Gen AI Engineer

We are seeking a hands-on AI Developer with 2-8 years of experience to join our fast-growing AI engineering team. You'll be part of a group delivering enterprise-grade GenAI solutions, AI agents, and cloud-native AI services using cutting-edge techniques including prompt engineering, MCP (Model Context Protocol), and MLOps.

You'll collaborate with senior AI engineers and architects, building scalable, intelligent applications that drive business impact across industries using OCI, Python, and LLM-based systems.

#LI-DNI

• Build and deliver AI Agents using GenAI frameworks, orchestrated through Model Context Protocol (MCP) to enable multi-step reasoning and tool invocation.
• Engineer prompt-based workflows, integrating LLMs with enterprise applications through REST APIs and OCI components.
• Develop and deploy AI models on OCI Functions, containerize them using OKE, and scale them through automated pipelines.
• Contribute to GenAI use case delivery across natural language querying, document intelligence, and process automation.
• Support MLOps practices for model versioning, continuous deployment, and monitoring in production.
• Write and optimize SQL queries and manage integration with structured data sources.
• Participate in system design, performance tuning, and end-user experience optimization for AI features.

Required Qualifications

• Master's degree in Artificial Intelligence, Machine Learning, Data Science, or a related field.
• 1-4 years of experience in Python development with exposure to ML/AI pipelines.
• Hands-on familiarity with Model Context Protocol (MCP) and AI Agent orchestration frameworks.
• Experience building solutions on Oracle Cloud Infrastructure (OCI) including Functions, OKE, and storage services.
• Strong understanding of prompt engineering, LLM APIs (OpenAI, Cohere, etc.), and embeddings.
• Proficiency with SQL, REST APIs, and containerized development (Docker/K8s).
• A passion for continuous learning, prototyping, and implementing state-of-the-art GenAI capabilities.

Nice-to-Have

• Exposure to LangChain, FastAPI, Streamlit, or UI frameworks for AI experience delivery.
• Past experience in production implementations of ML or GenAI features.
• Familiarity with model observability, vector databases, and secure AI deployment best practices.

Ideal Candidate Traits

• Builder's mindset with strong curiosity for emerging AI technologies and techniques.
• Ability to research, evaluate, and implement latest AI papers, tools, or APIs quickly.
• Comfortable switching contexts between coding, system debugging, and conceptual solutioning.
• Collaborative and proactive in team environments, with a strong sense of ownership.

Interview Process

• Round 1: Deep coding test - Python, logic, and ML patterns
• Round 2: Technical interview - MCP, AI Agent flow, prompt design, OCI skills
• Round 3 ( Optional) : Solution walkthrough - Design and delivery thinking
• Round 4 (Optional): Culture and growth alignment

#LI-DNI

Career Level - IC2