AI Interaction Engineer
On-siteMohali, Punjab, India
Job Summary
Design, test, and refine prompt strategies to drive optimal agent behavior across diverse use cases. Build pipelines integrating RAG, knowledge graphs, APIs, and layered memory to ensure large language models and multi-agent systems are accurate and compliant in production. Optimize token usage and context allocation for long-running workflows, while developing reusable interaction templates and implementing safety guardrails. Conduct A/B testing on prompt and context variations to measure accuracy, latency, and cost trade-offs, using execution traces and automated evaluation to continuously improve agent responses. Maintain a central library of tested interaction patterns and stay updated on multi-agent orchestration frameworks. This role sits at the intersection of linguistics, context engineering, and enterprise AI systems for a fast-growing Data and AI Foundry focused on agentic systems.
Required Qualifications
- 2–4 years in AI/ML engineering, NLP, or enterprise software development
- Strong understanding of LLM architectures, prompt engineering, and context window limits
- Hands-on with RAG pipelines, vector databases, and knowledge graph integration
- Proficiency in Python and frameworks like LangChain, LangGraph, LlamaIndex
- Familiarity with enterprise AI governance, privacy, and compliance standards
- Proven ability to translate business objectives into structured AI interactions
Desired Qualifications
- Experience with multi-agent orchestration (MCP, A2A messaging, AgentBridge)
- Knowledge of reinforcement learning (RLHF, RLAIF, reward modeling)
- Exposure to edge AI deployment and quantized inference
- Domain knowledge in BFSI, GRC, SOC, or FinOps
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