What are the responsibilities and job description for the GenAI & Agentic AI Developer position at Arkhya Tech. Inc.?
Role Overview
We are looking for a hands-on AI Engineer with strong practical experience in Python, TypeScript, LLMs, Agentic AI, and RAG-based applications. The ideal candidate should have experience designing, developing, and deploying enterprise-grade AI solutions and be comfortable working across the complete AI application lifecycle, from development to production deployment.
Key Responsibilities
- Design and develop AI-powered applications using LLMs, Agentic AI frameworks, and RAG architectures.
- Build and deploy enterprise AI solutions for business use cases.
- Develop backend services and AI workflows using Python and TypeScript.
- Implement multi-agent workflows, orchestration patterns, and tool integrations.
- Create and optimize RAG pipelines, including document ingestion, vector databases, retrieval strategies, and prompt engineering.
- Evaluate LLM performance and implement monitoring, testing, and quality assessment frameworks.
- Build and maintain CI/CD pipelines using GitHub Actions.
- Support automated deployment, model lifecycle management, and production operations.
- Collaborate with architects, product owners, and business stakeholders to translate requirements into scalable AI solutions.
- Follow software engineering best practices, including code reviews, testing, security, and documentation.
Mandatory Skills
- Strong hands-on experience in Python development.
- Good experience with TypeScript and modern application development.
- Practical experience with LLMs, prompt engineering, and AI application development.
- Hands-on knowledge of Agentic AI, multi-agent systems, and workflow orchestration.
- Experience building RAG (Retrieval-Augmented Generation) solutions.
- Strong understanding of GitHub Actions, CI/CD pipelines, and deployment automation.
- Experience with REST APIs, microservices, and enterprise application integration.
- Knowledge of LLM evaluation, testing, monitoring, and optimization techniques.
Preferred Skills
- Experience with frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar.
- Exposure to vector databases such as Pinecone, Weaviate, FAISS, ChromaDB, or Azure AI Search.
- Experience with cloud platforms (AWS, Azure, or GCP).
- Understanding of MLOps concepts and AI solution deployment.
- Knowledge of containerization technologies such as Docker and Kubernetes.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, or related field.
- Excellent communication and stakeholder management skills.
- Ability to work independently and collaboratively in agile teams.
- Strong problem-solving and analytical mindset.
Nice to Have
- Experience with enterprise AI platforms and production AI deployments.
- Exposure to Responsible AI, AI governance, and security best practices.
- Experience with monitoring and observability tools for AI applications.