# AIOps Platform Engineer Senior Associate Director, Software Engineering

**Company**: GCIO
**Location**: Hyderabad, Telangana, India
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Finance

**Apply**: https://portal.careers.hsbc.com/careers/job/563774612526709?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_9428901d-ce7

## Description

We are seeking an experienced Senior AIOps Engineer to design, build, and operate the autonomous agents that turn observability data into safe, closed-loop operational action.

You will sit at the intersection of service observability and agentic AI: connecting agents to metrics, logs, traces, events, change data, and service topology so they can detect, diagnose, and remediate production issues with minimal human intervention.

In this role, you will:

- Design and build autonomous AIOps agents (LLM-based and multi-agent) that run the full operational loop , observe, correlate, diagnose, decide, act, and verify , across incident triage, root-cause analysis, and auto-remediation

- Connect agents to the observability estate (OpenTelemetry, Grafana, Tempo/Jaeger, APM, CMDB, change and deployment events) through well-defined tools/APIs and MCP servers, giving agents real-time, topology-aware context to reason over

- Turn observability signals into autonomous action: build event-driven triggers on SLO burn-rate, anomaly, and correlated alert patterns that launch agent workflows such as rollback, restart, scale-out, failover, traffic shift, config fix, or ticket enrichment

- Build the agent action layer: convert runbooks into machine-executable, idempotent actions (runbook-as-code), with pre-checks, blast-radius limits, dry-run modes, automatic rollback, and post-action health verification against SLIs

- Implement guardrails and human-in-the-loop controls: risk-tiered autonomy levels, policy-as-code, approval gates for high-risk changes, full audit trails, and explainable reasoning for every decision an agent makes

- Apply AI to observability data: anomaly detection, forecasting, alert noise reduction, event correlation, and retrieval-augmented reasoning over past incidents, runbooks, and post-mortems to speed up RCA and cut MTTD/MTTR

- Build evaluation and observability for the agents themselves: trace agent reasoning and tool calls, measure accuracy, action success rate, false-action rate, latency, and cost; run replay/simulation and chaos tests before increasing autonomy in production

- Partner with SRE, platform, and application teams to onboard services to autonomous operations, set standards and reusable patterns, and coach engineers on using AI + observability to automate their own operational workflows

To be successful in this role, you should meet the following requirements:

- 10+ years overall experience with 5+ years in SRE, AIOps, observability, or platform engineering.

- Proven hands-on development of autonomous agents using frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, or equivalent; strong grasp of tool/function calling, MCP, planning, memory, and multi-agent orchestration

- Deep service observability expertise: OpenTelemetry, Grafana, Jaeger/Tempo, or enterprise APM (Splunk, AppDynamics); strong PromQL/LogQL/SQL and SLO/SLI/error-budget design

- Track record of delivering closed-loop auto-remediation in production that measurably reduced MTTR, alert noise, or manual toil, with clear safety controls and rollback

- Strong Python (Go a plus) with experience building event-driven services and integrations across Kubernetes, CI/CD, ITSM (ServiceNow), and automation tools.

- Practical knowledge of applied ML and LLM techniques for operations: anomaly detection, time-series forecasting, event correlation, RAG, prompt engineering, and evaluation of LLM outputs

- Understanding of responsible and secure AI in regulated environments: least-privilege agent access, PII redaction, auditability, model risk management, and change-control compliance

- Demonstrated technical leadership, with experience mentoring and leading engineers, setting engineering direction, reviewing designs, and developing team capability while influencing risk partners and senior stakeholders

## Skills

### Required
- Python
- Go
- LangGraph
- LangChain
- CrewAI
- AutoGen
- Semantic Kernel
- OpenTelemetry
- Grafana
- Jaeger/Tempo
- PromQL/LogQL/SQL
- Kubernetes
- CI/CD
- ITSM
- ServiceNow
- anomaly detection
- time-series forecasting
- event correlation
- RAG
- prompt engineering

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Source: [Apply at portal.careers.hsbc.com](https://portal.careers.hsbc.com/careers/job/563774612526709?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)