Site Reliability Engineer by practice. AI-powered Builder by conviction. Systems Thinker by nature.
I'm an engineer with 8+ years on the front lines of enterprise production systems — where milliseconds matter, failures cost millions, and elegance under pressure separates good engineers from great ones.
My work sits at the intersection of SRE, intelligent automation, and AI-augmented engineering. I've spent years debugging what others couldn't, automating what others accepted as manual, and building resilience into systems at scale — across banking, financial markets, and enterprise IT infrastructure.
Today, I'm channeling that operational depth into building AI-driven tools, automation pipelines, and open-source projects that solve real, gnarly, production-grade problems.
🔥 Mission: Bridge reliability engineering with AI to build systems that scale and self-heal
🎯 Superpower: Turning production chaos into structured, automated, observable engineering
🌱 Growth: Cloud-native SRE | LLM integration | Open-source tooling
🤝 Open to: Remote SRE/SWE roles | Startup engineering | OSS collaboration
🏦 Bank of America — Production Support Specialist | 3+ years
Domain: Capital Markets | Financial Systems | Regulatory Operations
- 🔍 Real-time monitoring of critical trading and capital markets systems using ITRS Geneos
- 🚨 Led incident management for high-severity production failures with zero-downtime recovery focus
- ⚙️ Built and maintained shell automation scripts to reduce manual operational overhead
- 📊 Collaborated with engineering teams to define alerting thresholds, runbooks, and escalation playbooks
- 🏛️ Ensured regulatory compliance in IT surveillance operations across financial infrastructure
🏢 Infosys — Technology Analyst | 4 years
Domain: Enterprise IT | Application Operations | Process Automation
- 🛠️ Managed end-to-end production support for enterprise-grade applications
- 🔄 Automated repetitive operational tasks via shell scripting and Python, reducing toil by significant margins
- 📋 Established ITIL-aligned incident, problem, and change management workflows
- 🤝 Partnered with development teams to accelerate root cause analysis and implement permanent fixes
⚡ Ducen — Associate Software Engineer | 4 months
- Delivered fast-paced production support in a lean, startup-oriented environment
- Demonstrated adaptability across varied infrastructure stacks and tight SLAs
current_focus = {
"learning": ["AWS Solutions Architect", "Go (Golang)", "Kubernetes basics"],
"building": ["AI-powered ops tools", "Production observability frameworks"],
"exploring": ["LLM integration in DevOps", "RAG pipelines", "MCP architecture"],
"goal": "Land a remote SRE / Software Engineer role in fintech or AI-first companies",
}- 🧩 Cloud-Native SRE — transitioning production expertise into scalable, cloud-native reliability patterns
- 🤖 AI-Augmented Engineering — using LLMs to accelerate debugging, incident triage, and code generation
- 🌐 Open Source — building tools that reflect real production pain points, not toy projects
"The best SRE is one who automates themselves out of repetitive work — and uses that time to build something remarkable."
I treat AI as an engineering multiplier, not a replacement. My approach:
| Layer | What I Do |
|---|---|
| 🔍 Observe | Build intelligent alerting that understands context, not just thresholds |
| 🧠 Analyze | Use LLMs to triage incidents, correlate logs, and surface root causes faster |
| ⚙️ Automate | Script away toil — from job failure recovery to environment health checks |
| 🚀 Ship | Leverage AI coding assistants to prototype and validate solutions in hours, not days |
| 📖 Learn | Continuously integrate AI tooling into daily engineering workflows |
I believe the most impactful open-source projects aren't built from scratch ideas —
they're built from real frustrations, real failures, and real production war stories.
My OSS focus areas:
- 🛡️ Reliability tooling — scripts, frameworks, and dashboards for production observability
- 🔁 Automation libraries — reusable ops automation for Linux/cloud environments
- 🤖 AI-ops integrations — LLM-powered incident responders, log analyzers, and runbook generators
- 📊 FinTech monitoring — domain-specific tools for capital markets and financial system health
If it caused a 3am incident, it deserves an open-source fix.
Blockchain isn't just hype to me — it's a paradigm shift in trust, transparency, and system design.
- 📘 Foundational knowledge in distributed ledger concepts, consensus mechanisms, and smart contracts
- 🔎 Exploring intersections between blockchain auditability and enterprise compliance/regulatory ops
- 🧪 Curious about DeFi infrastructure reliability and the unique SRE challenges it introduces
Projects I'm building (or planning to build) — aligned with my background:
| Project | Description | Stack |
|---|---|---|
| 🚨 IncidentIQ | AI-powered incident triage bot — paste your logs, get root cause hypotheses | Python, LangChain, Claude API |
| 📋 RunbookGen | Auto-generate runbooks from historical incident tickets using LLMs | Python, OpenAI, Markdown |
| 📡 SRE Dashboard | Lightweight personal SRE metrics dashboard for Linux servers | Shell, Prometheus, Grafana |
| 🔄 AutoHealer | Self-healing script framework for common production failure patterns | Python, Shell, Cron |
| 🧾 LogLens | CLI tool to scan, pattern-match, and summarize large log files intelligently | Python, Click, regex |
| Channel | Link |
|---|---|
| linkedin.com/in/ajith-kumar-mohan/ | |
| ajithkumar.mohan96@gmail.com | |
| 🐦 Twitter / X | @YOUR_HANDLE |
| 🌐 Portfolio | your-portfolio.dev |
Open to: Remote SRE roles · Software Engineering opportunities · Fintech/AI startups · OSS collaboration
"Systems fail. Engineers learn. Automation scales. AI accelerates. Keep building."