Description

Architect and build scalable AI solutions using modern LLM stacks and backend systems.

This role is on-site.

Responsibilities

• Design and implement backend systems using LangChain, RAG pipelines, and vector stores.
• Integrate LLMs (OpenAI, Gemini, Claude) with enterprise data sources and APIs.
• Develop modular agents and orchestrate workflows using tools like n8n, UIpath, or Haystack.
• Build telemetry dashboards to monitor AI implementations, track usage, and manage FinOps.
• Translate business requirements into scalable AI solutions in collaboration with developers.

Required Skills

• 2-5 years of backend engineering experience, including 2+ years in AI/ML systems.
• Proficiency in Python and frameworks like LangChain, FastAPI, and Flask.
• Experience with LLM orchestration, RAG, and vector databases.
• Familiarity with cloud platforms (AWS, GCP, Azure) and AI services (Bedrock, Vertex).
• Strong understanding of API integration, IAM, and secure data access protocols.
• Experience with ML Ops tools, context engineering, and prompt engineering.
• Knowledge of enterprise architecture, semantic search, and document intelligence.

Preferred Skills

• Experience with agentic AI frameworks and LCNC platforms.
• Understanding of AI governance, compliance, and enterprise scaling strategies.

Key Skills

Education

Any Gradute