Expert - Agentic Development & Automation

Key Responsibilities

• Agentic AI Development • Design and develop AI agents and multi-agent systems for enterprise use cases. • Build AI assistants, copilots, and workflow automation solutions. • Implement agent orchestration, planning, memory, reasoning, and tool integration capabilities. • Develop reusable agent frameworks, skills, and components.
• GenAI & LLM Engineering • Design and implement RAG-based solutions using enterprise knowledge sources. • Integrate and optimize LLMs for business applications. • Perform prompt engineering, evaluation, and performance optimization.
• Enterprise Integration & Deployment • Integrate AI agents with enterprise applications, APIs, databases, and cloud platforms. • Collaborate with MLOps teams for deployment, monitoring, and scaling of AI solutions. • Ensure security, governance, and responsible AI practices.
• Technical Leadership • Mentor engineers and share best practices in Agentic AI development. • Support architecture reviews, technology evaluations, and innovation initiatives. • Contribute to AI standards, frameworks, and reusable assets.
• Experience • 8+ years of software engineering experience. • 3+ years of hands-on experience in Generative AI/LLM-based applications. • Proven experience delivering AI solutions in production environments.
• Technical Skills • Agentic AI frameworks: LangGraph, LangChain, CrewAI, AutoGen, , OpenAI Agents SDK. • LLMs, Prompt Engineering, RAG architectures, and Vector Databases. • Strong Python programming and API development skills. • Cloud platforms (Azure, AWS, or GCP). • Docker, Kubernetes, CI/CD, and AI deployment practices. • Understanding of AI governance, security, and observability.
• Success Measures • Successful deployment of AI agents into production. • Improved automation and productivity through AI solutions. • High-quality, scalable, and secure AI implementations. • Adoption and business impact of delivered Agentic AI solutions.