Role Summary
We are seeking a highly skilled Agentic AI Developer with 5+ years of experience in deign, develop, and deploy intelligent AI solutions that drive business transformation and innovation. The ideal candidate will have strong expertise in Generative AI, Large Language Models (LLMs), AI agent frameworks, and modern software engineering practices. This role requires hands-on experience in building scalable, secure, and production-ready AI systems aligned with enterprise objectives.
Key Responsibilities
- Design, develop, and implement AI agents for enterprise business use cases.
- Build intelligent workflows leveraging LLMs, tools, APIs, memory management, and human-in-the-loop approval mechanisms.
- Develop Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge repositories and structured/unstructured data sources.
- Integrate AI solutions with enterprise applications, databases, APIs, and knowledge management systems.
- Create and maintain reusable prompts, tools, templates, and workflow components.
- Evaluate AI solutions for accuracy, reliability, safety, latency, scalability, and cost efficiency.
- Apply machine learning techniques and statistical methods where appropriate.
- Deploy, monitor, troubleshoot, and continuously optimize AI applications in production environments.
- Ensure compliance with security, privacy, governance, and Responsible AI standards.
- Collaborate closely with architects, developers, product owners, and business stakeholders to deliver innovative AI solutions.
- Contribute to AI solution architecture, technical design, and best practice frameworks.
Required Skills & Experience
Primary Skills
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field.
- 5+ years of experience in software development, AI solution design, or enterprise application development.
- Strong programming expertise in Python.
- Hands-on experience with Generative AI, Large Language Models (LLMs), and AI application development.
- Experience designing and building AI Agents, autonomous workflows, and multi-agent systems.
- Strong understanding of Retrieval-Augmented Generation (RAG) architectures.
- Experience with embeddings, vector databases, semantic search, and knowledge retrieval systems.
- Solid understanding of machine learning concepts, model evaluation, and statistical techniques.
- Experience working with REST APIs, databases, Git, testing frameworks, and CI/CD pipelines.
- Knowledge of cloud platforms such as Azure, AWS, or Google Cloud Platform.
- Experience with Docker, containerization, and enterprise integrations.
- Strong analytical, problem-solving, and troubleshooting skills.
- Excellent verbal and written communication skills.
Secondary Skills (Good to Have)
- Experience with AI orchestration frameworks such as:
- LangGraph
- LangChain
- Semantic Kernel
- AutoGen
- CrewAI
- Experience with workflow orchestration platforms such as Temporal.
- Knowledge of Model Context Protocol (MCP).
- Experience with AI observability, evaluation frameworks, guardrails, and responsible AI implementation.
- Familiarity with prompt engineering, agent memory management, and tool-calling architectures.
- Experience integrating AI solutions with enterprise platforms such as:
- SharePoint
- Jira
- ServiceNow
- Microsoft Teams
- SAP
- Knowledge of MLOps and AI deployment best practices.
- Experience working in telecom, manufacturing, automotive, or large-scale enterprise environments.
Nice to Have
- Microsoft Azure AI certifications or equivalent AI certifications.
- Experience with Fine-Tuning, Prompt Optimization, and AI Governance frameworks.
- Exposure to Knowledge Graphs and Graph-based RAG architectures.
- Experience with multi-modal AI applications involving text, image, and document intelligence.
- Contribution to open-source AI projects or communities.
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