Project Role : Custom Software Engineer
Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Must have skills : Python (Programming Language)
Good to have skills : NA
Minimum 2 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
Summary:
We are looking for a GenAI/Agentic AI Developer with 2–5 years of hands-on software development experience and practical experience building Generative AI and Agentic AI solutions. The role will focus on developing AI agents, agentic workflows and LLM-powered applications using Python and appropriate AI frameworks and platforms.
Roles & Responsibilities:
- Design, develop, test and maintain GenAI and Agentic AI solutions using Python and appropriate AI frameworks.
- Develop AI agents, agentic workflows and integrations with LLMs, APIs, enterprise applications, databases, knowledge bases and external tools.
- Design and optimize prompts, implement RAG and retrieval mechanisms, and experiment with models, tools and agentic approaches to improve solution quality.
- Implement testing, validation, error handling, logging and guardrails, troubleshoot AI-generated outputs, and collaborate with architects, developers, QA and business stakeholders.
Professional & Technical Skills
- Strong proficiency in Python with experience developing production-quality applications, APIs, reusable components, testing, debugging and performance optimization.
- Hands-on experience with GenAI/LLM application development, prompt engineering, context management, tokens, model parameters, embeddings and tool/function calling.
- Hands-on experience developing AI agents and agentic workflows using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, Amazon Bedrock Agents or equivalent.
- Good understanding of REST APIs, LLM integrations, RAG, embeddings, vector databases, semantic search and knowledge retrieval.
Additional Information:
- Exposure to MCP, multi-agent architectures, cloud GenAI services such as Amazon Bedrock/OpenAI/Anthropic/Azure OpenAI, AI evaluation, guardrails, Responsible AI and hallucination mitigation is preferred.
- Exposure to Docker, CI/CD, cloud deployment, vector databases and enterprise GenAI/Agentic AI use cases is desirable.
- Good understanding of Agile development practices and ability to document prompts, agent workflows, implementation approaches and technical decisions.
