Founding AI OPS Engineer (AIOps + DevOps + CloudOps )

About Us

We are a startup based in the US and have a registered office in India. We are building an industry-leading FinTech mobile app that brings hedge-fund-grade trading intelligence to everyday investors. Think Robinhood but powered by AI-driven insights, ultra-low-latency systems, and radically transparent user experiences. We need your investment of a minimum of 20 Hours per Week (Part-time), which offers significant equity returns, as you continue working while we secure funding and onboard you as a Full-time employee within the next 6–8 months. You’ll be a partner with our Data Scientist, AI engineers, quantitative research, frontend, and backend teams.

As part of our founding technical team, you will inherit, optimize, and implement the operational (Dev/Cloud Ops) foundation that powers our entire platform from AI model infrastructure and trading services to real-time observability and self-healing systems.

Role Overview

An AI-driven Cloud/DevOps Engineer (GitHub CI/CD + Cloud Provisioning/Operations) is a rare hybrid who combines deep knowledge of cloud infrastructure with AIOps principles. You will bridge Dev, Cloud-Ops, and use AI to automate, optimize, and proactively manage our complex, distributed FinTech environment, reducing manual toil and eliminating incidents before they reach production.

Experience

• Minimum 10 years of hands-on work experience in DevOps, CloudOps, AIOps, or a closely related engineering discipline.

Key Responsibilities

Cloud Operations (CloudOps)

• Provision and manage cloud resources on AWS and Azure using both portal-based workflows and Infrastructure as Code (IaC) via Terraform.
• Design and maintain cloud IAM policies in JSON and YAML for both AWS and Azure, ensuring least-privilege access controls.
• Architect scalable, cost-efficient cloud environments aligned with FinTech compliance and security requirements.

Development Operations (DevOps)

• Develop, manage, and optimize GitHub Actions workflows for CI/CD pipelines across all services.
• Implement and maintain container orchestration using Docker and Kubernetes (EKS) for reliable deployments.
• Manage deployment lifecycle, rollbacks, blue-green deployments, and feature flag strategies.

AIOps & Intelligent Monitoring

• Build ML-powered predictive alerting systems to identify anomalies and forecast incidents before they impact production.
• Integrate and administer AIOps platforms such as Splunk and Datadog into the existing IT infrastructure.
• Configure observability stacks using Prometheus and Grafana for real-time dashboards and SLO tracking.

Automated Incident Response

• Design and implement self-healing mechanisms and automated runbooks to resolve recurring IT issues without manual intervention.
• Develop intelligent playbooks that leverage AI to triage, categorize, and route incidents automatically.
• Define and own Mean Time to Resolution (MTTR) SLAs; continuously improve incident response workflows.

Log, Data & Root Cause Analysis

• Analyze high-volume logs, metrics, and distribute traces for root cause analysis (RCA) using ML-assisted tooling.
• Build pipelines that ingest operational telemetry into analytics platforms for continuous insight generation.
• Correlate signals across systems to surface hidden dependencies and failure patterns.

AI Model Lifecycle Management

• Maintain, scale, and monitor AI/ML models in production to ensure consistent performance and reliability.
• Implement model versioning, A/B deployment strategies, and automated rollback on degraded performance.
• Collaborate with ML engineers to operationalize new models with minimal downtime.

Essential Skills & Qualifications

Programming & Scripting

• High proficiency in Python — automation scripts, data pipelines, CLI tooling, and ML integrations.
• Proficiency in Bash/Shell scripting for system-level automation and operational tasks.
• Familiarity with YAML and JSON for configuration management and IAM policy authoring.

Cloud & Infrastructure

• Hands-on experience with AWS services: EC2, Lambda, S3, EKS, IAM, CloudWatch, VPC.
• Working knowledge of Microsoft Azure services and Azure IAM (RBAC, Managed Identities).
• Proficiency with Terraform for Infrastructure as Code across multi-cloud environments.
• Experience with Docker and Kubernetes for containerized workloads and microservices.

AIOps & Observability

• Experience with AIOps platforms: Splunk, Datadog, Dynatrace, or equivalent.
• Proficiency in Prometheus and Grafana for metrics collection, alerting, and dashboards.
• Familiarity with distributed tracing tools (Jaeger, OpenTelemetry) and log aggregation (ELK Stack).

AI / ML Knowledge

• Working understanding ML algorithms, anomaly detection techniques, and NLP.
• Exposure to Generative AI and Large Language Models (LLMs, GPT-based systems) in operational contexts.
• Ability to interpret model performance metrics and identify drift or degradation in production.

DevOps & CI/CD

• Proficiency with GitHub Actions for CI/CD pipeline development and management.
• Understanding of GitOps principles, branching strategies, and release management.
• Experience with secrets management tools (AWS Secrets Mana

Analytical & Debugging Skills

• Strong ability to debug complex, distributed systems at scale.
• Systematic approach to root cause analysis using data-driven methodologies.
• Comfortable operating in high-ambiguity, early-stage environments with shifting priorities.

Why Join Us?

• Founding equity stake: You will own a meaningful share of what we are building.
• Greenfield architecture, no legacy systems; design the stack from scratch, the right way.
• High-impact role at the intersection of AI and financial technology.
• Direct collaboration with founders; your decisions shape the product and company direction.
• A mission that democratizes institutional-grade trading intelligence for everyday investors.