Role Description
Job Title: Technical Lead – Backend (Python / FastAPI / Azure) About the Role We are looking for a highly skilled Technical Lead to build and scale cloud-native backend systems on Azure. This role combines hands-on engineering, technical leadership, and innovation in Generative AI to deliver high-impact solutions for global clients. The ideal candidate is a proactive leader who can balance deep technical expertise with team leadership, drive architectural decisions, and ensure high-quality delivery while collaborating with internal and external stakeholders.
Key Responsibilities Technical Leadership
- Lead and mentor a cross-functional engineering team (5–7 engineers), ensuring high standards in code quality and delivery
- Own backend architecture, system design, and engineering roadmap
- Drive end-to-end design, development, and deployment of scalable systems
- Conduct code reviews, enforce best practices, and resolve complex technical challenges
- Drive internal R&D initiatives in GenAI, automation, and scalable cloud solutions Backend Engineering
- Design and build high-performance, scalable, and secure REST APIs using FastAPI
- Develop microservices and distributed systems with fault tolerance and resiliency
- Optimize systems for latency, scalability, and reliability
- Implement best practices for: o Performance optimization o Security o Testing (unit/integration) o Observability (logging, metrics, tracing) Cloud &
Architect and deploy cloud-native solutions using: o Compute: Azure App Services, Container Apps, AKS, Azure Functions o Data: Azure SQL, Cosmos DB, Storage Accounts o Monitoring: Application Insights, Log Analytics
Build and manage CI/CD pipelines using Azure DevOps
Implement Infrastructure-as-Code using Terraform (preferred) or Bicep
Ensure: o High availability and fault tolerance o Monitoring, ing, and observability o Cost optimization and governance Client &
Act as the primary technical point of contact for internal clients
Lead technical discussions, solution design workshops, and architecture reviews
Translate business requirements into scalable technical solutions
Communicate risks, trade-offs, and progress effectively
Present technical concepts clearly to both technical and non-technical stakeholders Generative AI (Preferred)
Design and implement RAG-based architecture and LLM-powered services
Work with: o Azure OpenAI / OpenAI APIs o Vector databases (e.g., Azure AI Search)
Build production-grade GenAI applications focusing on scalability, latency, and security
Evaluate and integrate emerging AI technologies into client solutions Leadership &
Communication: Clearly explains technical decisions, trade-offs, and risks; leads client discussions confidently
Team Leadership: Mentors engineers, provides actionable feedback, and maintains high engineering standards
Ownership: Takes end-to-end responsibility for delivery, production issues, and system quality
Decision-Making: Makes sound technical decisions under ambiguity, balancing short-term needs and long-term design
Execution: Drives predictable delivery, proactively manages risks, and ensures high-quality outcomes
Collaboration: Works effectively across engineering, product, and business teams
Adaptability: Quickly learns, adopts new technologies (especially GenAI), and drives continuous improvement Required Skills &
8–12 years in core software development, distributed systems, or large-scale platform engineering - including strong Python and Nodejs expertise.
4-5 years building, deploying, and scaling machine learning models, LLMs, or agentic workflows into live production.
Deep experience with FastAPI (or similar modern frameworks)
Hands-on experience with Azure cloud architecture and operations
Strong knowledge of: o Microservices and distributed systems o Docker and Kubernetes (ACA and AKS)
Proven experience with: o CI/CD pipelines (Azure DevOps) o Infrastructure as Code (Terraform preferred)
Demonstrated leadership experience in mentoring teams and driving delivery Preferred Skills
Experience with Azure AI foundry, Databricks, or big data pipelines
Knowledge of event-driven systems (Azure Service Bus, Azure Data Factory)
Familiarity with API gateways and service mesh
Understanding of cloud security, IAM, and governance
Skills
CI/CD, Agentic AI, Azure DevOps, LLMs, Kubernetes, Docker, Generative AI
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