AI Interaction Engineer

XenonStack Moments; Sahibzada Ajit Singh Nagar; On-site; INR 1,000,000 - 1,200,000; Full time

Benefits offered by this job

Career Mobility & Growth

Global Exposure

Culture of Excellence

Job summary

A leading AI product company in Punjab is seeking an AI Interaction Engineer to design and optimize AI agent interactions within enterprise workflows. The role requires proficiency in LLM architectures and prompt engineering, focusing on compliance and optimization. Ideal for candidates with 2-4 years in AI/ML engineering, this full-time position offers significant career growth opportunities in a fast-paced environment.

Qualifications

• Strong understanding of LLM architectures, prompt engineering, and context window limits.
• Proficiency in Python with frameworks like LangChain, LangGraph, and LlamaIndex.
• Knowledge of enterprise AI governance, privacy, and compliance standards.

Responsibilities

• Design, test, and refine prompt strategies.
• Build pipelines integrating RAG, knowledge graphs, APIs.
• Optimize token usage and context for workflows.
• Develop reusable interaction templates.
• Implement safety and compliance guardrails.

Skills

2–4 years in AI/ML engineering, NLP, or enterprise software development

Strong understanding of LLM architectures

Hands-on with RAG pipelines

Proficiency in Python and frameworks like LangChain

Familiarity with enterprise AI governance

Job description

About Xenonstack

XenonStack is the fastest‑growing Data and AI Foundry for Agentic Systems, enabling people and organizations to gain real‑time and intelligent business insights.

We Deliver Innovation Through

• Agentic Systems for AI Agents → akira.ai
• Vision AI Platform → xenonstack.ai
• Inference AI Infrastructure for Agentic Systems → nexastack.ai

Our mission: Accelerate the world’s transition to AI + Human Intelligence by reimagining how enterprises adopt and scale agentic AI.

The Opportunity

We are seeking an AI Interaction Engineer to design, implement, and optimize the way AI agents understand, respond, and act within enterprise workflows. This role sits at the intersection of linguistics, context engineering, and enterprise AI systems. You will blend prompt engineering, context orchestration, and memory architecture to ensure large language models (LLMs) and multi‑agent systems are accurate, reliable, and compliant in production.

Key Responsibilities

• Prompt Engineering – Design, test, and refine prompt strategies to drive optimal agent behavior across diverse use cases.
• Context Orchestration – Build pipelines integrating RAG, knowledge graphs, APIs, and layered memory (short‑term, long‑term, episodic).
• Optimization – Optimize token usage and context allocation for long‑running, multi‑turn, and multi‑agent workflows.
• Reusable Blueprints – Develop reusable interaction templates and context blueprints for engineering and product teams.
• Compliance & Guardrails – Implement safety, compliance, tone, and brand guardrails in agent workflows.
• Continuous Improvement – Use execution traces, feedback, and automated evaluation to improve agent responses.
• Experimentation – Conduct A/B testing on prompt and context variations to measure accuracy, latency, and cost trade‑offs.
• Knowledge Management – Maintain a central library of tested interaction patterns and context management strategies.
• Research Tracking – Stay updated on multi‑agent orchestration frameworks and the state of AI interaction design.

Skills & Qualifications

Must‑Have

• 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.

Good‑to‑Have

• 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.

Why Join Us

• Agentic AI Product Company
• A Fast‑Growing Category Leader
• Career Mobility & Growth
• Global Exposure
• Create Real Impact
• Culture of Excellence
• Responsible AI First

Culture & Values

• Agency – Be self‑directed and proactive.
• Taste – Sweat the details and build with precision.
• Ownership – Take responsibility for outcomes.
• Mastery – Commit to continuous learning and growth.
• Impatience – Move fast and embrace progress.
• Customer Obsession – Always put the customer first.

Product Philosophy

• Obsessed with Adoption – Making AI accessible and enterprise‑ready.
• Obsessed with Simplicity – Turning complexity into seamless, intuitive AI experiences.

Seniority Level

Entry level

Employment Type

Full‑time

Job Function

Engineering and Information Technology

Industries

Software Development