What are the responsibilities and job description for the Agentic AI Engineer / Developer position at NeuroNet Solutions Inc?
Job Summary
We are seeking an experienced Agentic AI Engineer / Developer to design, develop, and deploy next-generation AI-driven autonomous and semi-autonomous systems for enterprise applications. The ideal candidate should have strong expertise in Generative AI, LLMs, AI agents, orchestration frameworks, and scalable cloud-native architectures. The role involves building intelligent agentic workflows capable of reasoning, planning, tool usage, and workflow automation within a secure enterprise ecosystem.
Must Have Technical/Functional Skills
- Strong hands-on experience in Python programming
- Experience developing AI/ML and Generative AI solutions in enterprise environments
- Strong understanding of Large Language Models (LLMs) and prompt engineering
- Hands-on experience with agentic AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar
- Experience building AI agents with memory, reasoning, planning, and tool integration capabilities
- Strong experience with Retrieval-Augmented Generation (RAG) architectures
- Experience integrating vector databases such as Pinecone, Weaviate, ChromaDB, or FAISS
- Experience with OpenAI, Anthropic, Gemini, or other enterprise LLM APIs
- Strong understanding of REST APIs, microservices, and event-driven architectures
- Experience with FastAPI, Flask, or similar backend frameworks
- Knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform
- Experience with Docker, Kubernetes, and CI/CD pipelines
- Strong understanding of data structures, algorithms, and distributed systems
- Experience with SQL and NoSQL databases
- Familiarity with monitoring, observability, and logging tools
- Understanding of AI governance, responsible AI, and enterprise security standards
- Experience with Git, GitHub/GitLab, Jira, and Agile methodologies
Nice to Have Skills
- Experience in banking or financial services domain
- Knowledge of AI workflow orchestration and multi-agent collaboration systems
- Familiarity with MLOps and LLMOps practices
- Experience with GPU optimization and model fine-tuning
- Exposure to Neo4j or knowledge graph technologies
- Experience building conversational AI or intelligent automation platforms
Roles & Responsibilities
- Design and develop enterprise-grade Agentic AI applications and intelligent autonomous systems
- Build AI agents capable of reasoning, planning, memory management, and task orchestration
- Develop scalable RAG pipelines and integrate enterprise knowledge sources
- Collaborate with business and technology teams to identify AI-driven automation opportunities
- Integrate LLMs, APIs, databases, and external tools into agentic workflows
- Optimize AI model performance, latency, scalability, and cost efficiency
- Ensure AI applications follow enterprise security, governance, and compliance standards
- Develop reusable frameworks, accelerators, and best practices for AI engineering
- Participate in architecture discussions, code reviews, and technical mentoring
- Monitor, troubleshoot, and enhance production AI systems
- Work within Agile/Scrum teams to deliver high-quality AI solutions
Preferred Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field
- Strong analytical, communication, and problem-solving skills
- Ability to work in a fast-paced enterprise environment
- Passion for innovation, emerging AI technologies, and continuous learning
Salary : $70 - $100