GenAI Engineer

Key Responsibilities :

- Design and implement GenAI solutions using cutting-edge frameworks (e.g., Transformers, LangChain, LangGraph, AWS Bedrock, Agentcore).

- Develop scalable and modular Python applications for deploying generative AI solutions.

- Build and manage cloud infrastructure using AWS services (S3, Lambda, DynamoDB, ECS, EKS).

- Collaborate with data scientists, ML engineers, and product teams to integrate AI models into domain-specific applications.

- Ensure production-grade scalability, reliability, and security of GenAI systems.

- Monitor and optimize system performance using tools like AWS CloudWatch.

- Stay updated with advancements in GenAI, cloud computing, MLOps, and DevOps.

- Contribute to code reviews, documentation, and Python development best practices.

Required Skills :

- Strong Python proficiency with experience in FastAPI, asyncio, modular application design, and parallel processing.

- Familiarity with Python parallel processing modules such as multiprocessing, concurrent.futures, and dask for efficient parallel and distributed computing.

- Hands-on experience with GenAI frameworks such as LangChain, LangGraph, and Prompt Engineering.

- Proficient in AWS cloud services and cloud-native architecture.

- Familiar with CI/CD pipelines, Docker, and Kubernetes.

- Familiarity with code quality tools such as pylint, black, isort, mypy, pytest, SonarQube, SonarLint, and Black Duck for linting, formatting, testing, static analysis, and open-source security compliance.

- Solid understanding of security best practices in cloud and AI deployments.

- Excellent analytical and communication skills.

- Should be able to network within GenAI team and with other teams as enablement tribe.

(ref:hirist.tech)