Senior AI Product Engineer

Role Overview

Senior AI Product Engineer at Jodayn. The role is based at the company's location (not specified in the source).

Role Purpose

Lead the design, development, and deployment of enterprise-grade artificial intelligence solutions and intelligent automation platforms. The successful candidate will develop scalable AI-powered products and reusable enterprise AI services that support digital transformation, governance automation, proposal evaluation, intelligent document processing, and enterprise workflow optimisation.

Key Responsibilities

AI Platform Engineering

• Design, develop, and maintain scalable enterprise AI platforms and intelligent automation solutions.
• Build modular and reusable AI services and APIs.
• Develop AI-powered workflow automation systems and intelligent orchestration pipelines.
• Design and implement scalable backend architectures supporting AI workloads.

Agentic AI Development

• Build autonomous and semi-autonomous AI agents.
• Develop multi-agent orchestration workflows and task delegation systems.
• Implement memory management and contextual reasoning capabilities.
• Integrate AI systems with external tools, APIs, and enterprise applications.

Large Language Model Integration

• Integrate and optimise large language model services including Claude, OpenAI, and open-source models.
• Develop prompt orchestration pipelines and retrieval-augmented generation architectures.
• Implement vector database integration and semantic search capabilities.
• Optimise model performance, response quality, and operational efficiency.

Enterprise System Integration

• Integrate AI platforms with enterprise systems, collaboration tools, and document repositories.
• Develop secure API integration patterns.
• Support authentication and identity integration requirements.
• Build AI-enabled enterprise workflow capabilities.

Proposal & Compliance Automation

• Develop intelligent proposal generation and evaluation systems.
• Build compliance validation and document inspection workflows.
• Implement AI-assisted scoring and recommendation engines.
• Support enterprise governance automation initiatives.

Infrastructure & Deployment

• Deploy AI applications in cloud, hybrid, and on-premise environments.
• Configure logging, observability, monitoring, and operational diagnostics.
• Support containerisation and deployment automation practices.
• Optimise infrastructure scalability and operational cost efficiency.

Qualifications & Experience

• Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, or related field.
• Master's degree is preferred but not mandatory.
• Minimum 7 years of software engineering experience.
• Minimum 3 years practical experience developing AI-powered applications.
• Proven experience building and deploying production-grade AI systems.
• Experience working in enterprise or regulated environments preferred.

Skills & Competencies

Programming & Backend Development

• Python.
• FastAPI or equivalent backend frameworks.
• RESTful APIs.
• PostgreSQL or equivalent databases.
• Git and version control systems.

AI Technologies

• Claude APIs.
• OpenAI APIs.
• LangGraph.
• LangChain.
• Retrieval-Augmented Generation.
• Vector databases.
• Prompt orchestration.
• AI workflow automation.

Frontend & Integration

• React or Next.js.
• API integration.
• Authentication and access control concepts.

Infrastructure & DevOps

• Docker.
• Linux environments.
• CI/CD pipelines.
• Cloud deployment concepts.

Core Competencies

• Strong analytical and problem-solving skills.
• Ability to independently deliver complex technical solutions.
• Strong software design capability.
• Fast execution and delivery orientation.
• Excellent communication and documentation skills.
• Ability to work in fast-paced enterprise environments.

Preferred Skills

• Experience with enterprise AI governance solutions.
• Experience with intelligent document processing systems.
• Experience using AI-assisted development tools.
• Exposure to multi-agent systems and orchestration frameworks.
• Familiarity with enterprise architecture concepts.