Python Developer – Generative AI & AWS
Summary
Trackmind is hiring a Python Developer in Hyderabad to design, build, and maintain scalable enterprise applications, integrate AI/ML-based solutions, and develop REST APIs while following enterprise security and operational standards. Core stack: Python (Django/Flask/FastAPI), SQL databases, REST, with exposure to GenAI/LLMs and cloud.
We are looking for an experienced Python Developer with strong expertise in AWS, Generative AI, LLMs, and Microservices Architecture. The ideal candidate should have hands-on experience developing scalable Python applications, integrating AWS services, and building AI-powered solutions using Large Language Models such as GPT and Cohere.
The role involves developing scalable backend services, implementing LLM-based applications and RAG solutions, building document-processing pipelines, and supporting automated CI/CD deployments in a cloud environment.
Key Responsibilities:
- Design, develop, test, and maintain scalable backend applications and REST APIs using Python.
- Integrate Python applications with AWS services including Lambda, S3, API Gateway, ECS, EKS, EC2, DynamoDB, RDS, SQS, SNS, CloudWatch, and IAM.
- Develop AI-powered applications using LLMs such as GPT and Cohere.
- Build and optimize prompt workflows, embeddings, semantic search, and Retrieval-Augmented Generation (RAG) solutions.
- Implement document-processing pipelines using chunking, segmentation, tokenization, and metadata enrichment techniques.
- Design and optimize different document chunking strategies, including fixed-size, recursive, semantic, and context-aware chunking, based on data type and use case.
- Develop and maintain RESTful APIs and event-driven microservices.
- Design scalable and reliable backend services using microservices architecture.
- Package and deploy applications using Docker and container orchestration platforms such as ECS/EKS where applicable.
- Develop and maintain CI/CD pipelines for automated testing, deployment, and release management.
- Monitor application performance and troubleshoot production issues to improve reliability, scalability, and performance.
- Follow secure coding practices and AWS best practices for IAM, access control, logging, monitoring, and application security.
- Write and maintain unit, integration, and end-to-end tests.
- Collaborate with AI/ML engineers, Data Scientists, DevOps teams, Product Managers, and other stakeholders.
- Prepare and maintain clear technical documentation, API documentation, and architecture details.
Required Skills
- Strong hands-on experience with Python.
- Good knowledge of OOP, data structures, and backend development.
- Strong experience developing REST APIs and microservices.
- Hands-on experience with AWS cloud services.
- Experience with Generative AI, LLMs, GPT, Cohere, embeddings, and RAG.
- Strong understanding of prompt engineering and LLM integration.
- Experience with document processing, chunking, segmentation, tokenization, and semantic search.
- Experience with Docker and CI/CD pipelines.
- Good understanding of cloud security, IAM, monitoring, and logging.
- Experience with SQL and relational databases, preferably PostgreSQL.
Good to Have
- Working knowledge of React.js.
- Working knowledge of Angular.
- Experience with PostgreSQL and database optimization.
- Experience with vector databases such as Pinecone, Qdrant, Weaviate, or similar.
- Experience with LangChain, LangGraph, or similar GenAI frameworks.
- Knowledge of Kubernetes and cloud-native application development.
- Experience with event-driven architectures using SQS, SNS, Kafka, or similar messaging platforms.
Preferred Candidate Profile
- Strong problem-solving and analytical skills.
- Good understanding of enterprise application development.
- Ability to work independently as well as collaborate with cross-functional teams.
- Good communication skills.
- Willingness to learn and work with emerging AI technologies.
Skills
- AI
- Angular
- API
- Api Documentation
- AWS
- CI/CD
- Cloud
- Cloud Native
- Cloud Security
- CloudWatch
- Cohere
- DevOps
- Docker
- DynamoDB
- EC2
- ECS
- EKS
- Embeddings
- Event Driven Architecture
- Generative AI
- IAM
- Kafka
- Kubernetes
- Lambda
- LangChain
- LangGraph
- LLM
- Machine Learning
- Microservices
- OOP
- Pinecone
- PostgreSQL
- Prompt Engineering
- Python
- Qdrant
- RAG
- RDS
- React
- REST
- S3
- Secure Coding
- Semantic Search
- SNS
- SQL
- SQS
- Test Automation
- Vector Databases
- Weaviate
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