Sr. Agentic AI(Python) Developer / Agentic AI Architect
Directly tied to vibe coding—building agentic AI and LLM-based agents, using prompt engineering, embeddings, and API-driven rapid demos.
About the Role
Senior Engineer focused on designing and delivering agentic GenAI solutions and pilots using Python and LLMs. The role builds end-to-end integrations, backend services, and lightweight front-end components to demonstrate AI-driven automation and conversational agent use cases for enterprise customers.
Job Description
Role
Senior Agentic AI Developer / Agentic AI Architect responsible for building pilot implementations and proof-of-value deployments of an enterprise AI platform. The role works closely with customers to translate business and technical problems into short‑timeline pilots that demonstrate GenAI/agentic capabilities and accelerate platform adoption.
Key Responsibilities
- Work directly with customers to understand business and technical problems and design pilot use cases.
- Design and build end-to-end pilot deployments, including backend services, integrations, and workflows.
- Leverage Generative AI and LLM capabilities (APIs, prompts, embeddings, agent patterns) to implement intelligent use cases.
- Integrate the platform with enterprise systems (ITSM, CRM, ERP, observability, databases) via REST APIs / ESB.
- Build or modify basic frontend components to support demos and customer workflows.
- Collaborate with Product Engineering to feed learnings back into the platform and support customer conversations on architecture and tradeoffs.
Requirements
- Strong backend development experience with hands-on Python coding.
- Experience with GenAI technologies and LLM APIs (examples listed: Claude, OpenAI, Azure OpenAI).
- Basic understanding of prompt engineering, retrieval-augmented generation (RAG), and agent-based patterns.
- Experience building integrations with enterprise systems (ITSM, observability, CRM, ERP) using REST APIs or ESB.
- Familiarity with databases, data pipelines, messaging systems, and cloud services (AWS, Azure, GCP).
- Exposure to cloud-native architectures (microservices, containers), DevOps practices (CI/CD, infrastructure as code), and observability.
- Strong debugging and problem-solving skills in ambiguous, customer-facing environments and prior experience in customer-facing engineering/support roles.
- Bachelor’s degree in Engineering or related field; relevant cloud/AI/architecture certifications are a plus.
Impact
- Deliver consistent, scalable user experiences across enterprise platforms, improve product usability and adoption, and accelerate customer value realization through pilot demonstrations.
Skills
Backend Development API Development Prompt Engineering Integration Design Cloud Architecture DevOps Observability Frontend Development (basic) Debugging Problem Solving Customer-facing Communication Collaboration Solution Design Self-directed Learning