communication skills.
- Fintech, payments, or regulated environments.
- Legacy .NET Core upgrades; Java or Go in production.
- Growing a pod or small team into a stable scrum team (or leading multiple squads).
- Creating engineering standards, test automation, or secure SDLC practices.
- Using AI to accelerate codebase comprehension, refactoring, test generation, or migration planning.
- Agentic SDLC automation: PR review agents, security scanning in CI/CD, bug-triage-to-fix pipelines, Slack or issue-tracker integrations.

How you work:

- You are pragmatic, hands-on, AI-forward but not reckless, and comfortable growing from pod lead into multi-squad leadership without losing technical credibility.
- You live in your AI tools continually experimenting and learning as models, products, and practices evolve, and bringing that curiosity back to the team. You enjoy sharing what you know in open technical discussion: pairing, working sessions, and honest conversation about what works and what does not. You are proactive about business context asking product and leadership the questions that sharpen technical.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 AI Principal Engineer (India)
🏢 Teamified
📍 India