Backend Engineer
TechDoQuest
Job Description
Build the Future of Enterprise AI
TechDoQuest is looking for passionate Backend Engineers to join a high-impact engineering team building a next-generation AI-native enterprise platform on AWS.
If you're excited about designing scalable event-driven systems, building AI-powered applications, and working with modern cloud technologies, we'd love to hear from you.
We are hiring across multiple experience levels:
- Backend Engineer (4–6 years)
- Senior Backend Engineer (7–9 years)
- Engineering Lead (10+ years)
What You'll Be Working On
You'll help build an AI-first platform that combines intelligent agents, event-driven microservices, cloud-native architecture, and human oversight to automate complex enterprise workflows.
Depending on your experience level, you'll contribute to:
- Designing and building Python/FastAPI microservices
- Developing event-driven applications using AWS services
- Integrating Large Language Models (LLMs) and AI Agents into production systems
- Designing prompts, structured outputs, tool/function calling, and AI workflows
- Building resilient, scalable backend services with observability and fault tolerance
- Creating APIs, event contracts, and reusable platform components
- Designing evaluation frameworks for AI agents and prompt improvements
- Writing automated unit, integration, and end-to-end tests
- Collaborating with architects, product teams, DevOps, and data engineers
- Mentoring engineers and driving engineering best practices (Senior & Lead)
- Leading architecture, platform standards, and technical delivery (Engineering Lead)
What We're Looking For
Required Skills
- 4+ years of backend software engineering experience (role based on experience)
- Strong Python development experience
- FastAPI or similar modern backend framework
- REST API and Microservices architecture
- Event-driven systems and asynchronous programming
- AWS Cloud (Lambda, EventBridge, ECS/Fargate, API Gateway, IAM)
- PostgreSQL and NoSQL databases
- Docker and Git-based development workflows
- Automated testing and CI/CD pipelines
AI Experience
We're looking for engineers who have practical experience building with modern AI technologies, including:
- LLM integration
- AI Agents
- Prompt Engineering
- Structured Outputs
- Function/Tool Calling
- Retrieval Augmented Generation (RAG)
- AI Evaluation & Guardrails
Experience with tools such as Claude Code, Cursor, GitHub Copilot, Windsurf, or similar AI-assisted engineering platforms is highly valued.
Nice to Have
- Event streaming technologies
- Infrastructure as Code (Pulumi, Terraform, CloudFormation)
- Healthcare, Insurance or Enterprise SaaS domain experience
- React / TypeScript exposure
- Performance optimization and distributed systems
- AI evaluation frameworks such as LangSmith or PromptFlow
Technology Stack
Languages: Python, SQL, TypeScript
Backend: FastAPI, Async Python, REST APIs
Cloud: AWS (Lambda, ECS/Fargate, EventBridge, API Gateway, RDS, DynamoDB)
AI: LLMs, AI Agents, Prompt Engineering, RAG, Tool Calling
Databases: PostgreSQL, DynamoDB, Redis
DevOps: GitHub Actions, Azure DevOps, Docker
Observability: CloudWatch, Structured Logging
Why Join Us?
- Build real-world AI products that solve complex business challenges
- Work with modern cloud-native architecture and event-driven systems
- Collaborate with experienced architects and engineering leaders
- Be part of an AI-first engineering culture
- Learn, innovate, and grow with cutting-edge technologies
- Competitive compensation and long-term career growth
Interested?
Send your resume along with your GitHub profile, portfolio, or any projects that showcase your work in backend engineering, cloud architecture, or AI application development.
If you're passionate about building scalable systems and applying AI in production, we'd love to hear from you.
Required Skills
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