Enterprise AI Implementation Engineer — Agentic AI Platforms

Pronix Inc; Hyderabad; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Pronix Inc. is seeking an experienced engineer to design and deliver production-grade AI, LLM and RAG solutions across global enterprises. The role involves hands-on work across leading agentic AI platforms and integration with enterprise data estates.

The ideal candidate has 5+ years in enterprise engineering and 3+ years delivering GenAI systems in production, with hands-on experience on major agentic AI platforms. You will drive security, cost tuning and knowledge transfer to client run teams.

Qualifications

• 5+ years enterprise engineering experience.
• 3+ years delivering AI/ML or GenAI in production.
• Hands-on with major agentic AI platforms (CRM/AI suites).

Responsibilities

• Build production AI agents — tool calling, orchestration, memory, prompts and guardrails; integrate with CRM and enterprise data estates.
• Implement RAG pipelines, evaluation frameworks, observability and agent integrations across platforms.
• Own CI/CD, security controls, cost tuning and knowledge transfer to customer run teams.

Skills

AI/ML in production

Agentic AI platforms

CI/CD

Security & governance

Tools

LangChain

LangGraph

Salesforce Agentforce

Job description

Design and deliver production-grade Agentic AI, LLM and RAG solutions for global enterprises, working hands-on across leading agentic AI platforms.

Responsibilities

• Build production AI agents — tool calling, multi-step orchestration, memory, prompts and guardrails — integrated with CRM, contact-center and enterprise data estates.
• Implement retrieval (RAG) pipelines, evaluation frameworks, observability and agent integrations across at least one major agentic AI platform.
• Own CI/CD, security controls, cost tuning and knowledge transfer to customer run teams.

Requirements

• 5+ years enterprise engineering; 3+ years delivering AI/ML or GenAI systems in production.
• Hands-on with at least one major agentic AI platform, such as Salesforce Agentforce, AWS Bedrock Agents/AgentCore, Kore.ai Agent Platform, Microsoft Copilot Studio, Google Vertex AI Agent Builder or LangGraph/LangChain.
• Strong grasp of security, PII handling, model risk and enterprise data governance.

Expected outcomes

• Ship production AI agents that meet agreed quality, latency and cost targets.
• Establish evaluation and observability so agent quality is measurable in production.
• Hand over well-documented systems that client run teams can operate independently.