As an AI Platform, Edge & Infrastructure Engineer at Kearney, you will contribute to consulting project teams as they offer honest advice and practical guidance to our clients. Depending on each clients unique needs, projects can differ in length, size, and location, giving you unique, hands-on experiences across a range of industries and service practices.

Responsibilities

1. Own platform reliability and deployment

- Manage the cloud and container platform that supports internal demos, client pilots, and production deployments.
- Build and maintain CI/CD workflows, release patterns, environment configuration, secrets management, and observability.
- Ensure the platform remains stable, debuggable, and secure as the product portfolio evolves.

2. Build hybrid, on-premise, and edge deployment capabilities

- Design deployment patterns across cloud, client-managed environments, on-premise systems, and air-gapped setups.
- Package repeatable Velocity in a Box distributions for high-density compute hardware and client-specific constraints.
- Support data-residency, security, and latency-sensitive requirements that require local execution.

3. Enable AI and GPU workloads

- Deploy and operate model-serving infrastructure, vector databases, agent runtimes, and other AI-specific platform components.
- Manage GPU capacity, storage, networking, and performance tuning for inference-heavy or multimodal workloads.
- Optimize for uptime, latency, utilization, and cost without sacrificing developer velocity.

4. Extend the platform into physical environments

- Support integrations with industrial robots, IoT devices, edge sensors, and factory or engineering data sources where needed.
- Work across conventional and unconventional interfaces to make solutions deployable in the environments where clients actually operate.
- Help define practical deployment patterns for solutions that must bridge software systems and physical operations.

5. Maintain security, operability, and resilience

- Implement identity, access control, network security, backup and recovery,



monitoring, logging, and incident-response practices.
- Create clean runbooks, deployment guides, and troubleshooting standards that reduce operational fragility.
- Partner with Kearney security and client IT teams where enterprise controls or custom approvals are required.

Who you are After nearly 100 years, we know this business is fundamentally about making connectionsbetween facts, figures, insights, strategies, tools, technologies, and above all, people. Thats why we look for collaborative, insightful, and inquisitive problem-solvers who dont accept the first thing in front of them and who are always unapologetically themselves.

We want to hear from you if you are:

- Ready to share your ideas and contribute as soon as you join a team
- Analytically inclined and enjoy solving problems
- Able to prioritize and are a doer by nature
- 6 -10 Years of Experience
- Strong hands-on platform engineering across Linux, networking, containers, Kubernetes, infrastructure-as-code, and CI/CD.
- Experience with Azure and cloud-native infrastructure patterns; experience across additional cloud providers is a plus.
- Practical experience operating AI workloads, including model serving, vector databases, GPU-backed infrastructure, and performance troubleshooting.
- Experience designing or supporting hybrid, on-premise, or air-gapped deployments.
- Robust scripting and automation ability in Python, Bash, or similar languages.
- Good security instincts across secrets, identity, networking, environment isolation, and enterprise deployment constraints.
- A builder mentality: you debug deeply, remove friction for developers,



and care about how systems behave in the real world.

Client-Facing Mindset

- Communicate clearly with senior client stakeholders, domain experts, and non-technical audiences.
- Translate messy business problems into crisp technical or product decisions.
- Understand where AI can add value in real product and operations workflows rather than chasing novelty.

Personal Traits

- High agency and ownership: you move from ambiguity to action without waiting for perfect instructions.
- Speed with judgment: you move fast, but you know where rigor matters.
- Curiosity and range: you enjoy learning new tools, domains, and problem spaces.
- Low ego, high collaboration: you work well with partners, clients, and specialists across disciplines.
- Responsible use of AI: you care about security, reliability, and practical value, not just impressive demos.

Nice to Have

- Experience with edge or industrial integration patterns, including protocols such as MQTT, OPC UA, or adjacent approaches.
- Exposure to robotics, IoT, factory systems, or other deployments close to physical operations.
- Experience packaging solutions for NVIDIA DGX-class or other high-density compute environments.
- FinOps, capacity planning, and cost optimization experience for AI-heavy workloads.

What we can offer you Every day, our people work to be the difference for our clients, our communities, and our colleagues. Helping them make an impact, they are sustained by a competitive remuneration package plus comprehensive benefits and perks, including but not limited to:

- Generous retirement/pension savings contributions
- Comprehensive medical insurance for employees and their families
- Non-partner equity-based awards (for consulting managers and above)
- Structured and on-the-job learning and development opportunities
- Personalized opportunities including talent mobility, flexible work programs and externships to help you chart a unique career journey to pursue your own personal and professional goals

📌 AI Platform, Edge & Infrastructure Engineer (Bengaluru)
🏢 Kearney
📍 Bengaluru