
Full-Stack Developer
1 week ago
Experienced full-stack developer with 8+ years specializing in React frontend and Python/FastAPI backend, skilled in building scalable APIs and AI-powered solutions. Strong expertise in Generative AI, LangChain, vector databases, cloud services, and leading engineering teams to deliver enterprise-grade applications.
Responsibilities- Develop and maintain frontend applications using React with a focus on hooks, state management, and modular components.
- Design, build, and optimize backend APIs and microservices using Python and FastAPI.
- Integrate AI/ML models and LLM APIs into applications for enterprise-scale solutions.
- Implement and manage vector database solutions (Milvus, Pinecone, Weaviate) to support AI workflows.
- Ensure secure access and authentication using OAuth2, JWT, and other security best practices.
- Lead and mentor engineering teams, collaborating with clients to gather requirements and deliver technical solutions.
- Manage deployment workflows using AWS services (Lambda, API Gateway, S3, EC2, RDS) and containerization with Docker.
- Monitor and maintain MLOps pipelines, including model monitoring, retraining, and CI/CD for machine learning.
- Utilize infrastructure-as-code tools (Terraform/CDK) and observability tools (CloudWatch, Prometheus, Grafana) for production environments.
- 8+ years of full-stack development experience with React and Python/FastAPI.
- Deep knowledge of the React ecosystem: hooks, state management, and modular components.
- Proven experience building production-grade APIs and microservices.
- Strong expertise in LangChain, Generative AI, RAG pipelines, and prompt engineering.
- Hands-on experience with vector databases like Milvus, Pinecone, and Weaviate.
- Proficiency in integrating AI/ML models and LLM APIs.
- Solid experience with SQL databases (PostgreSQL, MySQL) and NoSQL databases (MongoDB, DynamoDB, Redis).
- Familiarity with AWS cloud services (Lambda, API Gateway, S3, EC2, RDS).
- Experience with containerization technologies such as Docker.
- Understanding of security best practices including OAuth2 and JWT.
- Excellent communication and client-facing consulting skills.
- Demonstrated leadership and team guidance capabilities.
- Experience with MLOps workflows and CI/CD for machine learning projects.
- Familiarity with Kubernetes, Terraform/CDK, and observability tools like CloudWatch, Prometheus, and Grafana.
- Experience delivering AI/ML solutions for enterprise clients across various industries.
- Strong understanding of advanced Generative AI techniques and enterprise LLM deployments.
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