Technical Lead

Job Summary

• 6+ years in software/AI engineering with hands-on DevOps/platform experience
• Build and deploy production AI multi-layered agents using Python

Key Responsibilities

· 6+ years in software/AI engineering with hands-on DevOps/platform experience

· Build and deploy production AI multi-layered agents using Python

· Python Expertise

Skill Requirements

· 6+ years in software/AI engineering with hands-on DevOps/platform experience

· Build and deploy production AI multi-layered agents using Python

· Python Expertise

· Strong proficiency in Python (6+ years) with a focus on building enterprise-grade backend APIs or data services.

· Experience with modern frameworks like FastAPI, Flask, or Django optimized for asynchronous execution.

· Understanding of data handling libraries (e.g., Pandas, SQLAlchemy, Pydantic) and integrating with GenAI/LLM frameworks (like LangChain, LlamaIndex, or native AI APIs) is a massive plus.

· DevOps & CI/CD

· Proven experience building and maintaining secure CI/CD pipelines using tools like GitHub Actions, GitLab CI, or Jenkins.

· Extensive experience with Infrastructure as Code (IaC) using Terraform or Ansible to manage multi-source cloud environments.

· Deep knowledge of cloud platforms (AWS, Azure, or GCP), specifically networking, security policies, and IAM management.

· Container Management & Orchestration

· Production-level expertise with Docker for containerising microservices and AI workloads.

· Deep hand-on experience managing and scaling Kubernetes (EKS, AKS, GKE, or OpenShift) clusters.

· Familiarity with Kubernetes constructs (Helm charts, ingress controllers, network policies, and cluster autoscaling).

· Data & Monitoring

· Comfortable interfacing with distributed data storage solutions (SQL, NoSQL, and Vector databases).

· Experience implementing comprehensive observability stacks (Prometheus, Grafana, ELK/PLG, Datadog) to monitor system and query performance

Other Requirements