Gen AI – Engineer
Job Description
At Iris, every role is more than a job — it’s a launchpad for growth.
Our Employee Value Proposition, “Build Your Future. Own Your Journey.” reflects our belief that people thrive when they have ownership of their career and the right opportunities to shape it.
We foster a culture where your potential is valued, your voice matters, and your work creates real impact. With cutting-edge projects, personalized career development, continuous learning and mentorship, we support you to grow and become your best — both personally and professionally.
Curious what it’s like to work at Iris? Head to this video for an inside look at the people, the passion, and the possibilities. Watch it here.
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Responsibilities
1. Generative AI Design & Development
a. Contribute to the design and implementation of GenAI-powered applications.
b. Translate functional requirements into efficient Python services.
c. Work with LLM orchestration frameworks (LangChain 1.0, LangGraph, OpenAI tools, custom agents).
d. Participate in PoCs and exploratory work for new GenAI capabilities.
2. Python & Cloud
a. Build and enhance RAG pipelines using embeddings, vector databases, and chunking strategies.
b. Implement basic Agentic workflows under guidance from senior team members.
c. Work with vector search systems (PGVector, FAISS, etc.).
d. Implement indexing, metadata tagging, and retrieval optimizations.
e. Exposure to MCP / tool-integration frameworks is an added advantage.
3. Collaboration
a. Participate in code reviews, design discussions, and documentation.
b. Follow best practices in coding standards, testing and DevOps
c. Collaborate with team.
Required Skills
• Strong hands-on proficiency in Python (Flask, REST, async programming).
• Practical experience with Generative AI and LLM-based applications.
• Good understanding of RAG system, embeddings, vector databases.
• Exposure to Agentic frameworks (LangChain 1.0, LangGraph, ReAct, OpenAI Assistants, or custom agents).
• Familiarity with AWS Cloud (ECS, S3, API Gateway, IAM, Bedrock).
• Experience with API development, microservices, containerization etc.
• Knowledge of CI/CD pipelines, Docker, GitLab/GitHub Actions.
Mandatory Competencies
Data Science and Machine Learning - Data Science and Machine Learning - Gen AI
Programming Language - Python - Flask
Beh - Communication
Cloud - AWS - AWS S3, S3 glacier, AWS EBS
Architecture - Architectural Patterns - Microservices
Cloud - AWS - Amazon API Gateway
DevOps/Configuration Mgmt - DevOps/Configuration Mgmt - GitLab,Github, Bitbucket
Development Tools and Management - Development Tools and Management - CI/CD
