Gen AI Fullstack Developer

Required Skills & Experience

• 1-6 years of professional full-stack engineering experience.
• Bachelor's degree in Computer Science, Engineering, or related technical field (BE/BTech/MCA)
• Strong

  Python

  development skills, particularly with F

  astAPI, Flask, or Django.

• Experience with data processing using

  Pandas.

• Proficient in

  JavaScript/TypeScript

  with at least one modern frontend framework

  (React, Angular).

• Solid understanding of RESTful and GraphQL API design.
• Experience with at least

  one cloud

  platform:

• Azure:

  Functions, App Service, AI Search, Service Bus, AI Foundry

• AWS:

  Lambda, S3, SageMaker, EC2
• Hands-on experience building GenAI applications using RAG and agent frameworks.
• Database proficiency with:
• Relational databases: PostgreSQL, SQL Server
• NoSQL databases: MongoDB, DynamoDB
• Vector stores for embedding retrieval
• Familiarity with LLM orchestration tools: LangChain, AutoGen, LangGraph, Crew AI, A2A, MCP
• Understanding of Responsible AI practices and working knowledge of LLM providers (OpenAI, Anthropic, Google PaLM, AWS Bedrock)

Good to Have Skills

• DevOps & Infrastructure: Terraform, Kubernetes, Docker, Jenkins
• MLOps capabilities: model versioning, inference monitoring, automated retraining
• Security experience with OpenID Connect, OAuth2, JWT
• Deep experience with data platforms: Databricks, Microsoft Fabric
• Prior experience in AI/ML R&D or working within cross-functional product teams

Soft Skills & Team Expectations

• Effective communication and documentation skills; ability to clearly articulate technical concepts to both technical and non-technical audiences.
• Demonstrated ability to work independently as well as collaboratively in a fast-paced environment.
• A builder's mindset with a powerful desire to innovate, automate, and scale.
• Comfortable in an agile, iterative development environment.
• Willingness to mentor junior engineers and contribute to team knowledge growth.
• Proactive in identifying tech stack improvements, security enhancements, and performance bottlenecks.