Engineering Manager – GPU Orchestration & AI Inference Platform

About Gruve

Gruve is an innovative software services startup dedicated to transforming enterprises to AI powerhouses. We specialize in cybersecurity, customer experience, cloud infrastructure, and advanced technologies such as Large Language Models (LLMs). Our mission is to assist our customers in their business strategies utilizing their data to make more intelligent decisions. As a well-funded early-stage startup, Gruve offers a dynamic environment with strong customer and partner networks.

Position Summary:

The Engineering Manager will lead the India engineering team building PulseAI, Gruve's on-premises, Kubernetes-native GPU orchestration and AI inference platform. This is a hands-on role: you will balance day-to-day delivery and people management with real technical involvement — reviewing designs and code, and unblocking engineers — while working closely with the Lead Architect / Product Owner to turn technical designs and JIRA backlogs into shipped, quality-tested increments. You will also grow a high-performing engineering team.

Key Roles & Responsibilities:

Lead and grow a team of engineers delivering PulseAI, Gruve's on-premises, Kubernetes-native GPU orchestration and AI inference platform

Own day-to-day engineering delivery: sprint planning, work breakdown, estimation, and tracking progress against roadmap commitments in partnership with the Product Owner and architecture team

Stay hands-on — review designs, participate in architecture discussions, read and review code, and unblock engineers on FastAPI/PostgreSQL backend, React frontend, and RKE2/OpenShift deployment issues

Translate technical design documents and JIRA stories into clear, sequenced execution plans for the India engineering team

Recruit, mentor, and develop engineers; run performance conversations, set growth plans, and build a strong engineering culture within the team

Coordinate closely with the external development vendor and internal architecture leadership to align delivery timelines, resolve cross-team dependencies, and maintain quality standards

Drive engineering best practices: code review discipline, CI/CD hygiene, test coverage, and consistent frontend routing and coding standards across the team

Partner with QA to plan release readiness, support UAT cycles, and ensure milestone sign-off criteria are met before delivery

Manage risk and dependency tracking across concurrent workstreams (Model Deployment, Observability & Metrics, Secrets Management, GPU Quota/Billing) and escalate blockers early

Contribute to technical decision-making on multi-tenant isolation, GPU resource quota enforcement, and identity/SSO federation as the platform evolves

Report on team velocity, delivery risk, and capacity to the Lead Architect / Product Owner and other stakeholders

Basic Qualifications:

Education: B.E / B.Tech or equivalent in Computer Science, Information Technology, or a related discipline

Experience: 10-15 years in software engineering, with at least 2-3 years in a engineering manager/ tech-lead capacity leading a team of 5-10 engineers

Demonstrated hands-on proficiency in at least one backend stack (Python/FastAPI or equivalent) and one frontend stack (React or equivalent), with the ability to review code and unblock engineers directly

Working knowledge of Kubernetes-native application development and deployment (RKE2, OpenShift, or vanilla K8s)

Experience managing delivery for complex, multi-service platforms (preferably virtualisation and control planes)

Well versed with Agile methodology including sprint planning, estimation, prioritisation, governance and reporting

Proven experience hiring, mentoring, and developing engineers, including performance management

Comfort working across India/US team structures and coordinating with external delivery vendors or partners

Strong communication skills, with the ability to translate between technical design detail and delivery status for architecture and product stakeholders

Preferred Qualifications

Experience with GPU-based infrastructure management and control platform, AI/ML inference platforms, or LLM serving stacks will be an solid added advantage

Familiarity with multi-tenant SaaS architecture, RBAC models, and quota/billing systems will be an added advantage

Experience with PostgreSQL schema-per-service architectures and event-driven or workflow automation tools (e.g., n8n) will be an added advantage

Exposure to Prometheus/Grafana-based observability stacks will be an added advantage

Prior experience managing or coordinating with offshore/nearshore development vendors will be an added advantage

Certifications such as CKA/CKAD or equivalent Kubernetes credentials are a plus

Why Gruve

At Gruve, we foster a culture of innovation, collaboration, and continuous learning. We are committed to building a diverse and inclusive workplace where everyone can thrive and contribute their best work. If you’re passionate about technology and eager to make an impact, we’d love to hear from you.

Gruve is an equal opportunity employer. We welcome applicants from all backgrounds and thank all who apply; however, only those selected for an interview will be contacted.