Principal consultant - AI/ML engineer

Inviting applications for the role of Principal consultant - AI/ML engineer

In this role, you will be responsible for supporting the network operations 24X7 for internal IT. You will be working actively on the operational issues along with internal / external stakeholders to recover the systems failure (proactive/reactive).

You will work Incident Management, Problem Management for each incidents/tickets and need to ensure the high uptime to the business.

Your role will network L2+ and need to work on various current/upcoming technologies (explained below) to support business needs.

Responsibilities

The candidate should be holding good experience of hardcore 24X7 network Ops experience

Candidate will work at the intersection of AI engineering, infrastructure automation, and platform engineering, enabling autonomous decision-making across Compliance, Multi-Cloud, Network DevOps, EUC, and Identity Management.

1. Agentic AI & Automation Development

• Design and implement agent-based AI systems for infrastructure operations (planning, reasoning, execution loops)

• Build autonomous remediation workflows for incidents, alerts, and service degradation (HITL, HOTL, HOOTL)

• Develop multi-agent orchestration frameworks for cross-domain infrastructure coordination

• Integrate LLMs with enterprise systems for context-aware decision-making

2. Infrastructure Automation (Domain-Specific)

• Continuously monitor policy adherence, detect drift, and enable automated remediation of compliance violations.

• Orchestrate MACD, optimization, and cost governance across AWS, Azure, and GCP using IaC and AI agents.

• Automate provisioning, validation, and AI-driven troubleshooting across hybrid networks using telemetry and APIs.

• Build self-healing automation for endpoint performance, application issues, and device lifecycle management.

• Automate access provisioning, enforce policies, and detect/respond to identity anomalies.

3. AI/ML & LLM Engineering

• Develop and fine-tune LLM-powered agents using frameworks like CrewAI, Langchain

• Build context-aware reasoning systems using telemetry, logs, and configuration data

• Ensure guardrails, explainability, and human-in-the-loop (HITL) controls

4. Observability & Telemetry Integration

• Integrate with observability platforms

• Correlate logs, metrics, traces for AI-driven insights and decisioning

• Build real-time telemetry pipelines for agent consumption

5. Platform & Engineering Integration

• Embed agents into CI/CD pipelines, ITSM workflows, and platform engineering stacks

• Integrate with ServiceNow, GitOps workflows

• Develop reusable automation modules and APIs

6. Governance, Safety & Reliability

• Implement AI safety, compliance, and governance frameworks

• Define levels of autonomy (HITL, HOTL, HOOTL)

• Ensure auditability and traceability of agent actions

Core Technical Skills

• Strong programming: Python (mandatory), plus PowerShell / JavaScript

• Experience with AI/LLM frameworks (CrewAI, Langchain)

• Hands-on with REST APIs, microservices, and event-driven architectures

• CI/CD pipelines (GitHub Actions, Azure DevOps)

Infrastructure & Automation

• Deep knowledge in at least 2 domains:

• Network (SD-WAN, routing, firewalls, proxies)

• EUC / Desktop Engineering

• Cloud (AWS / Azure / GCP)

AI Engineering

• Experience with:

• LLMs, RAG pipelines, embeddings, vector DBs

• Prompt engineering and agent orchestration

• Understanding of:

• Autonomous systems design patterns

• Planning, reasoning, and tool-use agents

Observability & Data

• Familiarity with:

• Logging, monitoring, tracing systems

• Data pipelines (Kafka, Kinesis)

Qualifications we seek in you!

Minimum Qualifications

• Experience building agentic AI systems for IT operations (AIOps)

• Exposure to FinOps, SecOps, or compliance automation

• Knowledge of Zero Trust architecture

• Certifications in cloud (AWS/Azure/GCP) or networking (Cisco, Palo Alto)

• Experience in large-scale enterprise environments

Preferred Qualifications/ Skills

• Systems thinking across infrastructure layers

• Strong problem-solving and debugging skills

• Ability to design autonomous, resilient systems

• Collaboration with cross-functional teams (Infra, Security, DevOps, AI)

• Experience with on-prem / edge AI deployments

• Knowledge of graph-based reasoning (knowledge graphs) for infra mapping