Role Summary

GES is looking for an Engineer – AI and Engineering Technology to design, build, and operate production AI applications for enterprise use cases. This role combines hands-on AI/ML engineering with practical experience deploying agentic systems, retrieval-augmented generation (RAG) pipelines, and enterprise-integrated AI tools that run securely at scale. The ideal candidate has already shipped AI-powered products in a production environment and is comfortable owning a system end to end – from model selection and training through deployment, security, and cost management.

Key Responsibilities

• Design, develop, and deploy production AI applications for internal and external enterprise use cases, including retrieval-augmented generation (RAG) pipelines and agentic AI systems

• Build and maintain autonomous agents and multi-agent workflows using frameworks such as Lang Chain, Llama Index, and Model Context Protocol (MCP) integrations

• Train and fine-tune AI/ML models for specific enterprise use cases, and evaluate model performance for accuracy, safety, and cost

• Integrate AI systems with enterprise data sources and platforms (ERP, Share Point, ticketing systems) to ground responses in live business data

• Own the security and governance of deployed AI systems: guardrails, PII masking, role-based access control, sandboxed execution environments, and abuse prevention

• Deploy, monitor, and manage containerized AI services on cloud infrastructure (AWS or Azure), including cost optimization

• Work directly with business stakeholders to translate ambiguous requirements into deployed, measurable AI solutions





• Automate cross-functional workflows connecting AI systems with existing enterprise processes

Required Skills & Experience

• 4–6 years of overall experience in AI/ML or software engineering, with meaningful hands-on experience building and deploying AI applications in production

• Practical experience with large language models (LLMs) – OpenAI, Claude, Hugging Face, or equivalent

• Experience training or fine-tuning AI/ML models for specific use cases

• Hands-on experience building agentic AI systems, RAG pipelines, and LLM orchestration frameworks (Lang Chain, Llama Index, or similar)

• Working knowledge of Model Context Protocol (MCP) or similar tool-integration standards for connecting AI systems to enterprise data

• Robust programming skills in Python, with experience in FastAPI and REST API development

• Experience with containerized deployment (Docker) and cloud infrastructure (AWS or Azure)

• Understanding of AI security practices: guardrails, prompt safety, PII masking, and access control

• Demonstrated experience developing AI applications for enterprise customers or internal enterprise stakeholders

Preferred / Nice-to-Have Skills

• Experience with vector databases (Pinecone, Qdrant, Elasticsearch) for semantic search and retrieval

• Background in data engineering (Apache Spark, Databricks, Kafka) is a plus

• Familiarity with workflow automation tools (n8n or similar)

• Experience working in a consulting or client-facing engineering role across multiple industries

Education

• Bachelor's degree in Computer Science, Engineering, or a relat

📌 Engineer – AI and Engineering Technology (India)
🏢 HIRESTAR JOB BANK
📍 India