Key Responsibilities:
- Design and prototype AI agents using LangChain or similar frameworks.
- Apply LLMs to real-world tasks through prompt engineering, chaining, and tool integration.
- Develop Python-based pipelines and backend services to support agentic logic and orchestration.
- Integrate external APIs and SDKs to extend agent capabilities and data access.
- Collaborate on the development of planning, memory, and decision-making components within agents.
- Support experimental design, model evaluation, and iterative tuning of LLM-based workflows.
- Contribute to basic CI/CD workflows to ensure reliable model deployment and testing.
- Partner with engineering and product teams to translate business problems into scalable AI solutions.
Required Qualifications:
- 5+ years of experience in data science or applied machine learning, with a focus on NLP or AI applications.
- Hands-on experience with LLMs and orchestration tools such as LangChain, Haystack, or similar.
- Strong Python programming skills and familiarity with building modular, production-ready code.
- Experience working with LLM APIs (OpenAI, Anthropic, etc.) and retrieval-augmented generation workflows.
- Proven track record of designing and integrating APIs and third-party SDKs.
- Familiarity with agent-based systems and autonomous workflows.
- Working knowledge of CI/CD pipelines and MLOps fundamentals.
Preferred Qualifications:
- Experience with vector databases, tool use in agents, or multi-agent systems.
- Background in developing AI solutions in enterprise or research environments.
- Strong analytical thinking and ability to translate abstract problems into data-driven agentic solutions.