AI Developer

What We Offer

• Work on impactful AI Project & Initiatives involving MCP, GenAI, and AI Agents.


• Mentorship from senior AI professionals working across LLMs, OCI, and MLOps pipelines.


• A culture of innovation, learning, and practical experimentation.


• Clear path to grow into AI Specialist or Technical Lead roles based on delivery excellence.

Career Level - IC1

Key Responsibilities

• 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.

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: Solution walkthrough Design and delivery thinking


• Round 4 (Optional): Culture and growth alignment