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Mid-level, metro role with hot GenAI skills but niche tooling reduces applicant density.
Generative AI skills transfer across industries, but enterprise domain experience moderately matters.
Explicit 3–6 years plus mandatory LLM, LangChain, vector DB and Python experience.
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Design, develop, and deploy Generative AI solutions using Large Language Models (LLMs) including building AI agents and multi-agent workflows for enterprise applications.
Create, test, optimize prompts and integrate LLM APIs such as OpenAI, Anthropic Claude, Gemini, or open-source models for scalable AI solutions.
Collaborate with product, engineering, and business teams for end-to-end AI solution integration and implement responsible AI practices including guardrails and security.
3–6 years of experience building AI-powered applications leveraging LLMs and prompt engineering techniques.
Hands-on experience with Python programming, REST APIs, JSON handling, and API integrations.
Strong understanding of Generative AI concepts including LLMs, Prompt Engineering, Retrieval-Augmented Generation (RAG), AI Agents, and fine-tuning/model evaluation.
Bachelor’s degree in Computer Science, Engineering, AI, Data Science, or related field.
Experienced in designing AI agents and multi-agent workflows for enterprise-scale AI applications.
Skilled in using AI frameworks/tools like LangChain, LlamaIndex, Semantic Kernel, and familiar with cloud AI platforms such as Azure OpenAI, AWS Bedrock, Google Vertex AI.
Familiar with AI governance, compliance, responsible AI practices, and has exposure to vector databases and DevOps engineering practices for scalable AI deployments.