Technical Lead Backend

Key Responsibilities

Technical Leadership

• Lead and mentor a cross-functional engineering team (57 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:
• Performance optimization
• Security
• Testing (unit/integration)
• Observability (logging, metrics, tracing.

Cloud & DevOps (Azure)

• Architect and deploy cloud-native solutions using:
• Compute: Azure App Services, Container Apps, AKS, Azure Functions
• Data: Azure SQL, Cosmos DB, Storage Accounts
• Monitoring: Application Insights, Log Analytics
• Build and manage CI/CD pipelines using Azure DevOps
• Implement Infrastructure-as-Code using Terraform (preferred) or Bicep
• Ensure:
• High availability and fault tolerance
• Monitoring, alerting, and observability
• Cost optimization and governance

Client & Stakeholder Management

• 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:
• Azure OpenAI / OpenAI APIs
• 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 & Soft Skills

• 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 & Qualifications

• 812 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:
• Microservices and distributed systems
• Docker and Kubernetes (ACA and AKS)
• Proven experience with:
• CI/CD pipelines (Azure DevOps)
• Infrastructure as Code (Terraform preferred)
• Demonstrated leadership experience in mentoring teams and driving delivery .